What is Kiln AI?
Kiln is an integrated desktop application designed to dramatically simplify the process of building powerful, custom AI models. It addresses the complexity of AI development by providing an intuitive, zero-code environment for fine-tuning, synthetic data generation, and evaluation. Kiln empowers your entire team—from engineers and data scientists to product managers—to collaborate effectively and create highly specialized AI.
Key Features
🎛️ Zero-Code Fine-Tuning Create highly specialized models tuned precisely for your use case. Kiln’s intuitive interface lets you fine-tune leading models like Llama and GPT-4o without writing any code and handles the serverless deployment for you, turning a complex process into a few simple clicks.
🤖 Interactive Synthetic Data Generation Move past data bottlenecks by generating high-quality training and evaluation datasets on demand. Kiln’s interactive visual tools give you direct control to create the exact data you need, ensuring your models are trained on relevant, well-structured information.
📊 Comprehensive Model Evaluations Iterate on your models with objective confidence. Kiln provides a robust suite of evaluation tools, including human preference ratings, allowing you to accurately measure model quality, align outputs with your goals, and make data-driven improvements.
🤝 Seamless Team Collaboration Empower every stakeholder to contribute to model quality. Kiln integrates directly with Git, allowing engineers, PMs, and QA specialists to collaborate on datasets, prompts, and ratings using a familiar, version-controlled workflow that everyone understands.
How Kiln Solves Your Problems:
Kiln is built to remove friction and accelerate your AI development cycle, regardless of your role.
For Data Scientists & ML Engineers: You can rapidly prototype new techniques and models in seconds. Instead of working from vague specs, you can use Kiln to build golden datasets, run evaluations, and share concrete, version-controlled results with your team. The open-source Python library and local-first design give you full control and extensibility.
For Product Managers & QA: You can directly influence the quality and alignment of AI models without needing to code. Use Kiln’s clear interface to generate data, rate model outputs, and contribute to evaluations, ensuring the final product meets user expectations and business requirements.
For Developers & Startups: You can build and deploy a custom, fine-tuned model from scratch with remarkable speed—one user reported it was 90% faster than manual tuning. Kiln provides all the tooling you need in one place, enabling small teams to achieve results that previously required dedicated ML specialists.
Unique Advantages
Privacy-First by Design Kiln is local software that runs directly on your machine. Your datasets, models, and API keys never leave your control and are never sent to our servers. This local-first architecture gives you complete privacy and security, with source code available on GitHub for full transparency.
Run Any Model, Anywhere Avoid vendor lock-in and maintain full flexibility. Kiln works seamlessly with models running locally via Ollama or through any major provider, including OpenAI, AWS, Groq, OpenRouter, and Azure. You have the freedom to choose the best and most cost-effective model for the job, without limitations.
Conclusion:
Kiln provides a complete, intuitive, and secure toolset for building powerful, custom AI models. By unifying fine-tuning, data generation, and evaluation in an accessible desktop application, it empowers your entire team to collaborate and innovate with greater speed and precision.
More information on Kiln AI
Launched
2024-10
Pricing Model
Free
Starting Price
Global Rank
6059447
Follow
Month Visit
<5k
Tech used
Top 5 Countries
75.55%
11.59%
9.41%
3.45%
United States
Turkey
Belgium
Canada
Traffic Sources
7.37%
1.15%
0.07%
15.94%
10.06%
65.24%
social
paidReferrals
mail
referrals
search
direct
Source: Similarweb (Sep 25, 2025)
Kiln AI was manually vetted by our editorial team and was first featured on 2025-07-29.
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