Kiln
Intuitive app to build your own AI models.
About Kiln
Kiln is an innovative AI development platform designed to empower both engineers and non-engineers to build, evaluate, and deploy AI models efficiently. As of 2026, Kiln stands out as a comprehensive no-code solution for synthetic data generation, fine-tuning, and dataset collaboration. By offering tools such as evals, RAG, and agents, Kiln allows users to create custom AI models tailored to specific use cases without the need for extensive coding knowledge. This makes it an ideal choice for startups, research institutions, and large enterprises alike. Kiln's local software ensures data privacy, as all datasets are stored on the user's hard drive, providing peace of mind in an era where data security is paramount. With a growing community of over 10,000 users, Kiln continues to be a preferred tool for AI development, offering a seamless integration with platforms like OpenAI, AWS, and Azure. Its open-source Python library further enhances its appeal, allowing for customization and flexibility. Kiln's commitment to privacy, ease of use, and powerful features make it a leading choice for those looking to innovate in the AI space in 2026.
Kiln Key Features
No-Code Synthetic Data Generation
Kiln allows users to generate synthetic data without writing any code. This feature is particularly valuable for creating large datasets for training AI models, especially when real data is scarce or privacy concerns limit data availability. Users can interactively control data generation parameters to tailor datasets to their specific needs.
Fine-Tuning
Kiln provides tools for fine-tuning AI models, enabling users to adapt pre-trained models to specific tasks or domains. This feature is crucial for improving model performance on niche applications without requiring extensive computational resources or deep expertise in machine learning.
Dataset Collaboration
Kiln facilitates collaboration on datasets through integration with Git and shared drives. This feature allows teams to work together seamlessly, sharing and versioning datasets, which enhances the efficiency and accuracy of AI model development.
Evaluations (Evals)
Kiln's evaluation tools help users assess model performance and alignment with human preferences. This feature supports iterative development by providing insights into model strengths and weaknesses, enabling users to make informed improvements.
Retrieval-Augmented Generation (RAG)
Kiln supports RAG, allowing users to build systems that combine retrieval of relevant documents with generative AI capabilities. This feature is valuable for applications requiring accurate and contextually relevant responses, such as chatbots and information retrieval systems.
Agentic Systems
Kiln enables the creation of agentic systems with multiple actors, allowing for complex interactions and decision-making processes. This feature is particularly useful for simulating environments or developing AI-driven automation solutions.
Tools & MCP Integration
Kiln allows users to enhance their AI systems by integrating tools and MCP (Model Control Protocol) servers. This feature expands the capabilities of AI agents, enabling them to perform a wider range of tasks and interact with external systems.
Open-Source Python Library
Kiln offers an open-source Python library that provides access to its core functionalities. This feature allows developers to integrate Kiln's capabilities into their own applications, fostering innovation and customization.
Kiln Pricing Plans (2026)
Free
- No-code synthetic data generation
- Fine-tuning tools
- Dataset collaboration
- Evals and RAG
- Local data storage
- Future pricing changes for large corporations
- Local storage requirements
Kiln Pros
- + Intuitive no-code interface that democratizes AI model development.
- + Strong commitment to data privacy with local data storage.
- + Comprehensive feature set including synthetic data, fine-tuning, and evals.
- + Open-source Python library for customization and flexibility.
- + Seamless integration with major platforms like AWS and Azure.
- + Free to use, with potential future pricing for large corporations.
Kiln Cons
- − Limited to local software, which may not suit cloud-centric workflows.
- − Potential learning curve for non-technical users despite no-code design.
- − Future pricing changes could impact large corporations.
- − Currently lacks a dedicated mobile app for on-the-go access.
- − May require substantial local storage for large datasets.
Kiln Use Cases
Rapid Prototyping for Startups
Startups can use Kiln to quickly prototype AI models tailored to their unique business needs. By leveraging no-code data generation and fine-tuning, startups can iterate rapidly and bring AI-driven products to market faster.
Academic Research
Researchers can utilize Kiln to explore new AI techniques and models. The platform's dataset collaboration and evaluation tools support rigorous experimentation and validation, making it ideal for academic settings.
Enterprise AI Solutions
Enterprise teams can deploy Kiln to develop and fine-tune AI models for various business applications, such as customer service automation and predictive analytics. The platform's integration capabilities ensure seamless deployment across different environments.
AI-Driven Content Generation
Content creators can use Kiln's RAG and agentic systems to generate contextually relevant content, such as articles or marketing materials. This use case highlights Kiln's ability to enhance creativity and productivity in content generation.
Healthcare Data Analysis
Healthcare professionals can leverage Kiln to analyze patient data and develop predictive models for disease diagnosis and treatment planning. The platform's data privacy and security features ensure compliance with healthcare regulations.
