Audio/Video/Data Implementation Plan 2026

Status: Draft — Ready for Review
Created: 2026-03-14
Owner: Brainforge Engineering
Purpose: Actionable implementation plan for leveraging ALL Brainforge data assets with sensitivity controls, cost management, and phased delivery


Executive Summary

This plan operationalizes the comprehensive Data roadmap into executable phases with clear boundaries, success criteria, and resource requirements. For the proactive briefing layer, see Pulse.

Key Decisions Confirmed:

  • All S3 video will be processed (not prioritized subset)
  • Sensitivity check system required before any content analysis
  • Full org calendar visibility for intelligent preparation
  • Market intel budget approved for premium data feeds
  • Cross-client benchmarking approved as long-term product direction

Not Building Now: This document is planning-only. Implementation begins after review, dependency confirmation, and Phase 1 scoping.


Sensitivity & Privacy Framework

Sensitivity Check System (Required Before Analysis)

Purpose: Prevent exposure of confidential, personal, or sensitive information before any AI processing or storage.

Implementation:

┌─────────────────────────────────────────────────────────────┐
│                  SENSITIVITY PIPELINE                      │
├─────────────────────────────────────────────────────────────┤
│  1. INGESTION → Automatic classification on ingest         │
│     - PII detection (names, emails, phones, SSNs)           │
│     - Financial data patterns (account numbers, amounts)    │
│     - Confidential keywords ("confidential", "NDA", etc.) │
│     - HR/legal flags ("termination", "performance", etc.)  │
│                                                              │
│  2. CLASSIFICATION → 4-tier sensitivity model              │
│     🔴 CRITICAL: Board meetings, HR issues, legal matters   │
│     🟠 HIGH: Financial details, strategic plans, M&A        │
│     🟡 MEDIUM: Client specifics, pricing discussions        │
│     🟢 LOW: General updates, public information            │
│                                                              │
│  3. HANDLING → Tier-based processing rules                 │
│     🔴 CRITICAL: Index only metadata, no content analysis   │
│     🟠 HIGH: Index with redaction, human review required      │
│     🟡 MEDIUM: Standard processing, opt-out available       │
│     🟢 LOW: Full processing, automatic indexing             │
│                                                              │
│  4. AUDIT → Complete audit trail for compliance            │
│     - Who accessed what content when                        │
│     - Sensitivity classification history                   │
│     - Override and exception logging                         │
└─────────────────────────────────────────────────────────────┘

Per-Source Sensitivity Rules

Data SourceDefault ClassificationSpecial Handling
S3 Video — Client meetings🟡 MEDIUMClient name always searchable, content respects client confidentiality
S3 Video — Internal meetings🟠 HIGHParticipant list indexed, content flagged for HR/legal keywords
S3 Video — Board/exec🔴 CRITICALMetadata only, explicit approval for any content processing
Gmail — External client🟡 MEDIUMFull processing, PII redacted in shared outputs
Gmail — Internal HR/legal🔴 CRITICALIndex metadata only, no content analysis
Gmail — General business🟢 LOWFull processing
Calendar — All events🟢 LOWMetadata only (who, when, where), no content extraction from descriptions
Slack — Client channels🟡 MEDIUMStandard processing, confidential threads excluded
Slack — Internal channels🟠 HIGHSensitivity scan on exec, hr, legal channels

User Controls

Individual Opt-Out:

  • Any employee can exclude their own calendar from intelligence features
  • Gmail folders can be excluded (e.g., “Personal”, “Confidential”)
  • Meeting classification can be overridden by meeting title keywords (“[PRIVATE]”, “[HR]”)

Admin Controls:

  • Org-wide exclusion lists (domains, keywords, participants)
  • Mandatory classification channels (auto-flag exec, hr)
  • Retention policy enforcement (auto-delete after N days)

Phase 1: Foundation (Months 1–3)

1.1 Infrastructure Setup (Week 1–2)

Deliverables:

