DecisionVault
A decision journal for small operations teams using AI assistants that records why each choice was made, flags when a new AI suggestion resembles a past decision, and keeps the reasoning alive after the chat session closes.
Operations leads at small companies whose teams rely on AI assistants to draft policies, vendor choices, and process changes
- One-click capture of the reasoning behind any AI-assisted decision
- Smart alerts when a new AI suggestion overlaps a previously reversed decision
- Stakeholder and evidence tags that survive across AI providers
- Read-only audit log exportable for compliance or board reviews
Selvedge's Dev.to traction and the comment thread about 'stale decisions' show real demand from small teams getting burned by AI repeating mistakes their org already paid to learn.
Concept validated by Selvedge (selvedge.sh) which captures AI reasoning for codebases, plus active content ecosystem (Sugarbug, Pactify decision-log posts), but the Dev.to post about 'stale decisions' could not be directly verified and the target audience (non-coding ops teams using AI assistants) is narrower than the dev-tooling wedge.Long-term memory for AI-coded codebases. | selvedge ↗Decision Log for Startups - Sugarbug ↗
Selvedge is scoped to AI coding agents; Decisions.com targets meeting management; Pactify/Sugarbug are Notion-template content plays. No direct competitor focuses on AI-assistant decision provenance for ops/policy/vendor choices — a distinct niche, though the total addressable market is also smaller.Selvedge: AI Agent Reasoning & Codebase Memory for Devs ↗Decisions: AI Meeting Management for Microsoft Teams ↗
Small ops leads are notoriously price-sensitive; competing Notion templates and DIY approaches are cheap. AI-agent pricing spans $0–$50k/mo per nocodefinder, but willingness to pay specifically for decision provenance (vs. coding memory where Selvedge is free MCP) remains unproven for a non-dev audience.AI Agent Pricing 2026 Complete Cost Guide & Calculator ↗
As long as teams use AI assistants for consequential decisions, the need for durable decision memory persists.
Buildable with LLM API, vector embeddings for similarity detection, and lightweight storage; comparable in scope to Selvedge (a local MCP server). Not trivial but well-trodden stack.