# MIRA AI Integration - 10 Major Tickets (1-Month Timeline) **Timeline:** 30 days (4 weeks) **Team Size:** 3-4 developers working in parallel **Priority Order:** CMS → CRM → Ecommerce → TalentIQ → Finance → Marketing --- ## 🏗️ TICKET 1: Foundation & AI Infrastructure **Epic ID:** MW-MIRA-001 **Priority:** CRITICAL **Estimate:** 6 days **Team:** Backend + AI Engineer **Dependencies:** None (blocking all other tickets) ### Overview Build the foundational infrastructure for MIRA including database schema, AI service layer, company context system, and core business intelligence engine. This is the backbone that all other modules will depend on. ### Detailed Scope **Database Architecture:** - Design and implement comprehensive database schema to support persistent AI conversations, message history, recommendations, nudges, user preferences, and analytics logs - Create models for conversations with company and user scoping, supporting both individual and team-based interactions - Build recommendations/nudges table with action tracking, dismissal reasons, and effectiveness metrics - Implement user settings table for MIRA preferences including tone preferences, notification settings, and module access controls - Create analytics logging system to track AI usage, token consumption, query performance, and business impact metrics - Establish proper indexes for performance optimization on high-volume tables - Set up soft deletes and audit trails for compliance and data recovery **AI Service Layer:** - Build core AI service infrastructure that interfaces with OpenAI GPT-4o-mini (current) with extensibility for future model upgrades - Implement company context builder that understands nonprofit vs for-profit branching, industry type, organization size, and mission focus - Create module data providers that can fetch real-time data from CRM, Donors, HR, Finance, Marketing, and CMS systems - Build PII detection and compliance wrapper to automatically redact sensitive information (SSN, credit cards, personal health info) - Implement token usage tracking and rate limiting per company with configurable thresholds and cost monitoring - Develop MIRA persona system supporting multiple tones (warm for donors, neutral for finance, supportive for HR) with context-aware tone switching - Create prompt engineering framework with reusable templates, variable substitution, and version control - Build response formatting system for structured outputs including tables, charts, action buttons, and embedded forms **Cross-Module Intelligence Core:** - Design data aggregation layer that can pull insights across multiple modules simultaneously - Implement caching strategy for frequently accessed data to improve response times - Build query optimization engine to minimize database load during AI operations - Create business rules engine for configurable logic (thresholds, scoring weights, alert conditions) **Security & Compliance:** - Implement row-level security ensuring users only see data they have permission to access - Build audit logging for all AI interactions including inputs, outputs, and actions taken - Create data retention policies with automatic cleanup of old conversations and analytics - Implement encryption for sensitive AI data at rest and in transit **Testing & Quality:** - Unit tests for all AI service components with 80%+ code coverage - Integration tests for cross-module data fetching - Load testing to ensure system handles 100+ concurrent AI requests - Validation of PII detection accuracy with test datasets ### Success Criteria - Database migrations run successfully across all environments - AI service can successfully process requests with company context - Module data providers return accurate real-time data - PII detection catches 95%+ of sensitive information - Token usage tracked accurately per company - System handles 100 concurrent AI requests without degradation - All tests passing with 80%+ coverage ### Future Sub-Tickets - Enhanced caching strategies - Multi-language support - Advanced PII detection models - Custom AI model fine-tuning - Performance optimization --- ## 🎨 TICKET 2: CMS Intelligence Integration **Epic ID:** MW-MIRA-002 **Priority:** CRITICAL **Estimate:** 5 days **Team:** Full-Stack Developer **Dependencies:** MW-MIRA-001 ### Overview Integrate MIRA with the existing CMS system (current priority per boss directive) to enable AI-powered content analysis, recommendations, generation, and optimization for blogs, pages, menus, and all content types. ### Detailed Scope **CMS Data Provider:** - Build comprehensive CMS data provider that interfaces with pages, blog posts, menus, post types, and CMS settings - Implement content metadata extraction including publish dates, authors, categories, tags, and custom fields - Create content performance tracking integration pulling view counts, engagement metrics, time-on-page, and bounce rates - Build revision history access for content change tracking and version comparison - Implement media library integration for image and file analysis **Content Analytics Engine:** - Develop content performance scoring algorithm considering views, engagement, social shares, and conversion rates - Build content gap analysis identifying missing topics, thin content, and optimization opportunities - Create SEO scoring system analyzing keyword usage, meta descriptions, header structure, and internal linking - Implement readability analysis using Flesch-Kincaid scores, sentence complexity, and paragraph length - Build content freshness tracking to identify outdated content requiring updates - Create competitor content analysis comparing against industry benchmarks **AI Content Generation:** - Implement natural language content generation for 9 content types: blogs, pages, emails, social posts, SMS, press releases, newsletters, landing pages, and product descriptions - Build template management system with industry-specific templates for nonprofit and for-profit organizations - Create content brief analysis that extracts key points, tone, and structure from user prompts - Implement multi-stage content generation with outline creation, draft generation, and refinement - Build content variation generator for A/B testing different headlines, intros, and calls-to-action - Create content repurposing engine that transforms blogs into social posts, emails into landing pages, etc. **Content Recommendations:** - Build recommendation engine suggesting optimal posting times based on historical engagement - Implement topic suggestions based on trending keywords, audience interests, and content gaps - Create content optimization suggestions for improving SEO, readability, and engagement - Build internal linking recommendations to improve site structure and SEO - Implement content refresh alerts for outdated or underperforming content **Integration Points:** - Deep integration with Create module for content generation interface - Real-time content analytics display in Analyze module - Content recommendations surfaced in Advise module - Attention cards in Hub for urgent content opportunities (trending topics, viral potential) **Quality & Performance:** - Content generation completes within 5 seconds for standard pieces - SEO scoring runs in under 1 second per page - Recommendations update daily or on-demand - Generated content maintains consistent brand voice and tone ### Success Criteria - MIRA can read, analyze, and understand all CMS content types - Content performance metrics display accurately in real-time - AI can generate high-quality content across all 9 content types - SEO and readability scores match industry-standard tools within 10% - Content recommendations are actionable and relevant - Users can generate and publish content directly from MIRA - Analytics reflect actual CMS performance data (not mock data) - System handles analysis of 10,000+ content pieces without slowdown ### Future Sub-Tickets - Multi-language content generation - Advanced plagiarism detection - Content workflow automation - Editorial calendar integration - Social media scheduling --- ## 💼 TICKET 3: CRM & Lead Intelligence System **Epic ID:** MW-MIRA-003 **Priority:** HIGH **Estimate:** 6 days **Team:** Backend + Frontend Developer **Dependencies:** MW-MIRA-001 ### Overview Implement AI-powered CRM intelligence including lead