  • Sensitivity classification service deployed
  • S3 batch processing pipeline scaffold
  • Gmail API integration with rate limiting
  • Calendar API connection with webhook support
  • Enhanced vector DB schema for source tagging

Dependencies:

  • S3 read access + inventory list
  • Google Workspace admin API keys
  • TurboPuffer capacity planning + cost estimate
  • Dagster cluster sizing for batch processing

1.2 S3 Video Archive Processing (Week 2–8)

Scope: ALL historical video in S3

Processing Pipeline:

S3 Inventory → Priority Queue → Transcription → Metadata → Indexing → Cleanup
     ↓              ↓                ↓             ↓            ↓           ↓
  List all      Sort by:        Whisper API    Scene       TurboPuffer   Original
  objects       size, date,     (or Azure      detection   + Supabase    kept for
                client          Speech)        + OCR       metadata    reference

Cost Management:

  • Estimated: ~10,000 hours of video
  • Whisper cost: ~3,600 for full archive
  • Azure Speech alternative for cost comparison
  • Parallel processing: 50 concurrent jobs max to control costs
  • Spot instance usage for transcoding where applicable

Sensitivity Integration:

  • All videos classified before transcription
  • CRITICAL videos: metadata only, no transcription
  • HIGH videos: transcription with PII redaction review

Success Criteria:

  • 100% of S3 video catalogued within 2 weeks
  • 80% transcribed and indexed by end of Phase 1
  • Processing rate: 100+ hours/day sustained
  • Cost tracking dashboard with alerts at 50%, 75%, 100% budget

1.3 Gmail Integration (Week 3–8)

Scope: ALL historical Gmail + ongoing sync

Ingestion Strategy:

Gmail API Bulk Export → S3 Archive → Text Extraction → Entity Extraction → Indexing
       ↓                      ↓              ↓                ↓               ↓
  Rate-limited          Immutable        MIME parsing    People,         TurboPuffer
  (250 quota units/     raw storage      + attachment    companies,      + Entity
  user/day)                              text extraction  commitments,    Graph
                                           (PDF, DOC)      dates

Rate Limiting Strategy:

  • 250 quota units per user per day (Google limit)
  • ~3,000 messages/day per user at typical quota cost
  • Backfill queue: process oldest first (legal discovery precedent)
  • Incremental sync: real-time via push notifications

Sensitivity for Email:

  • Subject line always indexed (low sensitivity)
  • Body content classified by keywords + attachments
  • Attachment extraction with virus scanning
  • Thread reconstruction maintains context

Entity Extraction Priority:

  1. People (from/to/cc, signatures)
  2. Companies (signature domains, mentioned orgs)
  3. Dates and deadlines (“by Friday”, “next week”)
  4. Commitments (“I will”, “we’ll send”, “I’ll prepare”)
  5. Action items (“need to”, “should”, “todo”)

Success Criteria:

  • 100% of historical email indexed within 6 weeks
  • Incremental sync latency: <5 minutes for new email
  • Entity extraction accuracy: 85%+
  • Thread reconstruction: 95%+ complete threads

1.4 Calendar Integration (Week 4–6)

Scope: Full organization calendar (read-only, metadata only)

Data Extracted:

  • Event metadata: title, time, duration, location, attendees
  • Recurrence patterns
  • Attendance status (accepted/declined/tentative)
  • Meeting descriptions (optional, sensitivity-scanned)

NOT Extracted:

  • Private events (unless explicitly shared)
  • Event descriptions marked sensitive
  • Attachments on calendar invites (separate email flow)

Intelligence Features:

  • Pre-meeting brief trigger (24 hours before)
  • Post-meeting action extraction trigger
  • Relationship cadence tracking
  • Optimal meeting time suggestion

Success Criteria:

  • 100% of org calendars connected within 2 weeks
  • Pre-meeting briefs generated for 90%+ of external meetings
  • Calendar-based relationship insights available

