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ContextBase for AI and automation Your healthcare systems, as one MCP server

Claude, ChatGPT, and your own agents read the same approved knowledge, under each person’s access. Every run is logged with who asked.

In production with a large national payer, a regional health plan, a PBM, and a large TPA

  • HITRUST i1
  • SOC 2 Type 2
  • Every run logged

One platform for enterprise AI

Put every assistant, agent, and automation on one knowledge graph your team owns. One context, one set of permissions, every run on record.

Connected use cases

ReviewLibraryAI recall corpus 248 of 352 eligible
All566
PITFALLS104
SKILLS & RECIPES76
METRICS88
DEFINITIONS & NOTES121
CONCEPTS149
ANALYSES & DECKS28
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KnowledgePitfallsDemo data
PitfallEndorsedEdit

Claims paid on an authorization that was denied

Authorization rows marked Denied have a matching claim that paid in full.

Endorsed by Payment integrity lead · Jul 8 · recalled in 10 answer runs

Fresh · review due Nov 5

Adjudication never reads the authorization status, so a denial does not stop payment. Join claim_header to authorization_case on claim_id and keep rows where status is Denied and plan paid is above zero.

Many of these are legitimate. An overturned appeal leaves an appeal_overturn row in inquiry_case, so exclude those matches and report both numbers. Counting the whole population as improper payment overstates the finding and puts the appeals team in the frame for doing its job.

Applies to
auth.authorization_caseclaims.claim_headercases.inquiry_case

ConnectedPart of Authorization

Demo data

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Enterprise AI context

Claude, ChatGPT, and your own agents read the same approved knowledge over MCP, with each person’s access carried through.

Reads
definitions · pitfalls · permissions
From
knowledge graph · identity
Delivers
one context for every agent

Your first answer, on your own data.

  1. 01Pick the question

    Choose one question and the systems that answer it, with our team.

  2. 02Connect one system

    Connected and mapped in days. Access is approved and time-limited, and every query lands on the audit trail.

  3. 03Check the answer

    The answer arrives with its queries, rows, and checks. Your team can test it against the source.

Questions teams bring first

Security

Built to pass your security review

  • HITRUST i1 and SOC 2 Type 2

    Audited every year. The certification letter is public, and reports are available on request.

  • Your access, carried through

    Each person’s access carries through to their agents. If a person cannot see a table, their agent cannot either.

  • An audit trail you own

    Every run is logged with who asked and what it read. The audit trail is yours to export.

  • Never trains a model

    Your data, definitions, and queries never train a model, and nothing you send is kept at the model layer.

Questions

What teams ask before they start

Does it work with Claude and ChatGPT?

Yes. Claude, ChatGPT, and your own agents reach ContextBase over MCP. They answer from the same approved knowledge, under each person’s access.

Which models does it run on?

The ones your team chooses. Test a new model against your own question set before anyone relies on it, and switch when it passes.

Can we see what every agent did?

Yes. Every run is logged with who asked, the queries it ran, and what it read. The audit trail is yours, and you can export it to your own systems.

How do we keep AI spend in check?

Track what each person and team spends against the budgets you set. Dashboards you build in ContextBase refresh without spending tokens, so recurring reports stay off the meter.

Does our data leave our control?

ContextBase reads your systems where they sit, over the private route your network team picks, through the grants you set. Your data stays with you, in your own cloud storage or in Google Cloud. PHI protections are set per deployment, and we sign a BAA. See security