Bitween AI is coming to your integration layer.
AI that drafts mappings, explains failures and lets agents work with your integrations, built on the controls Bitween already has: permissions, previews, retry budgets and an audit trail nobody can edit.
Capabilities on this page are under development and may change before release.
You
Draft rules
What's coming
AI where integration work actually takes time.
Mapping, diagnosing failures and finding the right exchange are where integration teams spend their days. That's where Bitween AI starts.
AI-assisted mapping
Describe the target, paste samples, and get draft mapping rules, with transforms, lookups and list filters included. Drafts run through the same server-side preview as hand-written rules and are never saved without review.
Failure explanations
A plain-language summary of why an exchange or a whole retry chain is failing, drawn from the exception, the response body and the pipeline configuration, with the change most likely to fix it.
Retry policy suggestions
Proposed matchers and budgets based on the failures a subscription actually sees, checked in the policy test panel before anyone saves them.
Ask your exchanges
“Failed shipment updates for Contoso this week” becomes a real exchange filter: in the URL, shareable, and limited to what your role can see.
MCP server for agents
Give AI agents Bitween tools through the Model Context Protocol. Each agent acts as a member with a role, so it can only do what that role allows, and every change lands in the audit trail.
Bring your own model
Self-hosted means your choice of model provider, or a model you run yourself. Payloads are never sent anywhere you have not configured.
Agents can call Bitween today
Available nowAn AI agent is just another partner. Give it an API key and point it at an API gateway: its documents are validated, mapped, delivered, retried within budget and recorded exactly like any other partner's.
Principles
The rules Bitween AI is being built by.
Integration is where AI meets money, patients, shipments and customers. It has to earn trust the same way the rest of the platform does.
Drafts, not deploys
AI proposes. People review, preview and save. Nothing changes production on its own.
Permissioned
AI features act with the permissions of the member or role using them, never more.
Audited
Configuration changes made with AI help are recorded like any other change, with before and after.
Private by default
No payload leaves your environment unless you connect a model provider yourself.
Grounded in the pipeline
Suggestions are checked by the same mapping preview and policy tests that already exist.
Why it belongs here
The guardrails AI needs already exist in Bitween.
Enterprises are discovering that agents need identity, validation, limits and evidence. Those are integration problems, and Bitween solved them for partners first.
- An agent needs an identity and credentialsPartners with their own API keys, revoked in one click
- Agent output can be malformed or incompleteValidators reject bad input before anything is stored
- A looping agent can hammer an endpointRetry policies with per-message caps and shared budgets
- You need to prove what an agent didEvery exchange keeps its input, output, response and result
- Someone must own every configuration changeAn audit trail with old and new values that no API can edit
- Agents should only reach approved systemsNamed data sources, named SQL statements and bound parameters
Help shape Bitween AI.
Early-access teams see capabilities first and tell us which problems matter most. Tell us about your integrations and where AI would save you time.