# InfoPlatform.ai

> InfoPlatform.ai lets any team fine-tune an open-weight (or frontier) LLM on their own business data — with no ML expertise — and fully own the result: your data, your weights, your training, your inference. Upload data, pick a model (GLM 5.2, DeepSeek V4, Qwen 3.5, Kimi K2.6, Llama 4, or the open multimodal Inkling via Thinking Machines' Tinker API) and a training provider, and get a production OpenAI-compatible API endpoint that drops into OpenCode, Cursor, LangChain, or any OpenAI-SDK app with a one-line base_url swap — plus model-level MCP tool connections.

Key positioning: data privacy (your data never trains anyone else's model; optional delete-training-data-after-training), cost (~1/5 of closed-model cost), and weight ownership (export your open-weight adapter). Target users: technical-but-lean teams, founders, and privacy/cost-sensitive orgs — banks, law firms, security engineers, SaaS support and engineering teams — who want custom AI without an ML team or vendor lock-in. Use cases include customer support automation, code-review/coding agents trained on your repo, legal contract drafting, and post-quantum cryptography migration.

## Docs

- [Developer Docs](https://infoplatform.ai/docs/): Tested integration guides — OpenAI-compatible API (OpenAI SDK, LangChain, cURL) and MCP tool connections. Every example is verified against production before publishing.

## Product

- [Home](https://infoplatform.ai/): Product overview, models, training providers, pricing.
- [Sign up](https://infoplatform.ai/signup): Free trial — upload data, run a feasibility check, train a model in hours.

## Blog

- [Blog](https://infoplatform.ai/blog): Guides and insights on fine-tuning open-weight LLMs, custom AI models, customer support AI, code review AI, legal AI, and industry trends. New posts published daily.

## Policies

- [Privacy](https://infoplatform.ai/legal/privacy)
- [Terms](https://infoplatform.ai/legal/terms)