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recensa
Recensa is a self-hosted web viewer that indexes Claude Code session transcripts into a local SQLite database, enabling full-text search, replay, and audit of all past agent conversations without uploading data anywhere.
AI repository intelligence
FR-AI / ANALYSISWhy it is worth attention
It combines multi-model support, autonomous multi-step agents, and a local knowledge engine with an open-core model that allows self-hosting and commercial use, while restricting only direct hosted service competition.
Who it is for
- Developers building AI-powered applications
- Knowledge workers and researchers managing large document sets
- AI enthusiasts who want to run models locally or self-host
- Organizations seeking a private, on-premises AI workspace
Use cases
- Automated research and analysis with multi-step agent tasks
- Building and sharing reusable artifacts from agent outputs
- Local document Q&A using RAG with custom models
- Prototyping and testing multiple LLMs in a unified interface
Strengths
- Supports a wide range of models including Anthropic, OpenAI, Google Gemini, and local Ollama
- Open-core licensing allows self-hosting and commercial derivative products
- Built-in autonomous agents with parallel task execution and human-in-the-loop
- Comprehensive RAG engine with smart chunking, vector search, and collections
Considerations
- BUSL-1.1 license prohibits offering the software as a competing hosted service
- Self-hosting requires Docker setup and configuration of multiple services
- Advanced features like multi-tenancy and billing are closed-source
README quick start
Bike4Mind
Your bicycle for the mind in the age of AI.
An open-core AI knowledge platform — a multi-model workspace where notebooks, autonomous agents, and a RAG knowledge engine work together to augment any cognitive task.
What is Bike4Mind?
Bike4Mind is an AI-powered knowledge platform that wires a superset of AI technologies together behind one workspace. Bring your own models, keep your data, and let agents do the heavy lifting.
- Notebooks — the core workspace: chat, documents, and context in one place, across any model.
- Multi-LLM by design — swap freely between Anthropic, OpenAI, Google Gemini, xAI, Ollama (local), and more, plus image models (FLUX, DALL·E 3, Stable Diffusion).
- Quest Master — autonomous, multi-step task planning: text and image generation, vision review, web search, math, code, and human-in-the-loop steps, run in parallel.
- AI Agents — autonomous ReAct-style agents that carry out complex tasks against your tools and knowledge.
- Knowledge Engine — RAG over your documents: smart chunking, vector search, collections, and tagging so agents can reason about what you know.
- Artifacts — reusable snippets, documents, and visualizations produced by agents, with a built-in publish-and-share layer.
Try the hosted service at app.bike4mind.com, or self-host the open core on your own infrastructure (below).
Open core
Bike4Mind is open core. The engine is public and self-hostable; the multi-tenant hosted service is our business.
- Open (this repo, BUSL-1.1): the agent engine, LLM adapters, CLI, data models, and the self-host path — published as
@bike4mind/*packages. - Commercial / closed: operating the multi-tenant hosted service — billing, entitlements, hosted infrastructure — and premium overlays such as Overwatch.
See CONTRIBUTING.md for the exact open/closed boundary.
Quickstart
Hosted (fastest): sign in at app.bike4mind.com — nothing to install.
Self-host: run the open core on your own hardware with Docker — no AWS account or cloud provider required. See the **[Self-Host Quickstart](./
Description
The open-core AI workbench — notebooks, agents, RAG, voice, and images across any model: OpenAI, Anthropic, Google, xAI, or local via Ollama/vLLM. BSL 1.1, auto-converting to Apache-2.0 on a two-year clock. Your AI keeps running when theirs doesn't.
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