What is Kiln?
Kiln is a workbench for the full AI development loop: evals, optimization, prompts, RAG, fine-tuning, synthetic data, agents, and tools - all working together. The desktop app lets your whole team contribute (PMs, subject-experts, and QA can rate outputs and add data without writing code). The MIT-licensed Python library ships the same tasks to production. Runs locally - bring your own API keys, or go fully offline with Ollama.
Highlights
Iterate, optimize, and collaborate
- 🖥️ Intuitive app - Easy-to-use apps for Mac, Windows, and Linux. One-click install.
- 📊 Eval Builder - Auto-generate evals (judge + synthetic eval dataset), and align to your preference in ~10 minutes.
- 🚀 Auto-Optimize - Automatically find the best way to run your AI task, optimizing prompt, model selection, tools, skills, subagents, parameters, and more.
- 💬 AI Assistant - Your AI data-science partner. Kiln Assistant proposes improvements, optimizes prompts, runs experiments, creates evals, and more.
- 🤝 Git-native collaboration - The app syncs to Git automatically — even for teammates who don't know what Git is.
Build & ship agents
- 🔍 RAG - Drag-and-drop docs (PDF, image, video, audio) to create a RAG. Auto-generated RAG evals from your own documents.
- 🤖 Subagents - Compose multi-agent hierarchies. Each runs in its own focused context window.
- 🪄 Synthetic Data Generation - Generate data for evals or fine-tuning in minutes.
- 🎛️ Fine-Tuning - Zero-code fine-tuning across 60+ models (Qwen, Llama, GPT, Gemini, …) on Fireworks, Together, and Vertex. Serverless deployment included.
- 🐍 Open Python library - Agents built in the app can be deployed to production. MIT open-source.
- 🧰 …and more - Tools & MCP, Skills, structured outputs, reasoning models, model library (190+ tested).
App Quickstart
Get started in minutes - one-click install.
Download Kiln Desktop for macOS, Windows, or Linux, then follow the 5-minute quickstart to run your first task.
Prefer to start in code? See the Python library quickstart.
Demo
Watch a 2-minute overview, or our end-to-end project demo (20 minutes).
Why Kiln?
Most AI tooling forces a tradeoff: a code-only framework that covers one slice (orchestration or evals or RAG), or a paid SaaS that locks in your data and can't be extended. Kiln is a free, local-first workbench where a single task and dataset flow through evals, prompt optimization, fine-tuning, RAG, agents, and synthetic data — all in one tool.
-
One dataset, every technique. Define a task once. Eval it, optimize the prompt, fine-tune a model, generate synthetic data, add RAG — all against the same dataset, with results that compound across stages.
-
Track every axis. Move fast. Don't regress. Keeping agents running well is hard — a prompt change quietly regresses behavior three steps downstream; a model upgrade improves five things and breaks two. Kiln tracks quality across every dimension you care about, so you iterate without breaking what already works.
-
Optimization, not just evaluation. Other tools tell you how a prompt scores, but not how to fix it. Kiln's Auto-Optimize searches across hundreds of prompt mutations and models to find what works best for every eval dimension.
-
GUI for the whole team, library for engineers. Kiln's desktop app lets PMs rate outputs, SMEs add training examples, and QA flag regressions — without a terminal. Engineers ship the same tasks via an MIT-licensed Python library. Data scientists can use the library in notebooks and experiments.
-
Local-first. Most AI platforms are SaaS-only. Kiln runs entirely on your machine. Bring your own API keys, or go fully offline with Ollama. Your data never leaves your control. Team-sync is provided via Git infrastructure you already own.
-
190+ models tested across every provider. Skip the guesswork — we've tested every model's capabilities across all major providers. OpenAI, Anthropic, Gemini, Bedrock, Ollama, OpenRouter, Fireworks, Groq, any OpenAI-compatible endpoint, and more. Swap models with confidence.
Open-source Python Library
Build AI tasks in the app. Deploy with the open-source library. Same engine, same project files, no rewrite. The MIT-licensed kiln-ai library is the same library used in the app. Load Kiln projects, run tasks, build fine-tunes, work in notebooks, integrate Pandas/Polars dataframes, and more.
pip install kiln-ai
This is the beginning of the README. Read the rest at the original. Read the full README ↗
