MIAPI

What is MIAPI?

If you're building an AI feature that needs to be factually accurate, MIAPI solves the problem most LLM APIs don't: it grounds every answer in real-time web search results and attaches inline citations so you know exactly where the information came from. The core product is a single API call that returns a web-grounded answer, source URLs, citation markers, and a confidence score. It's built as an OpenAI-compatible drop-in — swap the base URL and it slots directly into anything already calling /v1/chat/completions, including LangChain pipelines and Cursor integrations. For developers who've spent time wrestling with hallucinations in production, that's a meaningful shortcut. **Response accuracy** is the main differentiator. Rather than relying on a model's training data, each query runs a live web search, retrieves sources, and uses them to construct the answer. The inline citation format [1][2] links directly to source material, which matters for any use case where users need to verify or trace information. Beyond standard Q&A, there are dedicated endpoints for news search and image search, a raw search-only mode for teams building their own RAG pipelines, and a knowledge…