scoring, pipeline health analysis, capacity planning, next-best-action recommendations, and the Pipeline → Capacity → Staffing → Delivery → Margin logic flow. ### Detailed Scope **CRM Data Provider:** - Build comprehensive CRM data provider accessing leads, contacts, accounts, opportunities, stages, statuses, follow-ups, activities, sources, and agents - Implement lead timeline tracking capturing all interactions, emails, calls, meetings, and notes - Create engagement scoring based on email opens, link clicks, form submissions, and website activity - Build lead source attribution tracking conversion rates and ROI per channel - Implement team performance metrics tracking agent activity, conversion rates, and pipeline velocity **AI Lead Scoring Engine:** - Develop multi-factor lead scoring algorithm considering engagement recency, interaction frequency, demographic fit, behavioral signals, and company size - Build hot/warm/cold classification with real-time updates as lead behaviors change - Implement likelihood-to-convert predictions using historical conversion patterns and current engagement levels - Create deal size prediction models based on company size, industry, and historical deal values - Build time-to-close estimates based on stage velocity and historical patterns - Implement churn risk detection for existing customers showing declining engagement **Pipeline Health Analytics:** - Build comprehensive pipeline visualization showing leads across all stages with values and probabilities - Implement stage velocity tracking measuring average time in each stage and identifying bottlenecks - Create pipeline coverage analysis comparing pipeline value to quota and identifying gaps - Build win rate analysis by stage, source, agent, and time period - Implement deal momentum tracking identifying accelerating and stalling opportunities - Create pipeline forecasting with confidence intervals based on historical close rates **Capacity Intelligence (Workforce OS Logic):** - Implement Pipeline → Capacity → Staffing → Delivery → Margin flow visualization showing business health metrics - Build capacity gap analysis comparing current pipeline demands against available staff hours and skill sets - Create staffing risk alerts when pipeline volume exceeds team capacity by configurable thresholds - Implement delivery feasibility scoring assessing whether team can successfully deliver on pipeline commitments - Build margin impact modeling showing profitability implications of capacity decisions - Create workload balancing recommendations distributing leads and opportunities across team members - Implement hiring timeline suggestions based on pipeline growth trajectories and capacity constraints **Next-Best-Action Recommendations:** - Build AI recommendation engine suggesting optimal actions for each lead based on stage, engagement, and historical success patterns - Implement follow-up timing suggestions based on engagement patterns and optimal contact windows - Create email draft generation for outreach, follow-ups, proposals, and contract negotiations - Build cross-sell and upsell opportunity identification for existing customers - Implement at-risk lead alerts for opportunities showing stalling signals or declining engagement - Create meeting agenda suggestions based on lead stage and previous interactions **CRM Smart Insights:** - Build anomaly detection identifying unusual patterns in pipeline behavior - Implement competitive intelligence alerts monitoring win/loss patterns against specific competitors - Create seasonal trend analysis identifying cyclical patterns in lead flow and conversion - Build territory analysis showing geographic performance and opportunity concentration ### Success Criteria - Every lead has an AI-calculated score that updates in real-time based on engagement - Lead scores correlate with actual conversion rates within 15% accuracy - Pipeline health dashboard provides actionable insights on bottlenecks and risks - Pipeline → Capacity → Staffing → Delivery → Margin flow visible in Hub with real-time data - Capacity alerts trigger automatically when thresholds breached - Staffing recommendations appear in Advise with cost and margin impact estimates - Next-best-action recommendations achieve 30%+ adoption rate by sales team - Email drafts generated in under 3 seconds with appropriate tone and content - Margin impact calculations accurate within 10% of actual profitability - CRM data queryable via chat with natural language (e.g., "Show me hot leads in California") ### Future Sub-Tickets - Advanced forecasting models - Competitive intelligence integration - Sales playbook recommendations - Meeting transcription and analysis - Social selling signals --- ## 🛒 TICKET 4: Ecommerce & Revenue Intelligence **Epic ID:** MW-MIRA-004 **Priority:** HIGH **Estimate:** 6 days **Team:** Backend + Analytics Developer **Dependencies:** MW-MIRA-001 ### Overview Build comprehensive ecommerce intelligence covering product performance, revenue analytics, customer insights, inventory management, cart abandonment recovery, and customer lifetime value predictions. ### Detailed Scope **Ecommerce Data Provider:** - Build comprehensive store data provider accessing products, variants, categories, attributes, inventory, orders, order items, carts, cart abandonment data, and customer purchase history - Implement real-time inventory tracking with stock levels, reorder points, and supplier lead times - Create customer behavior tracking capturing browse patterns, cart additions, abandonments, and purchase sequences - Build pricing history tracking monitoring price changes, discount effectiveness, and margin impact - Implement shipping and fulfillment data integration tracking delivery times, costs, and customer satisfaction **Product Performance Analytics:** - Develop product performance scoring considering sales velocity, revenue contribution, profit margins, inventory turnover, and return rates - Build best/worst performer identification with automatic categorization and trend analysis - Implement product lifecycle tracking identifying introduction, growth, maturity, and decline phases - Create product recommendation engine suggesting what to promote, discount, or discontinue - Build variant performance analysis comparing sizes, colors, and configurations - Implement category performance tracking identifying winning and losing product categories - Create seasonal trend analysis predicting demand spikes and planning inventory accordingly **Inventory Intelligence:** - Build smart inventory alerts triggering notifications for low stock (below reorder point), overstock (above maximum threshold), and dead stock (no sales in 90 days) - Implement reorder point calculations based on sales velocity, lead times, and buffer stock requirements - Create stock-out prediction models forecasting when products will go out of stock based on current velocity - Build overstock identification suggesting products to discount or bundle to clear excess inventory - Implement inventory value optimization balancing carrying costs against stockout risks **Revenue & Order Analytics:** - Build comprehensive revenue dashboard showing daily, weekly, monthly, quarterly, and annual trends with year-over-year comparisons - Implement revenue forecasting using historical trends, seasonality, and current pipeline - Create average order value (AOV) tracking with trend analysis and improvement recommendations - Build order frequency analysis identifying purchase cycles and optimal remarketing timing - Implement payment analysis tracking payment methods, success rates, and processing costs - Create profitability analysis showing gross margins, net margins, and contribution margins by product, category, and customer segment **Customer Insights & LTV:** - Develop customer lifetime value (LTV) prediction models based on purchase frequency, average order value, retention rates, and customer lifespan estimates - Build customer segmentation engine creating high-value, at-risk, new, loyal, and churned segments - Implement RFM analysis (Recency, Frequency, Monetary) for targeted marketing - Create purchase pattern analysis identifying cross-sell and upsell opportunities - Build cohort analysis tracking customer behavior over time - Implement churn prediction identifying customers at risk of not returning **Cart Abandonment Recovery:** - Build cart abandonment tracking capturing abandoned items, cart values, and abandonment timestamps - Implement automated recovery recommendation system suggesting optimal follow-up timing and messaging - Create personalized recovery email generation with cart contents, urgency messaging, and incentive suggestions - Build abandonment reason analysis through exit surveys and behavioral signals - Implement conversion rate optimization identifying friction points in checkout process **ProductPitch (AI Content Generation):** - Build AI-powered product description generator creating SEO-optimized, compelling copy from product attributes - Implement multi-variant description generation for A/B testing - Create feature-benefit transformation turning technical specs into customer-focused benefits - Build competitive differentiation highlighting unique selling propositions - Implement tone variation for different customer segments (B2B vs B2C, luxury vs value) ### Success Criteria - Product performance analytics update in real-time or within 5 minutes of sales - Inventory alerts trigger automatically within 1 minute of threshold breach - Revenue forecasts accurate within 15% of actual results over rolling 30-day period - Customer LTV predictions within 20% accuracy validated over 6-month period - Cart abandonment recovery recommendations shown within 30 minutes of abandonment - Recovery emails generate automatically with personalized content - ProductPitch generates descriptions in under 5 seconds that are SEO-optimized and compelling - All ecommerce metrics queryable via chat (e.g., "What are my top products this month?") - Customer segmentation updates daily automatically - Dashboard loads in under 2 seconds with full data visualization ### Future Sub-Tickets - Dynamic pricing optimization - Bundle and cross-sell recommendations - Supplier performance tracking - Fraud detection - Returns and refunds analysis --- ## 👥 TICKET 5: TalentIQ & HR Intelligence **Epic ID:** MW-MIRA-005 **Priority:** MEDIUM **Estimate:** 5 days **Team:** Backend Developer **Dependencies:** MW-MIRA-001 ### Overview Implement recruitment intelligence (HireAssist), workforce capacity planning, staffing risk management, candidate scoring, skill gap analysis, retention predictions, and compliance-focused HR analytics. ### Detailed Scope **HR Data Provider:** - Build comprehensive HR data provider accessing employee records, candidate database, job openings, applications, interviews, skills, documents, shifts, attendance, and performance data - Implement privacy-first design with PII protection, data anonymization for analytics, and role-based access controls - Create recruitment pipeline tracking from application through offer acceptance - Build skill inventory system cataloging team capabilities and certifications - Implement time-tracking integration for workload and capacity analysis **Recruitment Intelligence (HireAssist):** - Develop AI candidate scoring model evaluating experience fit, skill match, culture alignment, and compensation expectations - Build job-candidate matching recommendations using semantic analysis of resumes against job descriptions - Implement qualification scoring highlighting must-have vs. nice-to-have criteria fulfillment - Create interview question generator suggesting role-specific questions based on candidate background and job requirements - Build resume parsing and standardization extracting structured data from diverse resume formats - Implement candidate pipeline analytics tracking time-to-hire, stage conversion rates, and bottleneck identification - Create interview feedback analysis aggregating interviewer ratings and sentiment - Build offer acceptance prediction based on candidate engagement, compensation competitiveness, and historical patterns **Staffing & Capacity Intelligence:** - Implement workforce capacity dashboard showing current headcount vs. needed capacity across departments and roles - Build workload analysis tracking actual work hours, project commitments, and available capacity - Create staffing risk alerts identifying understaffed teams, overworked employees, and capability gaps - Implement scenario modeling showing impact of hiring decisions on capacity and costs - Build hiring timeline recommendations suggesting when to start recruitment based on lead times and capacity needs - Create span of control analysis identifying management capacity issues - Implement overtime tracking and cost analysis **Skill Gap Analysis:** - Build skills inventory comparing current team capabilities against project and pipeline requirements - Implement gap identification highlighting missing critical skills - Create training recommendations suggesting courses, certifications, or knowledge transfers to close gaps - Build succession planning identifying backup coverage for critical roles - Implement skills trending analysis predicting future capability needs based on business trajectory **Workforce Analytics:** - Develop retention risk scoring identifying flight-risk employees based on tenure, engagement, performance, and external factors - Build turnover prediction modeling future attrition rates and replacement costs - Implement engagement trend analysis tracking satisfaction, burnout indicators, and team morale - Create performance distribution analysis identifying high performers, solid contributors, and underperformers - Build diversity analytics tracking representation across dimensions with goal achievement monitoring - Implement compensation equity analysis identifying pay disparities requiring attention **Compliance & Privacy:** - Build separate analytics layer with full anonymization for workforce trends that doesn't expose individual identities - Implement access controls ensuring only authorized users see individual employee data - Create audit logging for all HR data access and AI interactions - Build GDPR/privacy compliance checks flagging risky data usage - Implement data retention policies with automatic cleanup ### Success Criteria - Candidate scoring model achieves 70%+ correlation with actual hire success (measured over time) - Job-candidate matching recommendations reduce time-to-hire by 15%+ - Staffing risk alerts trigger proactively before capacity issues impact delivery - Skill gap analysis accurately identifies critical capability shortages - Retention risk predictions achieve 65%+ accuracy (validated over 6 months) - All HR analytics fully anonymized except for users with explicit permission - PII detection catches 98%+ of sensitive data with 0 false negatives for highly sensitive info (SSN, health records) - Capacity dashboard updates in real-time as project assignments change - Interview question generator produces role-relevant questions in under 3 seconds - Hiring timeline recommendations align with business capacity needs ### Future Sub-Tickets - Learning and development recommendations - Career pathing suggestions - Compensation benchmarking - Employee engagement surveys analysis - Benefits optimization --- ## 💰 TICKET 6: Finance & Donation Intelligence **Epic ID:** MW-MIRA-006 **Priority:** MEDIUM **Estimate:** 6 days **Team:** Backend + Finance Specialist **Dependencies:** MW-MIRA-001 ### Overview Build financial intelligence covering revenue tracking, invoice management, payment health, cash flow forecasting, budget analysis, margin calculations, and nonprofit-specific donor intelligence including DonorPulse lapse prediction. ### Detailed Scope **Finance Data Provider:** - Build comprehensive finance data provider accessing invoices, invoice items, payments, payment pages, expenses, budgets, financial accounts, and transaction history - Implement nonprofit-specific provider for donations, donation categories, donor records, giving history, and campaign financials - Create real-time financial data synchronization ensuring accuracy within 5 minutes - Build multi-currency support for international operations - Implement fiscal year and reporting period configurations **Revenue & Financial Analytics:** - Build comprehensive revenue dashboard tracking by source (products, services, donations, grants), time period, customer/donor segment, and geographic region - Implement revenue forecasting using historical trends, pipeline data, seasonality patterns, and growth