CUSTOM API INTEGRATION
Custom API Integrations for Systems That Were Never Introduced
If no off-the-shelf connector exists between your CRM and your proprietary or legacy system, I build that connector, document it, and hand it over. You own it, not a subscription to someone else's middleware.
I used the same approach on a pipeline that turned two disconnected state licensing data sources into 263,982 verified contractor records, live in one week. That's the standard I hold every build to: connect the systems, then prove they stay in sync.
THE SIGNAL
When You Need a Custom Integration
No native connector exists
One or both systems aren't on any vendor's supported-integrations list. There's no app-store connector to install, because nobody built one for this pairing.
The vendor's connector drops fields
A native or Zapier-style connector exists, but it maps a fraction of the fields you actually need and silently ignores the rest.
One side is proprietary or legacy
An in-house system, an old database, or a platform with no public documentation. No-code tools assume a public REST API. This doesn't have one.
Volume breaks the no-code tools
Thousands of records, paginated endpoints, rate limits, and platform execution timeouts. Zapier-class tools are built for hundreds of records a day, not this.
THE PROCESS
How the Build Works
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Map the Data
I map every field on both sides before writing any code, and answer one question first: which system holds the source of truth for each field, and what happens when they disagree.
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Build the Connector
I choose API calls, webhooks, or scheduled polling, whichever the systems and the latency requirement call for. If an AI agent needs the same access, that's an MCP server, not a workaround bolted onto an app integration.
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Monitor for Silent Failures
An integration that fails loudly is a minor incident. One that fails silently is a data problem nobody notices until it's expensive. Monitoring gets built in before handoff, not added after the first outage.
RESULTS
Proof, Not Promises
6 custom MCP servers built where none existed
Standard connectors stop at GitHub, Slack, and Google Drive. Six custom servers connected AI models directly to project management, field service, and design QA systems that had no existing bridge.
See case study →263,982 records synced from two disconnected data sources
A pipeline normalizes California's scraped board records and Texas's bulk data files into one schema, on a monthly refresh cycle, with zero manual reconciliation.
See case study →4,510 pages synced in 74 minutes, zero timeouts
20 workflows connect a paginated, OAuth-gated deed data API to AI classification and a searchable frontend, self-batching around the platform's execution timeout.
See case study →INVESTMENT
How It's Priced
Every engagement is a fixed price, agreed with you before work starts and scoped on the free diagnostic call above. There's no hourly billing and no scope creep once I've locked the scope. A support window and full documentation come with every build, so the price covers the handoff, not just the code.
QUESTIONS
Common Questions About Custom Integrations
If your two systems have never talked to each other
30-minute diagnostic call to map the data, confirm the direction of truth, and scope what the connector actually requires.
Book a Diagnostic Call