Knowledge Capture AI Agent: Pilot MVP Proof of Concept

Project Type: Knowledge Capture AI Agent Pilot MVP
Current State: Building from scratch with AI tools
Duration: 12 weeks (3 months)

Executive Summary

The Knowledge Capture AI Agent transforms skilled trades knowledge management through AI-driven capture and validation. Using AR technology, the system accelerates knowledge documentation by converting expert demonstrations and interviews into structured, validated learning materials.

Pilot Scope:
Early pilot users in single facility
2-3 critical manufacturing processes
AI-powered knowledge capture with human validation workflow
Proof-of-concept infrastructure suitable for pilot validation
Foundation for future enterprise scaling

Core Challenge

Capture, validate, and structure critical manufacturing knowledge (equipment, tools, materials, tasks) using AI agents with mandatory human validation from both Contractor and Client teams to ensure accuracy and compliance.

This proposal outlines a focused 3-month implementation of the Knowledge Capture AI Agent, designed to validate core capture concepts and establish foundation for future platform expansion.

Important Note: This is NOT an enterprise-grade deployment. Full enterprise implementation would require significant additional investment over 18-27 months to meet Fortune 500 automotive manufacturing standards.

Solution Architecture

The Knowledge Capture AI Agent operates through integrated components with dual human validation:

Knowledge Capture AI Agent - Conducts SME interviews, processes content, and generates structured documentation in BEST format, subject to human validation from both Contractor technical team and Client subject matter experts before finalization.

12-Week Implementation Plan

Below is the anticipated team and tech stack for this project. Based on the evolving project, we may need further assistance as the scope changes. Any changes would be signed-off and agreed upon by all parties.

Anticipated Team: Tech Lead + Senior Developer + Conversational AI PM + Human Reviewer

Month 1: Core Infrastructure & Capture Foundation

Sprint 1-2 Components:
Core Platform: Unified software foundation with authentication, storage, and API management
Interview Engine: AI system for structured SME conversations with intelligent prompt chaining
Speech Processing: OpenAI Whisper-powered transcription pipeline or similar
Human Validation Workflow: Dual-approval system requiring both Contractor and Client validation

Deliverables:
Basic Knowledge Capture AI Agent
Human validation workflow system
Speech-to-text processing pipeline

Month 2: Validation & Documentation Systems

Sprint 3-4 Components:
Validation System: Quality assurance engine cross-referencing captured content against SOPs
Video Intelligence: Automated video processing with captions and timestamp generation
AR Framework: AR technology integration for real-time capture
BEST Format Generator: Automated job aid creation with validation checkpoints

Deliverables:
Functional validation system with human oversight
Video annotation and curation pipeline
AR-integrated capture capability

Month 3: Integration, Testing & Deployment

Sprint 5-6 Components:
System Integration: Complete capture-to-validation of 2-3 critical manufacturing processes
Human Validation Dashboard: Interface for Contractor and Client validation teams
Quality Assurance: Automated testing and performance optimization
Production Deployment: Pilot system deployment with monitoring

Deliverables:
Complete Knowledge Capture AI Agent with validation workflow
Human validation dashboard for both teams
Deployed pilot system with documentation

Technical Architecture

Below is the anticipated tech stack for this project, these may change during the build phase for the best technical architecture stack possible. We can only know the full capabilities and limitations of each part of the stack during implementation.

Core Technology Stack:
AI/ML Framework: GPT-based NLP pipeline, computer vision for AR
Database Layer: PostgreSQL for structured data
Authentication: Ory Kratos with role-based access control
AR Integration: AR technology SDK
Validation Workflow: Custom approval system for dual human oversight

Data Flow:
1. Capture: AR Headset → AI Agent → NLP Processing → Initial Documentation
2. Validation: Contractor Review → Client SME Review → Approval/Revision Loop
3. Storage: Validated Knowledge → Structured Storage → BEST Format Output

Human Validation Requirements

Contractor Validation:
Technical accuracy review
System functionality verification
Documentation quality assurance
Integration testing approval

Client Validation:
Subject matter expert content review
Safety protocol compliance verification
SOP alignment confirmation
Final approval for knowledge base inclusion

Validation Process:
All captured knowledge requires dual approval before finalization
Revision loops built into workflow for iterative improvement
Clear escalation path for validation disagreements
Audit trail maintained for all validation decisions

Milestone-Based Deliverables

Milestone 1: Foundation & Core Capture (4 weeks)
Requirements gathering and technical architecture
Plant assessment and integration planning
Basic infrastructure setup with validation workflow
SME interview system with human oversight

Milestone 2: Validation & Processing Systems (4 weeks)
Knowledge validation system with dual approval
Video processing and AR integration
BEST format generation with quality checks
Human validation dashboard development

Milestone 3: Deployment & Pilot Launch (4 weeks)
Complete system integration and testing
Pilot deployment with validation teams
User training for both Contractor and Client teams
Performance metrics collection and reporting

Milestone 4: Final Acceptance & Delivery (expected within 1-2 weeks)
Final acceptance testing with Client validation team
Complete system documentation and user manuals
Knowledge transfer sessions and technical handover
30-day warranty period initiation
Project completion certification and sign-off

Pilot Scope & Limitations

What This Pilot Includes:
10-30 users in single facility
Knowledge capture AI with human validation of 2-3 key workflows
Proof-of-concept infrastructure
Basic AR technology integration
Foundation architecture for future expansion

What This Pilot Does NOT Include:
AR hardware products
Enterprise-grade security certifications
Enterprise hosting costs of data sets
Full system integration with enterprise APIs
Multi-plant deployment
Advanced AI learning or analytics capabilities
24/7 enterprise support

Success Metrics

Pilot Success Criteria:
Knowledge Capture: 5-10 critical processes documented and validated
System Performance: 95% uptime during pilot (Contractor not liable for stack outages)
Validation Efficiency: <48 hour turnaround for dual approval process

Measurable Outcomes:
Documentation accuracy improved through dual validation
Structured knowledge capture in BEST format
Reduced time for knowledge documentation
Established foundation for future AI learning systems

AI-Assisted Development Strategy

Development team will utilize AI-assisted coding tools for estimated 20%-200% development acceleration using tools such as Cursor, Amazon CodeWhisperer, Qodo, Tabnine, or others as appropriate.

Potential Ongoing Pilot Support

Monthly Support Options:
Technical Support: Monthly maintenance (bug fixes, maintenance, monitoring)
Content Development: Monthly enhancement (additional documentation, AI refinement)
Pilot Management: Monthly coordination (reporting, stakeholder communication)
Total Comprehensive Support: Available upon request

Next Steps

Immediate Actions:
Pilot approval and contract finalization
Contractor and Client validation team identification
Facility selection for pilot implementation
Technical requirements and validation workflow definition

This focused pilot provides the foundation for informed enterprise decision-making while delivering immediate value through achievable objectives within the 12-week timeframe, with robust human validation ensuring quality and compliance.