trajectories - Create revenue recognition tracking for subscription and recurring revenue models - Build revenue concentration analysis identifying dependence on key customers or donors (risk management) - Implement month-over-month and year-over-year comparison analytics with variance explanation - Create revenue attribution tracking source of income to marketing campaigns, sales efforts, or fundraising activities **Invoice & Payment Intelligence:** - Build invoice analytics tracking outstanding invoices, overdue amounts, days sales outstanding (DSO), and collection efficiency - Implement payment health scoring for customers based on payment history, timeliness, and outstanding balances - Create automated collection reminders with AI-generated messaging appropriate to customer relationship and overdue severity - Build payment prediction models forecasting when invoices likely to be paid based on historical patterns - Implement early payment discount optimization suggesting optimal discount rates to accelerate cash flow - Create bad debt prediction identifying invoices at risk of non-payment **Cash Flow Intelligence:** - Develop cash flow forecasting projecting inflows and outflows over 30, 60, 90-day horizons - Build cash position modeling showing impact of payment timing, expenses, and planned investments - Implement liquidity alerts warning of potential cash shortfalls before they occur - Create working capital optimization recommendations balancing receivables, payables, and inventory - Build seasonal cash flow analysis identifying predictable cycles and planning accordingly **Budget Management:** - Implement budget vs. actuals tracking showing variance by category, department, and time period - Build variance alert system triggering notifications when actuals exceed budget by configurable thresholds (e.g., 10%) - Create spend rate analysis projecting annual spend based on current burn rate - Implement budget reallocation recommendations suggesting optimal resource deployment - Build scenario analysis modeling impact of budget changes on business outcomes **Margin Analysis:** - Develop margin tracking by product, service, customer, project, campaign, and business unit - Build contribution margin analysis showing profitability after variable costs - Implement margin trend analysis identifying improving or declining profitability - Create pricing optimization recommendations to improve margins without sacrificing volume - Build cost structure analysis identifying fixed vs. variable cost ratios and optimization opportunities **FinanceNarrator:** - Build natural language financial summary generator creating plain-English explanations of financial performance - Implement key metrics extraction highlighting most important financial indicators - Create narrative generation explaining trends, variances, and notable changes in accessible language for non-financial stakeholders - Build executive summary generator for board reports and investor updates - Implement anomaly explanation providing context for unexpected financial results **DonorPulse (Nonprofit Intelligence):** - Develop donor lapse prediction model identifying donors at risk of not giving again based on recency of last gift, historical frequency, donation amount trends, and engagement levels - Build at-risk donor scoring with confidence percentages and recommended intervention timing - Implement giving trend analysis tracking frequency, amounts, channels, and campaign responsiveness per donor - Create major gift identification flagging donors showing increasing capacity and inclination signals - Build campaign effectiveness ROI analysis comparing costs to donations generated with lifetime value impact - Implement recurring vs. one-time donor analysis showing stability of revenue base - Create donor retention tracking and churn analysis - Build monthly giving upgrade recommendations identifying one-time donors likely to convert to recurring **Nonprofit-Specific Analytics:** - Implement grant tracking with deadline alerts, reporting requirements, and utilization monitoring - Build restricted vs. unrestricted fund analysis ensuring proper allocation and compliance - Create program cost allocation supporting accurate indirect rate calculations - Build fundraising efficiency metrics calculating cost per dollar raised - Implement donor stewardship tracking ensuring appropriate recognition and engagement ### Success Criteria - Revenue dashboard displays accurate real-time financial data - Revenue forecasts within 15% accuracy over rolling 90-day period - Invoice analytics accurately identify high-risk accounts with 75%+ precision - Cash flow forecasts within 20% accuracy over 30-day horizon - Budget variance alerts trigger automatically within 1 hour of threshold breach - FinanceNarrator summaries generate in under 10 seconds with clear, accurate explanations - Margin analysis calculations match manual financial reports exactly - DonorPulse predictions achieve 70%+ accuracy in identifying lapsing donors - At-risk donor alerts enable proactive retention efforts reducing lapse rate by 10%+ - Campaign ROI tracking provides actionable insights for fundraising optimization - All financial data queryable via chat with natural language - Financial analytics comply with GAAP/nonprofit accounting standards ### Future Sub-Tickets - Advanced forecasting with ML models - Tax planning and optimization - Financial consolidation across entities - Audit preparation assistance - Investment portfolio analysis --- ## 📢 TICKET 7: Marketing & Campaign Intelligence **Epic ID:** MW-MIRA-007 **Priority:** MEDIUM **Estimate:** 5 days **Team:** Full-Stack Developer **Dependencies:** MW-MIRA-001 ### Overview Implement marketing intelligence including campaign performance tracking, email analytics, sentiment analysis, engagement predictions, A/B test recommendations, audience segmentation, automation performance, and CampaignCoach recommendations. ### Detailed Scope **Marketing Data Provider:** - Build comprehensive marketing data provider accessing campaigns, campaign pages, email sends, opens, clicks, conversions, automation workflows, automation logs, contact lists, and engagement history - Implement integration with email service providers (ESP) for real-time engagement data - Create social media integration pulling post performance, engagement, and follower data - Build advertising platform integration for paid campaign performance (Google Ads, Facebook Ads) - Implement UTM parameter tracking for comprehensive attribution **Campaign Performance Analytics:** - Build campaign dashboard tracking open rates, click-through rates (CTR), conversion rates, unsubscribe rates, bounce rates, and engagement scores - Implement benchmarking comparing performance against industry averages and historical campaigns - Create campaign effectiveness scoring with AI-powered assessment of creative, targeting, timing, and messaging - Build multi-touch attribution modeling showing campaign contribution to conversions across journey - Implement cost-per-acquisition (CPA) and return on ad spend (ROAS) tracking for paid campaigns - Create campaign comparison analysis showing performance across time periods, segments, and channels **CampaignCoach (AI Recommendations):** - Develop AI recommendation engine analyzing campaign performance and suggesting optimizations - Build subject line optimization suggesting higher-performing alternatives with predicted open rate lifts - Implement content recommendations analyzing message effectiveness and suggesting improvements - Create timing optimization identifying best send times based on audience engagement patterns - Build frequency optimization balancing engagement against fatigue and unsubscribe risk - Implement creative recommendations suggesting imagery, layout, and call-to-action improvements - Create personalization suggestions identifying opportunities for dynamic content and segmentation **Email Intelligence:** - Build detailed email performance tracking at campaign, email, and recipient levels - Implement email engagement scoring tracking overall recipient interaction levels - Create inbox placement monitoring tracking deliverability rates and spam folder placement - Build list health tracking monitoring bounce rates, complaint rates, and engagement decay - Implement sender