Systems Integrations

An AI deployment is really only useful when it lives where the work is actually happening. In practice, that means inside the systems your team is already using every day, rather than off in some separate console that nobody opens after week two.

What we connect to

Most things. The ones that come up constantly include the following.

• Databases. PostgreSQL, MySQL, MongoDB, SQL Server, Snowflake, BigQuery, and whatever custom data warehouse you happen to run.
• Communication tools. Slack, Teams, Discord, Twilio, and email over both SMTP and IMAP.
• Productivity and CRM. Google Workspace, Microsoft 365, Salesforce, HubSpot, Notion, and Airtable.
• Cloud and APIs. AWS S3, Azure Blob, GCS, plus essentially any HTTP/REST or GraphQL endpoint you can point us at.
• Files and queues. SFTP, message queues, and webhooks. All the plumbing nobody really wants to write themselves.

For anything that isn't on that list, we build the integration. It's pretty rare for us to hit a system we can't reach.

How we configure each one

Every integration gets hardened during onboarding. That includes scoped credentials, network rules, retry and rate-limit handling, error recovery, and audit logging. The integration is treated as part of the deployment we operate, rather than as something your team has to babysit on the side.

What this saves you

Roughly the six to twelve weeks it would otherwise take your engineers to build, test, and harden the connectors themselves, along with the ongoing on-call burden of keeping them all running afterward.

Tell us what you need to connect, and we'll tell you what it would take.