KnowledgeVault AI intent
internal prototype · canonical JSON + Dreamborn Forge HTML
internal generated
intent · supabase_json

KnowledgeVault AI intent

Manufacturing and distribution companies face an institutional knowledge cliff as experienced employees retire. Decades of irreplaceable tacit knowledge — product quirks, troubleshooting heuristics, application expertise — walks out the door with no scalable way to capture it first.

Planning Surface

Use this to decide what happens next.

Status

approved

problem

Manufacturing and distribution companies face an institutional knowledge cliff as experienced employees retire. Decades of irreplaceable tacit knowledge — product quirks, troubleshooting heuristics, application expertise — walks out the door with no scalable way to capture it first.

success metrics
  • 5+ pilot distributors signed within 12 weeks
  • 50+ expert profiles and 10+ active company projects in beta
  • Project completion rate — % of contracted projects that deliver usable knowledge assets
  • Expert retention — experts who complete one project and return for a second
  • MRR and 10-15% commission volume on expert transactions
  • Knowledge retrieval accuracy — answers are grounded in expert-provided content
  • Onboarding time reduction for buyers who deploy knowledge assets to new hires
Agent Handoff
Start Here

Manufacturing and distribution companies face an institutional knowledge cliff as experienced employees retire. Decades of irreplaceable tacit knowledge — product quirks, troubleshooting heuristics, application expertise — walks out the door with no scalable way to capture it first.

Completion Evidence
  • 5+ pilot distributors signed within 12 weeks
  • 50+ expert profiles and 10+ active company projects in beta
  • Project completion rate — % of contracted projects that deliver usable knowledge assets
  • Expert retention — experts who complete one project and return for a second
  • MRR and 10-15% commission volume on expert transactions
  • Knowledge retrieval accuracy — answers are grounded in expert-provided content
  • Onboarding time reduction for buyers who deploy knowledge assets to new hires
Problem

Manufacturing and distribution companies face an institutional knowledge cliff as experienced employees retire. Decades of irreplaceable tacit knowledge — product quirks, troubleshooting heuristics, application expertise — walks out the door with no scalable way to capture it first.

Goal

Build a category-defining two-sided marketplace that connects retiring experts with manufacturers and distributors who need their knowledge captured, structured, and made AI-ready. Validate product-market fit with 5+ pilot distributors within 12 weeks, 50+ expert profiles and 10+ active company projects in beta.

Success Metrics
  • 5+ pilot distributors signed within 12 weeks
  • 50+ expert profiles and 10+ active company projects in beta
  • Project completion rate — % of contracted projects that deliver usable knowledge assets
  • Expert retention — experts who complete one project and return for a second
  • MRR and 10-15% commission volume on expert transactions
  • Knowledge retrieval accuracy — answers are grounded in expert-provided content
  • Onboarding time reduction for buyers who deploy knowledge assets to new hires
Structured Payload

Machine-readable source fields

goal

Build a category-defining two-sided marketplace that connects retiring experts with manufacturers and distributors who need their knowledge captured, structured, and made AI-ready. Validate product-market fit with 5+ pilot distributors within 12 weeks, 50+ expert profiles and 10+ active company projects in beta.

users
goalnamepain
Earn meaningful flexible income, leave a lasting legacy, contribute without frictionRetiring Experts & SMEsNo platform respects their expertise or makes it easy to share — they have to write, which they hate
Capture knowledge before it walks out the door; get AI-structured outputs integrated into LMS/ERPDistributors & Manufacturers (Buyers)Key employees retire and knowledge disappears — new hires take years to get up to speed
Get up to speed faster, solve problems in the moment without calling the retired expertNew Employees & Field TechniciansGeneric manuals do not reflect real-world experience; no fast answer when standing in front of a machine
Build a defensible, scalable marketplace business with subscription + commission monetizationPlatform Owner (BezelIQ)Two-sided marketplace cold-start — need experts AND buyers simultaneously
problem

Manufacturing and distribution companies face an institutional knowledge cliff as experienced employees retire. Decades of irreplaceable tacit knowledge — product quirks, troubleshooting heuristics, application expertise — walks out the door with no scalable way to capture it first.

brand voice
tone

Professional and credible, grounded in real-world expertise. Never generic, never corporate-manual.

personality

The platform that bridges generations of knowledge — it takes retiring experts seriously as the source of truth and delivers their knowledge in forms that actually get used.

language rules
  • Speak to experts as professionals with valuable expertise, not as users of a tool
  • Speak to buyers in operational terms — knowledge assets, onboarding time, support deflection
  • Never say AI-generated — say expert-grounded or expert-informed
  • Use specific, measurable language; avoid vague claims
project name

KnowledgeVault AI

ux philosophy

Voice-first, guided — experts contribute without writing or tech expertise. Field technicians get answers hands-free in the moment, in natural language. Every interaction should feel like talking to someone who actually knows the answer, not reading a spec sheet.

scope boundary
in v1
  • Voice-first guided interview capture mode (Deepgram + GPT-4o real-time)
  • AI knowledge extraction and structuring — FAQs, troubleshooting guides, training modules
  • Expert marketplace — profiles, project posting, matching, contracting
  • Subscription tiers (Free / Pro / Enterprise) + marketplace commission model
  • Natural language knowledge retrieval for buyers and their employees
  • Basic LMS/ERP export of structured knowledge assets
  • Ground-truth gate — expert validates AI-extracted knowledge before payment bonus fires
out v1
  • Voice-activated hands-free field retrieval (mobile offline)
  • AI chatbot for customer/partner self-service deployment
  • Live mentorship / Q&A sessions between experts and employees
  • Legacy document and drawing upload with cross-referencing
  • Voice cloning for Virtual Expert
  • Counter-sales integration (reorder recommendations)
  • Proactive knowledge suggestion engine
non negotiables
  • Voice-first capture — experts must be able to contribute with zero writing or tech expertise
  • AI knowledge graph auto-structures captured content into searchable, reusable assets
  • Outputs are ERP/LMS-ready — knowledge must integrate into enterprise workflows to have value
  • Payment is reliable and transparent — experts must trust the platform to pay them correctly
  • Extraction must surface tacit knowledge — the AI asks follow-ups experts would not answer unprompted
success metrics
  • 5+ pilot distributors signed within 12 weeks
  • 50+ expert profiles and 10+ active company projects in beta
  • Project completion rate — % of contracted projects that deliver usable knowledge assets
  • Expert retention — experts who complete one project and return for a second
  • MRR and 10-15% commission volume on expert transactions
  • Knowledge retrieval accuracy — answers are grounded in expert-provided content
  • Onboarding time reduction for buyers who deploy knowledge assets to new hires
what wrong looks like
  • Expert completes a session but the output is shallow or generic — buyer cannot use it
  • New employee still calls the retired expert directly because the platform could not answer their question
  • Knowledge assets sit unused because they are not integrated into LMS or ERP
  • Expert drops off during onboarding because the platform requires too much technical effort
  • Company pays for a project and the knowledge captured does not justify the cost