reputation monitoring ensuring optimal deliverability - Create re-engagement campaign recommendations identifying inactive subscribers and suggesting win-back strategies **SentimentScope (Sentiment Analysis):** - Develop sentiment analysis engine processing email replies, social media comments, and customer feedback - Build real-time sentiment scoring showing positive, negative, and neutral response distribution - Implement trend analysis tracking sentiment changes over time and by campaign - Create alert system flagging negative sentiment spikes requiring immediate response - Build topic extraction identifying common themes in customer responses - Implement competitive sentiment comparing brand sentiment against competitors **Engagement Predictions:** - Develop predictive models forecasting who will open, click, and convert based on historical behavior, profile data, and campaign characteristics - Build engagement score per contact predicting future interaction likelihood - Implement send-time optimization using predicted optimal engagement windows per recipient - Create churn prediction identifying contacts at risk of disengagement - Build conversion likelihood scoring for targeting highest-probability prospects **Audience Segmentation:** - Implement AI-powered audience segmentation creating behavioral, demographic, and psychographic segments - Build segment performance analysis showing which segments respond best to different message types - Create lookalike audience recommendations identifying prospects similar to best customers - Implement dynamic segmentation with real-time updates as behaviors change - Build segment health tracking monitoring size, engagement, and revenue contribution per segment **Marketing Automation Intelligence:** - Build automation performance dashboard tracking trigger rates, conversion rates, revenue generated, and ROI per workflow - Implement bottleneck identification showing where contacts drop out of automation flows - Create optimization recommendations suggesting trigger refinements, timing adjustments, and content improvements - Build automation comparison analysis showing relative performance across workflows - Implement automation ROI calculation showing time saved, revenue generated, and cost efficiency **A/B Testing Intelligence:** - Build A/B test recommendation engine suggesting high-impact test opportunities - Implement statistical significance calculation ensuring valid test results - Create test result analysis with clear winning variant identification and expected impact - Build test idea generator suggesting creative, subject line, timing, and targeting tests - Implement progressive testing roadmap prioritizing tests by potential impact ### Success Criteria - Campaign performance dashboard displays real-time metrics updated within 5 minutes - CampaignCoach recommendations improve campaign performance by 15%+ when implemented - A/B test suggestions are statistically valid and actionable - Engagement predictions achieve 70%+ accuracy in forecasting opens and clicks - SentimentScope accurately classifies sentiment with 80%+ precision - Send-time optimization improves open rates by 10%+ compared to standard send times - Audience segmentation creates meaningful, actionable segments with distinct behaviors - Automation performance tracking identifies bottlenecks and optimization opportunities - All marketing data queryable via chat (e.g., "Show me my top performing campaigns this quarter") - Email deliverability monitoring catches issues within 1 hour ### Future Sub-Tickets - Advanced attribution modeling - Predictive lead scoring integration - Social listening and monitoring - Influencer identification - Content calendar optimization --- ## 🎯 TICKET 8: MIRA Command Center (Hub Dashboard) **Epic ID:** MW-MIRA-008 **Priority:** HIGH **Estimate:** 5 days **Team:** Frontend + Backend Developer **Dependencies:** MW-MIRA-001, MW-MIRA-002 (CMS for initial data) ### Overview Build the MIRA Command Center dashboard featuring the 4 intelligence engines (Growth, Relationship, Execution, Revenue), Pipeline → Capacity → Staffing → Delivery → Margin flow visualization, attention cards for urgent priorities, KPI tracking, and recent AI outputs panel. ### Detailed Scope **Hub Architecture:** - Design responsive dashboard layout optimized for desktop (primary) and tablet viewing - Implement modular card-based architecture allowing customization and rearrangement - Build real-time data refresh system updating metrics every 30 seconds without full page reload - Create dashboard personalization allowing users to customize visible widgets and priority metrics - Implement role-based dashboard views showing relevant metrics per user role (executive, manager, individual contributor) **4 Intelligence Engines:** **Growth Engine:** - Build metrics tracking pipeline growth, lead acquisition rates, website traffic trends, content performance, and market expansion - Implement lead velocity rate (LVR) showing acceleration or deceleration of pipeline growth - Create opportunity dashboard showing new business opportunities by source, stage, and value - Build growth forecast showing projected revenue growth based on current trajectory - Implement growth levers analysis identifying top drivers of growth (marketing, sales, content, referrals) **Relationship Engine:** - Build metrics tracking customer health scores, donor engagement, retention rates, churn risk, and lifetime value trends - Implement relationship strength indicators showing engagement levels per key account or donor - Create at-risk relationship alerts flagging accounts or donors showing declining engagement - Build relationship timeline showing recent interactions, upcoming touchpoints, and relationship milestones - Implement net promoter score (NPS) or satisfaction tracking with trend analysis **Execution Engine:** - Build metrics tracking project completion rates, task velocity, deadline adherence, and team productivity - Implement capacity utilization showing percentage of team capacity allocated vs. available - Create bottleneck identification highlighting workflow slowdowns and blockers - Build delivery risk tracking showing projects at risk of missing deadlines - Implement automation efficiency metrics showing time saved and error reduction from automations **Revenue Engine:** - Build metrics tracking revenue performance, margin trends, cash flow health, and financial forecasts - Implement revenue pacing showing progress toward targets with on-track/behind/ahead indicators - Create deal close rate tracking and win/loss analysis - Build profitability tracking showing gross margin, net margin, and EBITDA trends - Implement cash runway calculation showing months of operations supported by current cash position **Pipeline → Capacity → Staffing → Delivery → Margin Flow:** - Build visual flow diagram showing: - **Pipeline:** Total value of opportunities in pipeline with stage breakdown - **Capacity:** Current team capacity to handle pipeline commitments - **Staffing:** Current headcount vs. needed headcount with gap identification - **Delivery:** Feasibility assessment of delivering on pipeline commitments - **Margin:** Projected profitability of pipeline at current staffing levels - Implement interactive flow allowing drill-down into each stage for detailed analysis - Create alert indicators on flow showing red/yellow/green status for each stage - Build flow optimization recommendations suggesting adjustments to improve end-to-end health **Attention Cards:** - Build dynamic attention card system surfacing top 3-5 priorities requiring immediate action - Implement card types: urgent opportunities (hot leads, expiring deals), critical risks (capacity shortfalls, at-risk customers), compliance alerts (overdue tasks, required actions), and optimization opportunities (high-impact improvements) - Create card prioritization algorithm ranking by impact, urgency, and effort required - Build card dismissal and snooze functionality with tracking of ignored recommendations - Implement action buttons in cards enabling one-click response to recommendations **KPI Visualization:** - Build customizable KPI panel showing 6-10 key metrics most important to user or organization - Implement metric widgets with current value, trend indicator (up/down), percentage change, and