1.5 Unified Search MVP (Week 6–10)

First Release: Search across meetings, email, Slack

Search Interface:

  • Natural language queries
  • Source filters (email only, meetings only, all)
  • Date range filters
  • Person/company filters
  • Confidence scoring

Result Presentation:

  • Meetings: timestamped transcript + video link
  • Email: thread summary + key excerpt + full thread link
  • Slack: channel context + thread link
  • Cross-source threading: “Related: 3 emails, 1 meeting”

Success Criteria:

  • Sub-2-second search response time
  • Relevance: top 3 results contain answer 80%+ of time
  • Daily active users: 50%+ of team

1.6 Pre-Meeting Brief MVP (Week 8–12)

Brief Components:

  1. Last Contact Summary — Last meeting transcript summary
  2. Email Context — Recent threads, open questions, commitments
  3. Open Items — Outstanding Linear tickets, promised deliverables
  4. Relationship Health — Communication frequency, responsiveness trends
  5. Suggested Agenda — Based on open items and historical patterns

Delivery:

  • 24 hours before external meetings
  • Slack DM to meeting organizer
  • Optional: calendar invite attachment

Success Criteria:

  • Generated for 80%+ of external meetings
  • Organizer opens brief 60%+ of the time
  • Positive feedback: “saved me time” or “caught something I missed”

Phase 2: Intelligence (Months 4–6)

2.1 Cross-Channel Action & Commitment Tracking

Unified Action Register:

  • Extract from: meetings, email, Slack
  • Deduplicate: same action mentioned in multiple channels
  • Track: owner, deadline, source, confidence
  • Alert: approaching deadline, overdue, completed

Commitment Detection:

  • Pattern matching: “I will”, “we’ll”, “I’ll”, “by [date]”
  • Deadline extraction: explicit dates, relative dates (“next Friday”)
  • Owner assignment: speaker/writer detection
  • Recipient tracking: who was the commitment made to

2.2 Relationship Health Scoring

Metrics (Cross-Channel):

  • Communication velocity: messages per week across all channels
  • Response time: average time to reply by channel
  • Sentiment trajectory: positive/negative trend over 30/60/90 days
  • Meeting quality: attendance, engagement, outcomes
  • Staleness: days since last meaningful contact

Health Score Calculation:

Health = (Communication Velocity × 0.3) + 
         (Response Quality × 0.25) + 
         (Sentiment Trajectory × 0.2) + 
         (Meeting Quality × 0.15) + 
         (Recency × 0.1)

2.3 Deal Communication Timeline

Timeline View:

  • Chronological: all touchpoints with a company/deal
  • Filterable: by channel, by participant, by topic
  • Searchable: within deal context
  • Exportable: for handoffs, post-mortems

Automatic Tagging:

  • Deal stage transitions (detected from content)
  • Stakeholder identification (who participated when)
  • Objection moments (flagged for review)
  • Commitment moments (tracked for fulfillment)

2.4 Market Intelligence Feeds

Data Sources (Budget Approved):

SourceCost/YearDataIntegration
Crunchbase Pro~$300Funding, acquisitions, leadershipAPI + webhooks
LinkedIn Sales Navigator~$1,500/userHiring patterns, leadership changesManual + API
SEMrush/Ahrefs~$2,000SEO trends, competitor contentAPI
G2/Capterra~$5,000Review trends, category shiftsAPI + scraping
SEC EDGARFree10-K, 10-Q, 8-K filingsDirect API
News APIs~$500Industry news, press releasesNewsAPI, GDELT
Industry ReportsVariableGartner, Forrester, IDCManual ingestion

Signal Detection:

  • Funding announcements → Expansion opportunity alert
  • Leadership changes → Champion risk/reach-out trigger
  • Competitive launches → Positioning alert
  • Regulatory changes → Compliance opportunity
  • Hiring surges → Demand signal

