Contracts, invoices, regulations, customers, hours. Structured, parameterized and available over MCP in Claude, ChatGPT or Gemini.
Contracts, invoices, regulations, records, hours.
Every document turned into fields: parties, amounts, dates.
The standard bridge between your data and AI.
Claude, ChatGPT and Gemini query your real data.
We define the fields that matter — parties, amounts, dates, clauses — and turn stacks of documents into clean, validated tables.
We build the connector between your database and AI: what can be queried, by whom, all of it logged. One connector serves every engine.
Natural-language search, reconciliation, expiry alerts, and agents that carry out tasks under supervision.
Every fragment of the document finds its field in the table. That is what parameterizing means.
Real, high-stakes documentation — where the result shows most.
MCP (Model Context Protocol) is an open standard, created by Anthropic and adopted across the major AI providers, for connecting data sources and tools to AI models securely and consistently.
The practical difference: instead of asking a model what it believes about a contract, you ask your own database which ones expire this quarter — and the answer comes from your data, with permissions and an audit trail. AI has become the interface; MCP is how your company plugs into it with data of its own.
A real conversation with the MCP server connected. The middle step is the point: the AI does not guess, it queries.
A working first flow in weeks, not months.
Which documents exist, where they live, and which ones hurt most.
Which fields get extracted, and under what rules.
AI extraction, with human review where it counts.
Your database, connected to the engine you choose.
It is the piece of software that implements the Model Context Protocol on top of your data. It defines what an AI engine may query or operate — for example, "find contracts by expiry date" or "log billable hours" — under which credentials, and it records every call. You build it once and connect it to any compatible engine.
Claude (Anthropic), ChatGPT (OpenAI), Gemini (Google) and any client that supports MCP, including working environments such as Claude Code and your own internal agents. The standard is open, so you are not locked into one vendor.
Contracts, invoices and bank statements, regulations and official filings, case law, customer records, timesheets, minutes and powers of attorney, property titles, complaints. If it is written down — in a PDF, a photograph or a legacy system — it can be structured. We define together which fields are worth extracting.
In your own database: your server, your cloud, or whichever we agree on. The MCP server exposes only the operations you authorize; the AI engine queries your data, it does not take the database with it, and nothing is used to train models.
No — it connects to them. The whole point of MCP is to add an AI layer on top of the systems you already run: your billing ERP, your CRM, your time-tracking system. AI becomes one more interface over the same data.
First conversation is free. Pick your channel:
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