Financial Risk Assessment
Financial institutions can use Kiln to build models that assess risk and detect fraudulent activities. The platform's fine-tuning and evaluation tools allow for precise model adjustments to meet regulatory standards and business requirements.
What Makes Kiln Unique
No-Code Approach
Kiln's no-code features make it accessible to users without extensive programming skills, allowing a broader audience to develop and deploy AI models.
Comprehensive Toolset
Kiln offers a wide range of integrated tools, from synthetic data generation to model evaluation, providing a one-stop solution for AI development.
Open-Source and Local
Kiln's open-source Python library and local deployment ensure transparency, security, and control over data, differentiating it from cloud-based competitors.
Collaboration Features
Kiln's integration with Git and shared drives facilitates seamless collaboration on datasets, making it ideal for team-based AI projects.
Versatile Integration
Kiln's ability to connect with various platforms and APIs, such as OpenAI and AWS, allows users to deploy models in diverse environments, enhancing flexibility and scalability.
Who's Using Kiln
Enterprise Teams
Enterprise teams use Kiln to develop custom AI solutions that enhance operational efficiency and drive business growth. The platform's integration capabilities and dataset collaboration features support large-scale deployments.
Academic Researchers
Researchers in academia use Kiln to experiment with new AI models and techniques. The platform's open-source library and evaluation tools facilitate rigorous scientific inquiry and innovation.
Startups
Startups leverage Kiln to quickly prototype and iterate on AI models, enabling them to bring innovative products to market faster. The no-code features make it accessible to teams with limited technical expertise.
Data Scientists
Data scientists use Kiln to explore and test new models and techniques. The platform's fine-tuning and synthetic data generation tools allow for rapid experimentation and model optimization.
Content Creators
Content creators use Kiln to automate and enhance content generation processes. The platform's RAG and agentic systems enable the production of high-quality, contextually relevant content.
How We Rate Kiln
Kiln vs Competitors
Kiln vs TensorZero
TensorZero is a cloud-based AI development platform that offers robust scalability and integration with various cloud services. While Kiln provides a no-code interface and local data storage for enhanced privacy, TensorZero excels in offering extensive cloud resources and scalability options.
- + Scalable cloud infrastructure
- + Wide range of integration options
- + Advanced analytics and reporting tools
- − Requires internet connectivity for full functionality
- − Potentially higher costs due to cloud usage
Kiln Frequently Asked Questions (2026)
What is Kiln?
Kiln is an intuitive AI development platform that allows users to build, evaluate, and deploy AI models without extensive coding knowledge, using features like synthetic data generation and fine-tuning.
How much does Kiln cost in 2026?
As of 2026, Kiln is completely free to use, though future pricing may apply to larger corporations with revenue over $10 million.
Is Kiln free?
Yes, Kiln is currently free to use, making it accessible for startups and small businesses.
Is Kiln worth it in 2026?
Kiln offers a comprehensive set of features and strong data privacy protections, making it a valuable tool for AI development in 2026.
Best Kiln alternatives in 2026?
Alternatives to Kiln in 2026 include TensorZero, Compass, Sourcely, Phoenix, and AI Detector.
Kiln vs competitors in 2026?
Kiln stands out with its no-code interface and local data storage, while competitors may offer different strengths such as cloud-based solutions or specialized features.
How to get started with Kiln?
To get started with Kiln, download the app from the official website, explore the documentation, and join the community for support and resources.
What platforms does Kiln support?
Kiln supports integration with platforms such as OpenAI, AWS, Azure, and more, enhancing its versatility for various use cases.
Is Kiln safe and secure?
Kiln prioritizes data privacy by storing all data locally on the user's hard drive, ensuring that sensitive information remains secure.
Who should use Kiln?
Kiln is ideal for startups, academic researchers, large enterprises, and anyone interested in AI development without extensive coding knowledge.
What's new in Kiln 2026?
In 2026, Kiln continues to enhance its feature set, focusing on improving user experience and expanding integration capabilities.
How does Kiln compare to alternatives?
Kiln offers unique advantages such as a no-code interface and local data storage, while alternatives may provide different benefits like cloud-based services or specialized AI tools.
Kiln Search Interest
Search interest over past 12 months (Google Trends) • Updated 2/2/2026
Kiln on Hacker News
VS Code Extension
Kiln Company
Kiln Quick Info
- Pricing
- Free
- Upvotes
- 63
- Added
- January 3, 2026
Kiln Is Best For
- Startups looking to innovate with AI without extensive technical resources.
- Academic researchers seeking a platform for AI experimentation.
- Large enterprises needing scalable AI solutions integrated with cloud infrastructure.
- AI developers and engineers interested in customizing AI tools.
- Non-technical users seeking to explore AI development with a no-code interface.
Kiln Integrations
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