Source: https://reclaimllm.com/
Your AI work. Reclaimed.Every AI conversation
is yours. Start treating it that way. RCLM captures every LLM interaction you generate — across every provider, every interface, every tool. Search it, reuse it as context, and govern it across your team. Get started free→ See how it works rclm search $ reclaimllm search “debugging the auth issue” ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ Found 12 sessions matching query ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 2h agoClaude Code47 msgsauth middleware refactor 3d agoChatGPT 23 msgsJWT token debugging session 1w agoClaude.ai 31 msgsOAuth callback fix + tests 2w agoGemini CLI 18 msgssession expiry edge cases ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 3 capture methods 4+ LLM providers 100% your data 0 lock-in The problemYour AI work vanishes into provider silos.
Every debugging session, every architecture discussion, every data pipeline you built through Claude Code or ChatGPT — that work disappears. Lost to ephemeral chat histories, unlogged API calls, disconnected tools. You can’t search it, can’t reuse it, can’t audit it. It’s your intellectual output, and you have zero control over it. Before RCLM- ✕Chat history lost when tab closes
- ✕No search across providers
- ✕API calls completely untracked
- ✕Zero visibility into AI costs
- ✓Every session indexed permanently
- ✓Full-text search across all tools
- ✓File diffs from every coding session
- ✓Per-session token and cost tracking
- ✓Reusable context across tools
- ✓Enterprise audit trail
- ✓Org-level AI governance
- ✓Usage and cost visibility
Three steps from invisible to indispensable.
01Capture
Three methods — pick what fits how you work. Local proxy for API calls (set one env var). Native hooks for Claude Code and Gemini CLI sessions. Chrome extension for ChatGPT, Claude.ai, and Gemini in the browser. All three produce the same normalized session record. Use one or all. 02Store & Search
Every session is indexed with full-text search and auto-organized with AI-generated titles, descriptions, and tags. Sensitive content — credentials, tokens, PII — is flagged automatically. Metadata searchable instantly. Full conversation blobs (messages, tool calls, file diffs) fetched on demand. 03Reuse & Govern
Export sessions for your own analysis, bring prior work into new assistants, or use the enterprise layer to govern your team’s AI usage. Context export, JSON export, and org-level visibility are the current focus. What you can doYour chat history is more valuable than you think.
⌕Search everything
Full-text search across every provider, model, and session. Find that debugging insight from three weeks ago in seconds. ◈Debug and replay
Full session logs show every step, every file change, every tool call. When an AI workflow goes wrong, you can see exactly what happened. ↗Reuse prior context
Carry forward debugging sessions, architecture decisions, and implementation details without rebuilding the same background in every new assistant. ⬡File diffs from hooks
Native Claude Code and Gemini CLI hooks capture every file the agent created or changed — before and after — in a structured diff. The highest-value data in the system. ⊞Enterprise governance
Visibility into which models your developers use, what proprietary code flows to third-party APIs, and where your AI spend is going — by team and project. ◉Works everywhere
Browser extension for ChatGPT, Claude.ai, and Gemini. Local proxy for API calls. Native hooks for Claude Code and Gemini CLI sessions. For individualsYour AI output is your intellectual property.
Every debugging session you close, every architecture you design, every workflow you build with AI — that’s your work. RCLM captures it permanently. Search it, debug with it, export it, and reuse it as working context when the next task starts.- →Free forever for personal use
- →Full-text search across all your sessions
- →AI-generated titles, tags, and descriptions
- →Sensitive content flagged automatically
- →Export to JSONL, HuggingFace, and more
Full observability over how your team uses AI.
Which models are your developers using? What proprietary code is flowing to third-party APIs? Where is the AI spend going? RCLM gives engineering leaders the visibility and control they don’t have today.- →Org-wide usage dashboard with team and cost attribution
- →Detect proprietary code or credentials sent to external APIs
- →Audit trail: searchable history of all AI interactions
- →Role-based access control across teams
- →On-premises deployment option — no data leaves your VPC