Ross ROSS = Recommend OSS · open-source software intelligence for agents

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

github.com/Kiln-AI/Kiln · homepage · Python · NOASSERTION (other) 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

Full methodology

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

Member repositories

RepositoryRoleHealth v2
Kiln-AI/Kilnmain90

For agents

markdown · JSON · MCP: product_card(name="Kiln-AI/Kiln")

Data as of 2026-08-30T08:39:29.467469+00:00 · Report a problem