Kiln-AI/Kiln
Build, Evaluate, and Optimize AI Systems. Includes evals, RAG, agents, fine-tuning, synthetic data generation, dataset management, MCP, and more. observed · 2026-08-28
Health v2 · maintenance only
90/100
- Activity 99
- Release rhythm 98
- Longevity 55
Flags: no_license
How is this computed?
round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10) — computed 2026-09-03. Adoption (stars, forks) is never an input.
- gap_med: 19
- age_days: 771
- days_rel: 13
- days_push: 7
- n_releases_24m: 34
Adoption not part of the score
5034 stars · 375 forks observed · 2026-08-28
What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-29, confidence not recorded
Kiln is a free desktop app and MIT-licensed Python library for the full AI development loop: evals, prompt optimization, RAG, agents, fine-tuning, synthetic data generation, and MCP tooling. It emphasizes team collaboration with git-based dataset versioning and lets non-engineers rate outputs and contribute data without code.
Use cases
- evaluate llm output quality with llm-as-judge evals
- build a rag pipeline over my pdf documents
- auto-optimize prompts against evals
- fine-tune a smaller model from gpt-4o outputs
- generate synthetic training data for fine-tuning
- build multi-agent systems with subagents and mcp tools
- collaborate with PMs and QA on rating ai outputs
- run ai models locally offline with ollama
When to choose
- you need an end-to-end workbench covering evals, RAG, agents, and fine-tuning in one tool
- non-technical teammates (PMs, QA, domain experts) must contribute ratings and datasets
- you want eval-driven prompt optimization or model comparison with cost/latency data
- you want local-first datasets versioned in git with no vendor lock-in
When to avoid
- you only need a lightweight programmatic library without a desktop app
- you require a fully permissive license for the app itself (the app is source-available, only the Python library is MIT)
- you need heavy custom infrastructure-level orchestration beyond Kiln's abstractions
- you depend on Kiln Pro features but cannot use hosted services
Facets
application · maturity active
machine-learning rag agent-framework prompt-engineering llm-training data-generation mcp chatbot developer-tools artificial-intelligence machine-learning large-language-models developer-tools data-science windows python cross-platform evals fine-tuning synthetic-data llm-as-judge prompt-optimization dataset-management collaboration desktop-app ollama rlhf ai-agents retrieval-augmented-generation macos linux desktop
10 sources
- readme: https://github.com/Kiln-AI/Kiln · fetched 2026-08-28 · 31c85e0abe6d
- homepage: https://kiln.tech · fetched 2026-08-29 · 18bef926fcc9
- site_page: https://docs.kiln.tech · fetched 2026-08-29 · 64fa3474254e
- site_page: https://kiln.tech/features/rag · fetched 2026-08-29 · 117f7a3e03cc
- site_page: https://kiln.tech/features/skills · fetched 2026-08-29 · 627874ae22c6
- site_page: https://kiln.tech/features/tools-mcp · fetched 2026-08-29 · 8b50e4f6ccb9
- site_page: https://kiln.tech/features/agents · fetched 2026-08-29 · 499f5449914f
- site_page: https://kiln.tech/features/evals · fetched 2026-08-29 · 7d86f823499c
- site_page: https://kiln.tech/features/auto-optimize · fetched 2026-08-29 · 8124226e4253
- site_page: https://kiln.tech/pricing · fetched 2026-08-29 · 789ea9281240
Member repositories
| Repository | Role | Health v2 |
|---|---|---|
| Kiln-AI/Kiln | main | 90 |
For agents
Data as of 2026-08-30T08:39:29.467469+00:00 · Report a problem