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AI-powered document search
Your documents, indexed for AI.

Quickly search your files and documents with AI, across 50+ filetypes and 80+ languages. Connect your documents, uploaded directly or synced from SharePoint and other cloud storage. We index and OCR them, and from then on you have a search layer of context for your AI work.

index4.ai plugs straight into your existing AI agent or chatbot. We OCR images, scanned PDFs, and even video, so everything you have becomes searchable. Fully managed, with no infrastructure for you to run.

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Works with
  • Claude
  • ChatGPT
  • MCP
  • OpenClaw

See it in action
Ask your documents anything.

Your assistant searches the index and answers with the source in hand: the clause from a contract PDF, the row from a spreadsheet, the diagram and page number from a manual, even the right moment in a training video. Documents in other languages come back just as easily.

Every answer carries its citation and its place in the document: section, paragraph, page. That's our patented structure-aware chunking at work: index4.ai knows where every passage sits, so people can check the source instead of trusting a guess.

  • 100% Recall on the OfficeQA benchmark: search that finds it every time
  • 23% Of the tokens standard chunking returns: same answers, fewer tokens
  • 50+ Filetypes searchable: PDF, DOCX, images, video… OCR included
  • 80+ Languages supported: search in any of them

Integration
Wire index4.ai into your agent.

Connecting takes a minute, whatever you run: Claude, ChatGPT, Cursor, or any agent that speaks MCP. Point it at index4.ai once and your documents are searchable from the conversation. No vector DB to provision, no embeddings to manage. Just a search endpoint your agent can call.

index4.ai is a connector in Claude's directory. Open the listing, click Connect, and sign in when your browser asks. No key, nothing to install.

Available in the Claude connector directory

Works with Claude on web, desktop, and mobile, and in Claude Code.

A signed one-click bundle for Claude Desktop. Download it, open it with Claude Desktop, and paste your project key into the API key prompt.

Download the .mcpb bundle

MCPB is the MCP bundle format: the whole server, packaged so Claude Desktop can install it in one step.

Add the hosted endpoint to any MCP client's config:

{
  "mcpServers": {
    "index4ai": {
      "type": "http",
      "url": "https://mcp.poma-ai.com/grill"
    }
  }
}

Prefer to run it locally? npx -y @poma-ai/poma-grill-mcp with your project key in POMA_API_KEY.

What it is
One index, top to bottom.

index4.ai builds a true index of what's inside each file, not a bag of text fragments. Every document gets an entry that mirrors its own structure: sections and subsections, tables kept as tables, figures and video scenes described in words. Each element keeps its place in the document, whether that's a section, a page, or a timestamp.

Structure and OCR are what set us apart. Because every element is indexed in its place, a query returns the exact elements along with the context that gives them meaning: a clause with its section, a table with its caption, a figure with its written description. OCR extends the index to scanned pages, images, and video, so content that plain text search never sees becomes findable. Your agents answer precisely, with the source in hand, and read fewer, more relevant tokens than raw text matching or naive chunking would return.

The index is powered by POMA AI's patented structural file chunking technology.

Part of one document's index entry. Structure preserved, every element searchable in place.

How it works
Three stages, no glue code.

Getting started is easy. Simply sign up and, if you want, set up an organisation and project to share with others. You can be searching your documents in minutes, powered by POMA AI's patent-protected chunking.

  • Connect: upload documents manually, through your AI agent, or with our CLI and developer toolsets, or use a cloud connector to sync SharePoint or any shared cloud drive. 50+ filetypes, with OCR for images, scanned PDFs, and video.
  • Index: as documents arrive they are organised into your index using our patented structure-aware chunking technique.
  • Search: the moment documents are indexed, they're searchable from your agent or chatbot through our SDK, API, or MCP servers, in 80+ languages.

Where it matters
Complex documents, in the industries that depend on them.

Contracts, policies, technical specs, clinical requirements: documents whose meaning lives in the relationship between clauses, tables, and footnotes. index4.ai preserves those relationships in the index, so a search finds the answer with its context intact.

Clauses retrieved with the definitions that bind them.

Finance & insurance

Policy terms paired with their coverage tables, always.

Engineering

Specs and tolerance tables retrieved together.

Medical

Requirements always arrive with their applicability criteria.

FAQ
Fair questions, straight answers.

What is the relationship between index4.ai and POMA AI?

index4.ai is built and operated by POMA AI, the Context Engineering company, and runs on POMA’s patent-protected structure-aware chunking technology. Your index4.ai account is a POMA account, and billing, docs, and support are shared.

Does an AI index still matter with the arrival of MCP?

Yes. MCP standardizes how AI tools connect to data sources and tools, but it does not decide which information is relevant. index4.ai serves your agent the right content over MCP, selecting, structuring, and delivering it, which becomes even more valuable as MCP adoption grows.

What happens when context windows get (much) larger?

Larger context windows theoretically reduce hallucinations by letting models see more at once, but in practice they are expensive to compute and often still miss or skim important details in the middle of long inputs. It is neither practical nor cost-effective to load everything into every prompt, so an effective index stays necessary even with very large windows.

Do I need my own vector database or embeddings?

No. Everything is handled end-to-end: there are no embeddings to manage and no vector database to run. You simply connect your documents and search the index from your agent or chatbot.

Ready to get started?
Sign up and start in minutes.

All you need is to sign up, grab your project key, and connect your documents. The free tier covers 5,000 pages and 1,000 queries. Point index4.ai at a document and start searching.

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