2.5 Communication Pattern Mining

Pattern Discovery:

  • Winning deal patterns: “Deals that close in 30 days have…”
  • Risk patterns: “Deals that stall show…”
  • Top performer patterns: “Top AEs consistently…”
  • Response patterns: “Reply rates highest when…”

Validation:

  • A/B test recommendations
  • Cohort analysis by outcome
  • Confidence scoring on patterns
  • Continuous re-evaluation

Phase 3: Systematization (Months 7–9)

3.1 Voice-of-Customer Radar

Feature Request Extraction:

  • Cross-channel clustering: “I wish…”, “We need…”, “Do you support…”
  • Frequency scoring: how many times mentioned
  • Account weighting: ARR of requesting accounts
  • Trend detection: emerging themes over time

Pain Point Tracking:

  • Frustration detection: sentiment + keyword patterns
  • Severity scoring: frequency + impact language
  • Resolution tracking: was it addressed? satisfaction?

Integration with Product:

  • Weekly digest to product team
  • Linear ticket suggestions with context
  • Customer validation invitations

3.2 Smart Clips Generator

Clip Types:

  • Decision moments: “We’ve decided to…”
  • Objection handling: “The concern is…” → response
  • Feature requests: “What we really need is…”
  • Success stories: “Since implementing…”
  • Executive quotes: C-level commentary

Generation Pipeline:

  1. Key moment detection (transcript analysis)
  2. Video timestamp extraction (scene matching)
  3. Clip boundaries (5-second buffer on each side)
  4. Transcript overlay generation
  5. Shareable link creation
  6. CRM/Slack integration

3.3 Meeting QA Scorecards

Metrics:

  • Talk ratio (rep vs. prospect)
  • Discovery questions (count + depth)
  • Objection handling (detected + response quality)
  • Next-step clarity (explicit commitment language)
  • Call structure (agenda, recap, actions)

Benchmarking:

  • Individual vs. team average
  • Trend over time
  • Correlation with outcomes (closed-won correlation)

3.4 Email Coaching

Analysis:

  • Response rate by length, tone, timing
  • Question quality (open vs. closed)
  • Follow-through rate
  • Subject line effectiveness
  • Thread management patterns

Recommendations:

  • “Try asking an open question here”
  • “Your response time is 2x team average — speed up”
  • “This email is 200+ words; 50-100 gets better responses”

Phase 4: Platform (Months 10–18)

4.1 Unified Org Intelligence Graph

Graph Schema:

NODES:
- Person (email, role, expertise, communication style)
- Company (domain, industry, health score, lifecycle stage)
- Project (status, team, dependencies, blockers)
- Deal (stage, value, timeline, participants)
- Decision (who, when, what, status)
- Commitment (who, to whom, what, deadline, fulfilled?)
- Topic (extracted themes, frequency, trend)

EDGES:
- COMMUNICATED_WITH (frequency, recency, sentiment)
- WORKS_ON (role, start date, allocation)
- DEPENDS_ON (dependency type, criticality)
- DECIDED (confidence, outcome, reversed?)
- COMMITTED_TO (deadline, fulfilled, communication channel)
- INTERESTED_IN (topic, intensity, recency)

Query Interface:

  • Natural language: “Who knows the most about AWS migrations?”
  • Graph queries: “Show all people who’ve worked with EnterpriseCo”
  • Path finding: “Shortest connection to CTO of TargetCo”

4.2 Predictive Opportunity Engine

Opportunity Types:

  • Expansion triggers: Client raised funding, hired team, launched product
  • New logo: Market signal + your expertise match
  • Churn prevention: Communication decline + market stress
  • Competitive displacement: Client frustration + your capability
  • Timing optimization: Industry event + client milestone

Scoring Model:

Opportunity Score = (Signal Strength × 0.4) + 
                    (Fit to Expertise × 0.3) + 
                    (Timing Urgency × 0.2) + 
                    (Access Likelihood × 0.1)