sparkline visualization - Create goal tracking showing progress toward targets with visual indicators - Build drill-down capability allowing click-through to detailed analytics - Implement comparison modes showing metrics against previous period, plan/budget, or benchmarks **Recent AI Outputs Panel:** - Build activity feed showing last 10-20 AI interactions including content generated, analyses run, automations created, and recommendations provided - Implement quick access links allowing users to revisit or continue previous AI sessions - Create sharing functionality for interesting AI outputs - Build favorites/save system for important AI interactions **Dashboard Performance:** - Implement aggressive caching strategy ensuring dashboard loads in under 2 seconds - Build progressive loading showing critical metrics first while others load in background - Create offline capability displaying last-loaded data when connection unavailable - Implement error handling with graceful degradation when specific data sources unavailable **Design System Integration:** - Apply Missio design system: Teal (#1A5F7A or brand teal), Gold (#D4AF37 or brand gold), Dark Ink (#1C1C1C) color scheme - Maintain consistency with https://designs.missio.io/missiostatic/missio-marketing.html - Implement smooth animations and transitions for card interactions - Build responsive charts and visualizations using modern charting libraries - Create accessible UI meeting WCAG 2.1 AA standards ### Success Criteria - Dashboard loads in under 2 seconds with full data visualization - 4 engine cards display real data from respective modules (starting with CMS, expanding as other modules complete) - Pipeline flow visualization accurately reflects business health across all stages - Attention cards surface truly high-priority items with 80%+ relevance rating from users - KPIs update in real-time or within 30 seconds of underlying data changes - Dashboard is responsive and functional on desktop and tablet devices - Design matches Missio brand guidelines with teal, gold, and dark ink color scheme - Users can customize dashboard layout and visible widgets - Recent AI outputs panel provides quick access to previous interactions - All dashboard elements accessible via keyboard navigation ### Future Sub-Tickets - Advanced data visualizations - Custom dashboard builder - Mobile app version - Dashboard sharing and permissions - Export dashboard as PDF --- ## 💬 TICKET 9: Persistent Chat & Global Side Panel **Epic ID:** MW-MIRA-009 **Priority:** HIGH **Estimate:** 6 days **Team:** Full-Stack Developer **Dependencies:** MW-MIRA-001, MW-MIRA-002 (for initial CMS context) ### Overview Build the persistent, context-aware MIRA chat system with global side panel accessible from anywhere in the portal, featuring conversation memory, context detection, natural language querying, action execution, and streaming responses. ### Detailed Scope **Chat Backend Infrastructure:** - Build comprehensive chat API supporting message sending, conversation retrieval, history management, and conversation deletion - Implement conversation threading allowing multiple concurrent conversations per user - Create message storage system with full conversation history, timestamps, user/AI attribution, and metadata - Build context capture system recording which page, module, and data user was viewing when chat initiated - Implement conversation tagging and categorization for organization and search - Create conversation sharing functionality allowing users to share insights with team members - Build conversation export system generating PDF/DOCX reports from chat sessions **Natural Language Processing:** - Implement intent recognition determining whether user wants to generate content, analyze data, get recommendations, create automation, or general question - Build entity extraction identifying specific data references (lead names, product IDs, date ranges, amounts) - Create query understanding that translates natural language into database queries (e.g., "Show leads from California" → database filter) - Implement ambiguity resolution asking clarifying questions when intent unclear - Build multi-turn conversation support maintaining context across multiple exchanges - Create conversation memory allowing MIRA to reference previous messages in same session **Context Intelligence:** - Build automatic context detection identifying current module (CRM, Ecommerce, Finance, etc.), specific page (lead detail, product page), and data being viewed - Implement context injection adding relevant information to AI prompts without user having to specify - Create context switching handling when user navigates between modules while chat open - Build proactive context suggestions offering relevant queries based on current view (e.g., on lead page: "Would you like analysis of this lead's engagement?") - Implement cross-module context understanding (e.g., "Show me customers who are also donors") **Real-Time Data Querying:** - Build dynamic query engine translating natural language questions into real-time database queries across all modules - Implement aggregation and calculation support for complex queries (averages, totals, percentages, trends) - Create data visualization generation producing charts and graphs from query results when appropriate - Build query optimization ensuring responses return within 3-5 seconds even for complex queries - Implement result caching for frequently asked questions improving response times - Create data freshness indicators showing when data was last updated **Action Execution:** - Build action button system displaying executable actions in chat responses (e.g., "Create this content", "Add to list", "Schedule follow-up") - Implement one-click action execution allowing users to complete suggested actions without leaving chat - Create action confirmation system showing what action was taken and allowing undo where appropriate - Build action templates for common workflows (create lead, send email, generate report) - Implement action chaining allowing multiple actions in sequence (e.g., create content → schedule post → notify team) **Chat UI/UX:** - Build threaded conversation interface with clear user/AI message distinction and timestamps - Implement message formatting supporting rich text, code blocks, tables, lists, links, and embedded images - Create typing indicators showing AI is processing request - Build message editing allowing users to refine questions without resubmitting - Implement message reactions and feedback (thumbs up/down, helpful/not helpful) - Create suggested questions/prompts helping users discover MIRA capabilities - Build quick reply buttons for common follow-ups **Chat Input Enhancements:** - Implement rich text input supporting formatting (bold, italic, lists) - Build file upload capability allowing users to attach documents, images, or spreadsheets for analysis - Create @mention system for referencing specific records (e.g., "@Lead-John-Smith") - Implement slash commands for quick actions (/analyze, /create, /recommend) - Build voice-to-text readiness preparing infrastructure for future voice input - Create input history allowing users to recall previous queries **Streaming Responses:** - Implement server-sent events (SSE) or WebSocket streaming for real-time AI response delivery - Build progressive rendering showing AI response as it generates (not waiting for full completion) - Create streaming optimization ensuring smooth character-by-character or word-by-word display - Implement interruption capability allowing users to stop generation if response going off track **Global Side Panel:** - Build floating MIRA button visible on all portal pages (bottom-right corner by default, moveable) - Implement slide-out panel with smooth animation (300-400ms transition) - Create panel sizing options (narrow for quick queries, wide for detailed analysis) - Build panel state persistence remembering open/closed preference across sessions - Implement panel positioning allowing users to dock left or right side - Create mini mode showing compact chat view with expand option - Build keyboard shortcuts for opening/closing panel (e.g., Cmd/Ctrl+K) **Chat Performance:** - Implement message pagination loading last 50 messages by default with infinite scroll for history - Build lazy loading for