4.3 Autonomous Relationship Management

Autonomous Actions (with human approval gates):

ActionConfidence ThresholdHuman Gate
Draft check-in email80%Preview before send
Suggest meeting times90%Auto-send below threshold
Share relevant content85%Preview with context
Flag at-risk account70%Alert only, no action
Schedule quarterly review90%Calendar integration

Learning Loop:

  • Track which autonomous suggestions were accepted
  • Feedback on sent messages (response rate, sentiment)
  • Continuous model improvement

4.4 Market Intelligence Platform (Productized)

Service Tiers:

TierPriceIncludes
Pulse$500/moWeekly industry digest, 3 competitors tracked
Radar$2,000/moDaily alerts, 10 competitors, custom topics
Command$5,000/moReal-time alerts, unlimited competitors, custom analysis, API access

Deliverables:

  • Automated market reports (PDF + dashboard)
  • Competitor monitoring with change alerts
  • Opportunity sizing based on market signals
  • Custom query interface (“What’s happening in X?”)

Phase 5: Moonshots (Months 18+)

5.1 Communication Simulator

Training Environment:

  • AI-generated scenarios from real patterns
  • Difficulty levels: novice, intermediate, expert
  • Industry-specific modules
  • Performance tracking and certification

Scenario Sources:

  • Difficult objections from deal history
  • Complex stakeholder situations
  • Executive conversation patterns
  • Crisis recovery stories

5.2 Outcome-Autonomous Revenue Organization

Agent Teams:

  • Prospecting Agent: Identifies targets, drafts outreach, manages sequence
  • Deal Agent: Manages active deals, schedules next steps, handles objections
  • Expansion Agent: Monitors health, identifies expansion signals, manages upsell
  • Market Agent: Tracks industry, identifies opportunities, feeds prospecting

Governance:

  • Weekly review of agent actions
  • Quarterly goal setting with human leadership
  • Exception handling protocols
  • Kill switch for any agent

5.3 Collective Intelligence Network

Cross-Client Insights:

  • Benchmarking: “Your onboarding is X% faster than peers”
  • Trend detection: “5 clients mentioned Y this month”
  • Best practice sharing: “Top performers do Z”
  • Market timing: “Q2 is historically best for X”

Privacy Model:

  • Differential privacy: noise added to prevent individual identification
  • Minimum cohort size: insights only for groups of 5+
  • Opt-in only: clients choose to participate
  • No raw data sharing: insights only, never underlying data

Resource Requirements

Team Structure

RolePhase 1Phase 2Phase 3+
Platform Engineer222
ML/AI Engineer122
Data Engineer122
Product Manager0.511
Frontend Engineer112
DevOps/SRE0.511
Total FTE6910

Infrastructure Costs (Monthly)

ComponentPhase 1Phase 2Phase 3Phase 4
S3 Processing$5,000$1,000$500$500
Transcription$3,600$800$500$500
Vector DB$500$1,000$2,000$3,000
Compute$1,000$2,000$3,000$4,000
Market Intel Feeds$500$1,000$1,500$2,000
Total~$10,600~$5,800~$7,500~$10,000

Note: Phase 1 spike due to one-time backfill processing

External Services Budget

ServiceAnnual Cost
Crunchbase Pro$3,600
LinkedIn Sales Navigator (3 seats)$4,500
SEMrush Business$6,000
NewsAPI + GDELT$6,000
Industry Reports$10,000
Misc (G2, Capterra, etc.)$5,000
Total$35,100/year

Risk Management

Technical Risks

RiskLikelihoodImpactMitigation
Gmail API rate limitsHighMediumIncremental sync, retry logic, queue management
S3 processing cost overrunMediumHighCost alerts, parallel limits, spot instances
Entity resolution accuracyMediumMediumHuman verification workflow, confidence thresholds
Search latency at scaleMediumMediumHierarchical indexing, caching, query optimization
Model hallucinationMediumHighConfidence scoring, human verification for high-stakes