embedded images and visualizations - Create response caching for frequently asked questions (served from cache in under 500ms) - Implement compression for conversation data reducing bandwidth usage - Build offline message queuing allowing users to compose messages when offline, sending when reconnected **Quick Actions & Shortcuts:** - Build quick action menu providing one-click access to common MIRA functions (Create, Analyze, Advise, Automate) - Implement module shortcuts jumping to specific module's MIRA view - Create template library for common queries and prompts - Build favorites/bookmarks allowing users to save useful queries for reuse - Implement conversation templates for repeated workflows ### Success Criteria - Chat persists across all portal sessions with full history retention - Context detection correctly identifies current module and page 95%+ of the time - Natural language queries return accurate data within 5 seconds for 90% of queries - Action buttons execute successfully without errors 98%+ of the time - Side panel opens/closes smoothly within 400ms with no janky animations - Floating MIRA button visible and functional on 100% of portal pages - Streaming responses display progressively with no lag or stuttering - Chat works seamlessly on desktop and tablet devices - File uploads process correctly (images, PDFs, spreadsheets up to 10MB) - Conversation export generates readable PDF/DOCX reports - Panel state (open/closed, position, size) persists across sessions - Users can access chat history dating back 90 days minimum - Chat interface meets WCAG 2.1 AA accessibility standards ### Future Sub-Tickets - Voice input and output - Multi-language support - Collaborative chat (multiple users in same conversation) - Chat analytics and insights - Advanced file parsing (Excel analysis, PDF extraction) --- ## 🤖 TICKET 10: Smart Recommendations & Automation System **Epic ID:** MW-MIRA-010 **Priority:** MEDIUM **Estimate:** 7 days **Team:** Backend + Frontend Developer **Dependencies:** MW-MIRA-001, all module intelligence tickets (MW-MIRA-002 through MW-MIRA-007) ### Overview Build the Advise module with AI-generated recommendations, the Automate module with natural language automation builder, smart nudge system, and impact tracking across all recommendations and automations. ### Detailed Scope **Recommendation Engine Architecture:** - Build centralized recommendation engine evaluating all modules simultaneously to identify cross-functional opportunities - Implement recommendation scoring algorithm prioritizing by financial impact, urgency, effort required, and success probability - Create recommendation types: opportunities (revenue generating), risks (problem prevention), optimizations (efficiency gains), compliance (regulatory requirements) - Build recommendation lifecycle tracking from generation → display → dismissed/actioned → outcome measurement - Implement machine learning feedback loop improving recommendations based on user actions and outcomes - Create recommendation templates for common scenarios (follow-up overdue, stock running low, donor lapsing) **Cross-Module Intelligence:** - Build insight aggregation pulling data from CRM, Ecommerce, Finance, HR, Marketing, and CMS simultaneously - Implement relationship mapping identifying connections across modules (e.g., customer who is also a donor, lead who purchased products) - Create holistic impact assessment showing how action in one module affects others (e.g., pricing change impact on margins, conversion rates, and customer satisfaction) - Build dependency detection identifying prerequisites for recommendations (e.g., must fix deliverability before sending email campaign) **Advise Module UI:** - Build recommendation feed displaying top 10-20 AI-generated recommendations sorted by impact - Implement recommendation cards showing title, description, expected impact ($ or %), effort required, and action buttons - Create filtering and sorting allowing users to focus on specific modules, types, or impact levels - Build recommendation detail view showing full analysis, supporting data, and implementation steps - Implement one-click action execution launching workflows directly from recommendations - Create recommendation dismissal with reason tracking (not applicable, already done, will do later) - Build recommendation history showing previously acted upon and dismissed recommendations **Impact Calculation:** - Develop impact modeling algorithms estimating financial benefit, time saved, risk reduced, or efficiency gained per recommendation - Build confidence intervals showing range of expected outcomes (e.g., "$5K-$15K additional revenue, 80% confidence") - Implement historical validation comparing predicted impact to actual results, refining models over time - Create impact attribution tracking actual outcomes of implemented recommendations - Build ROI dashboard showing total value generated by MIRA recommendations **Smart Nudge System:** - Build contextual nudge engine triggering notifications based on user behavior, data changes, and opportunities - Implement nudge types: inline (embedded in page content), toast (temporary popup), banner (persistent header), badge (notification dot) - Create nudge trigger conditions based on real-time data, user actions, time-based rules, and predicted events - Build nudge personalization showing different messages to different user roles - Implement nudge throttling preventing notification overload (max 3 active nudges, configurable quiet hours) - Create nudge effectiveness tracking measuring view rate, action rate, and outcome quality - Build nudge feedback system allowing users to rate helpfulness and report issues **Automation Builder (Natural Language):** - Build natural language automation parser translating plain English into executable workflows - Implement automation template library with pre-built workflows for common use cases (lead assignment, follow-up reminders, inventory reordering, donor thank-you emails) - Create automation validation ensuring logic is sound before activation (checking for infinite loops, missing data, permission issues) - Build variable system allowing dynamic values in automations (current date, user name, record data) - Implement conditional logic supporting if/then/else branching in workflows - Create multi-step automation sequencing chaining multiple actions together - Build automation testing allowing dry-run before live activation **Visual Workflow Diagrams:** - Implement flowchart generation automatically creating visual representation of automation logic - Build interactive diagrams allowing click-to-edit workflow steps - Create clear visual indicators for triggers, conditions, actions, and branches - Implement zoom and pan for complex workflows - Build export functionality generating workflow documentation **Automation Management:** - Build automation dashboard listing all active, paused, and draft automations - Implement automation performance tracking showing trigger count, success rate, failure reasons, and impact metrics - Create automation editing allowing modifications to active workflows with version control - Build automation logs showing detailed execution history per run - Implement error handling and retry logic for failed automation steps - Create automation alerts notifying users of failures or unusual patterns **Suggested Automations:** - Develop pattern detection analyzing user behavior and data flows to identify automation opportunities - Build automation suggestions showing recommended workflows based on repetitive tasks - Implement automation ROI prediction estimating time saved and error reduction per suggested automation - Create one-click automation activation launching suggested workflows with single button press **Impact Metrics:** - Build comprehensive impact tracking for all automations showing time saved, revenue generated, errors prevented, and tasks completed - Implement automation ROI dashboard comparing automation setup/maintenance costs against benefits - Create efficiency metrics showing percentage of tasks automated vs. manual - Build comparison analysis showing manual workflow time vs. automated workflow time - Implement business impact reporting showing automation contribution to KPIs **Notification System:** - Build smart notification engine for recommendations and automation results - Implement notification preferences allowing users to customize frequency, channels, and types - Create notification batching grouping multiple updates into daily digests - Build notification priority levels (critical, high, normal, low) with different delivery mechanisms - Implement cross-platform notifications (email, in-app, mobile push ready) ### Success Criteria - Recommendation engine generates minimum 10 high-quality recommendations daily per company - Recommendations show measurable impact predictions with 70%+ accuracy when validated retrospectively - One-click actions execute successfully 95%+ of the time without errors - Nudges appear contextually at appropriate times with 80%+ relevance rating from users - Nudge system does not overwhelm users (max 3 simultaneous nudges enforced) - Automation builder successfully parses natural language with 85%+ accuracy - Visual workflow diagrams generate automatically and display correctly for all automation types - Automations execute reliably with 98%+ success rate - Failed automations trigger alerts within 5 minutes of failure - Automation impact tracking accurately measures time saved and business value - Suggested automations achieve 30%+ activation rate (users implement suggestions) - Impact dashboard shows real, measurable value from MIRA recommendations and automations - All recommendations and nudges accessible to screen readers and keyboard navigation ### Future Sub-Tickets - Advanced ML recommendation models - Predictive automation triggers - Multi-step approval workflows - Automation marketplace (sharing workflows) - Advanced scheduling and timing controls --- ## 📊 SUMMARY & EXECUTION PLAN ### Timeline Overview **Total Duration:** 30 days (1 month) **Team Size:** 3-4 developers **Methodology:** Agile with parallel workstreams ### Ticket Breakdown | Ticket | Epic ID | Priority | Days | Team Members | Can Start | |--------|---------|----------|------|--------------|-----------| | 1. Foundation & AI Infrastructure | MW-MIRA-001 | CRITICAL | 6 | Backend + AI Engineer | Day 1 | | 2. CMS Intelligence | MW-MIRA-002 | CRITICAL | 5 | Full-Stack Dev | Day 7 | | 3. CRM Intelligence | MW-MIRA-003 | HIGH | 6 | Backend + Frontend | Day 7 | | 4. Ecommerce Intelligence | MW-MIRA-004 | HIGH | 6 | Backend + Analytics | Day 13 | | 5. TalentIQ Intelligence | MW-MIRA-005 | MEDIUM | 5 | Backend Dev | Day 13 | | 6. Finance Intelligence | MW-MIRA-006 | MEDIUM | 6 | Backend + Finance | Day 19 | | 7. Marketing Intelligence | MW-MIRA-007 | MEDIUM | 5 | Full-Stack Dev | Day 19 | | 8. Command Center Hub | MW-MIRA-008 | HIGH | 5 | Frontend + Backend | Day 12 | | 9. Chat & Side Panel | MW-MIRA-009 | HIGH | 6 | Full-Stack Dev | Day 12 | | 10. Recommendations & Automation | MW-MIRA-010 | MEDIUM | 7 | Backend + Frontend | Day 24 | ### Execution Strategy (4 Weeks) **Week 1 (Days 1-7): Foundation** - **MW-MIRA-001** (Foundation) — BLOCKING, must complete first - Team: Backend dev + AI engineer working full-time - Goal: Database ready, AI service operational, PII protection active by Day 6 **Week 2 (Days 8-14): Core Modules + Hub** - **MW-MIRA-002** (CMS) — Full-stack dev (Days 7-11) - **MW-MIRA-003** (CRM) — Backend + frontend team (Days 7-12) - **MW-MIRA-008** (Hub) — Frontend dev starting Day 12 - **MW-MIRA-009** (Chat) — Full-stack dev starting Day 12 - Goal: CMS live, CRM functional, Hub showing real data, Chat working by Day 14 **Week 3 (Days 15-21): Module Expansion** - **MW-MIRA-004** (Ecommerce) — Backend + analytics (Days 13-18) - **MW-MIRA-005** (TalentIQ) — Backend dev (Days 13-17) - **MW-MIRA-006** (Finance) — Backend + finance specialist (Days 19-24) - **MW-MIRA-007** (Marketing) — Full-stack dev (Days 19-23) - **MW-MIRA-008** (Hub) continues — integrating new modules - **MW-MIRA-009** (Chat) continues — adding module contexts - Goal: All major modules integrated, Hub comprehensive, Chat context-aware **Week 4 (Days 22-30): Polish & Advanced Features** - **MW-MIRA-010** (Recommendations & Automation) — Backend + frontend (Days 24-30) - Testing, bug fixes, performance optimization across all tickets - Documentation, user training materials, demo preparation - Goal: Recommendations live, automation builder functional, system ready for launch ### Parallel Workstreams **Workstream A (Backend + AI):** Days 1-6: Foundation → Days 7-12: CRM → Days 13-18: Ecommerce → Days 19-24: Finance → Days 24-30: Automation backend **Workstream B (Full-Stack):** Days 7-11: CMS → Days 12-17: Chat → Days 18-23: Marketing → Days 24-30: Recommendations UI **Workstream C (Frontend + Analytics):** Days 7-11: Assist CMS → Days 12-17: Hub → Days 18-23: TalentIQ → Days 24-30: Polish & testing ### Dependencies Map ``` MW-MIRA-001 (Foundation) ├─→ MW-MIRA-002 (CMS) ├─→ MW-MIRA-003 (CRM) ├─→ MW-MIRA-004 (Ecommerce) ├─→ MW-MIRA-005 (TalentIQ) ├─→ MW-MIRA-006 (Finance) ├─→ MW-MIRA-007 (Marketing) ├─→ MW-MIRA-008 (Hub) ← also needs MW-MIRA-002 for initial data ├─→ MW-MIRA-009 (Chat) ← also needs MW-MIRA-002 for context └─→ MW-MIRA-010 (Advise/Automate) ← needs all module tickets ``` ### Risk Mitigation **Risks:** 1. **Foundation delays block everything** — Mitigate: Start Day 1, daily progress checks, have backup developer ready 2. **AI service rate limits** — Mitigate: Implement caching, request throttling, fallback to degraded mode 3. **Module integration complexity** — Mitigate: Build data providers incrementally, extensive testing per module 4. **Performance issues with real data** — Mitigate: Load testing starting Week 2, optimize queries proactively **Contingency Plans:** - If any module delayed, Hub and Chat can launch with subset of modules - Advanced features (automation, some recommendations) can be phased delivery if timeline tight - Consider 4-week core + 1-week polish if needed ### Success Metrics (End of Month) **Functional:** - [ ] All 5 MIRA modules accessible and functional - [ ] Hub displaying real-time data from minimum 4 modules (CMS, CRM, Ecommerce, Finance) - [ ] Chat operational with context awareness across all integrated modules - [ ] Minimum 50 recommendations generated across modules - [ ] Minimum 10 automations created and functional **Performance:** - [ ] Dashboard loads < 2 seconds - [ ] Chat responses < 5 seconds for 90% of queries - [ ] AI content generation < 5 seconds for standard pieces - [ ] System handles 50+ concurrent users without degradation **Quality:** - [ ] 0 critical bugs in production - [ ] < 10 minor bugs across all tickets - [ ] 80%+ code coverage on core services - [ ] All accessibility standards met (WCAG 2.1 AA) **Business:** - [ ] Demo-ready for stakeholders - [ ] User documentation complete - [ ] Training materials prepared - [ ] Rollout plan finalized --- ## 📋 JIRA IMPORT CHECKLIST ### When Creating Tickets in JIRA: **For Each Epic (MW-MIRA-001 through MW-MIRA-010):** - [ ] Set Epic Name and ID - [ ] Add detailed description from "Overview" and "Detailed Scope" sections - [ ] Set Priority (Critical, High, Medium) - [ ] Set Estimate (use "Days" field or story points: 1 day = 8 points) - [ ] Add module labels: Foundation, CMS, CRM, Ecommerce, TalentIQ, Finance, Marketing, Hub, Chat, Automation - [ ] Add technology labels: Backend, Frontend, Full-Stack, AI, Analytics - [ ] Link dependencies (Epic Link or Blocks/Blocked relationships) - [ ] Assign to team/individuals based on "Team" field - [ ] Set start date based on execution plan - [ ] Add "Success Criteria" section as Acceptance Criteria - [ ] Tag nonprofit-specific features with "Nonprofit-Only" label **Sub-Tickets (To Be Created Later):** Each epic has "Future Sub-Tickets" section listing candidates for breakdown when work begins **Sprint Planning:** - Sprint 1 (Week 1): MW-MIRA-001 - Sprint 2 (Week 2): MW-MIRA-002, MW-MIRA-003, MW-MIRA-008, MW-MIRA-009 - Sprint 3 (Week 3): MW-MIRA-004, MW-MIRA-005, MW-MIRA-006, MW-MIRA-007 - Sprint 4 (Week 4): MW-MIRA-010 + testing and polish --- ## 🚀 READY TO START **First Action Item:** Create MW-MIRA-001 (Foundation & AI Infrastructure) in JIRA and assign to backend team **Key Contacts:** - Product Owner: [Assign] - Tech Lead: [Assign] - AI/ML Engineer: [Assign] - Frontend Lead: [Assign] **Next Steps:** 1. Review and approve this ticket structure 2. Import into JIRA 3. Assign team members 4. Schedule kickoff meeting 5. Begin MW-MIRA-001 on Day 1