Business Risks

RiskLikelihoodImpactMitigation
Low adoptionMediumHighStart with power users, demonstrate value, gradual rollout
Privacy concernsMediumHighSensitivity framework, opt-out, transparency, audit
Alert fatigueMediumMediumSmart prioritization, digest format, thresholds
CompetitionLowMediumProprietary data moat, continuous improvement
Scope creepHighMediumStrict phase gates, MVP focus, defer nice-to-haves

Compliance Risks

RiskMitigation
GDPR (EU clients)Data processing agreements, right to deletion, audit trail
CCPA (California)Opt-out mechanisms, data inventory, disclosure
SOC 2Access controls, audit logging, encryption, monitoring
Client confidentialityTenant isolation, no cross-contamination, sensitivity classification

Success Metrics by Phase

Phase 1 (Month 3)

MetricTargetMeasurement
S3 video processed80%+Objects transcribed / total objects
Historical email indexed100%Messages indexed / total messages
Calendar connected100%Users with calendar integration
Pre-meeting briefs generated80%+External meetings with briefs
Unified search DAU50%+Daily active users / total users
Time to find information<30sUser-reported search time
Cost on budget100%Actual / planned spend

Phase 2 (Month 6)

MetricTargetMeasurement
Action extraction coverage90%Actions captured / total commitments
Relationship health scores50 accountsAccounts with full scoring
Market alerts actionable5+/weekAlerts with follow-up actions
Deal timeline usage70%Deals with timeline viewed
User-reported time saved5+ hrs/weekSurvey response average

Phase 3 (Month 9)

MetricTargetMeasurement
VoC Radar usage100% product teamWeekly active users
Meeting scorecard delivery<1 hourTime from meeting end to scorecard
Clip relevance rate70%+User-confirmed relevant clips
Forecast accuracy+20%Comparison to pre-implementation

Phase 4 (Month 18)

MetricTargetMeasurement
Complex query success85%+Queries with satisfactory answer
Predictive opportunities10+/monthOpportunities surfaced
Autonomous task completion30%Low-touch tasks handled automatically
Market intel product revenue$20K MRRExternal customer revenue
Platform NPS50+Net Promoter Score survey

Decision Log

DateDecisionRationaleAlternatives Considered
2026-03-14Process ALL S3 videoMaximum data moat valuePrioritized subset (rejected: loses historical value)
2026-03-14Sensitivity check requiredPrivacy compliance, trustPost-hoc classification (rejected: risk of exposure)
2026-03-14Full org calendarComplete relationship intelligenceOpt-in only (rejected: incomplete picture)
2026-03-14Budget approved for market intelQuality external signalsFree sources only (rejected: insufficient coverage)
2026-03-14Cross-client benchmarking approvedLong-term product directionKeep proprietary (rejected: limits value)

Next Steps (Planning Complete)

Immediate (This Week)

  • Review this plan with stakeholders
  • Confirm Phase 1 resource allocation
  • Validate cost estimates
  • Approve external service procurement

Pre-Implementation (Next 2 Weeks)

  • S3 inventory and access verification
  • Google Workspace admin API setup
  • Sensitivity classification model selection
  • Phase 1 ticket creation in Linear
  • Success metric baseline measurement

Phase 1 Kickoff (Month 1)

  • Sprint planning for Week 1–2 infrastructure
  • S3 processing pipeline deployment
  • Gmail API integration begin
  • Weekly status review establishment

DocumentPurpose
Audio/Video/Data RoadmapStrategic vision and 30+ project concepts
Data Platform RoadmapInfrastructure and pipeline planning
Slack Assistant RoadmapInternal AI assistant integration
Sensitivity Framework (this doc)Privacy and classification system

Document History

DateChange
2026-03-14v1 — Complete implementation plan with sensitivity framework, resource requirements, phase-by-phase execution