Systems that actually talk to each other
Custom API integration connecting your website, CRM, and marketing tools into one working system instead of five disconnected ones.
Where this usually breaks down
Most "integration problems" are really just systems that were never actually connected. Someone exports a spreadsheet from one tool, reformats it, and imports it into another, on a schedule that depends on them remembering to do it. That manual step is where records go stale, fields get mistyped, and two systems that should agree on a customer's status quietly stop agreeing.
The gap usually isn't a missing feature - it's that nobody built the connector. Two SaaS tools can each have a perfectly good API and still have no data flowing between them, because building that link requires someone to map the fields, handle the edge cases, and decide what happens when a request fails.
What this service actually solves
API integration is the work of building that connector - reading data out of one system, transforming it into the shape the other system expects, and moving it automatically, in real time or on a schedule that actually matches how the business operates. Done properly, it also accounts for what happens when a request times out or a field is missing, instead of assuming every call succeeds.
API integration is the custom development work that connects two or more systems' APIs so data moves between them automatically, without someone manually exporting and re-entering it.
How we run it
We start by reading the actual API documentation for both systems before writing anything, because assumptions about what a field means or how a rate limit works are where integrations quietly break in production. From there we map fields explicitly, build the connector with error handling from the start rather than bolting it on afterward, and test against edge cases - missing fields, duplicate records, expired tokens - not just the clean data a demo environment provides.
Capabilities & deliverables
Custom Connector Development
- Point-to-point API integrations
- Authentication handling (OAuth, API keys, tokens)
- Rate-limit-aware request design
Data Mapping & Transformation
- Field-level mapping between systems
- Format and validation rules
- Handling for partial or malformed data
Webhooks & Real-Time Sync
- Webhook listener setup
- Event-driven sync instead of scheduled polling
- Retry logic for missed or failed events
Error Handling & Monitoring
- Failure alerts before data silently drops
- Logging for every sync attempt
- Dead-letter handling for repeated failures
Documentation & Handover
- Written mapping and logic documentation
- Handover for internal teams to maintain
What's in scope, area by area
| Area | What we deliver |
|---|---|
| Connector | A working, tested integration between the specified systems, deployed to production |
| Data Mapping | Documented field-level mapping and transformation logic |
| Monitoring | Error alerting so a failed sync gets flagged, not discovered weeks later |
| Documentation | A written reference so future maintenance doesn't require rediscovering how it works |
How an engagement runs
API Review
We read both systems' API documentation and test their actual behaviour, since documentation and reality don't always match.
Data Mapping
Every field that needs to move is mapped explicitly, including what happens when a value is missing or in the wrong format.
Connector Build
We build the integration with error handling and logging included from the start, not added after something breaks.
Webhook & Sync Setup
Where real-time sync matters, we set up webhooks rather than relying on scheduled polling that introduces delay.
Testing Against Edge Cases
We test with malformed data, expired tokens, and rate limits deliberately, not just the happy path.
Monitoring & Handover
The integration ships with monitoring in place and documentation so your team can maintain it going forward.
How this compares
| Custom API Integration | Manual Export and Re-Import |
|---|---|
| Data moves automatically and continuously | Data moves whenever someone remembers to do it |
| Failures are flagged and logged | Failures go unnoticed until someone spots a discrepancy |
| Field mapping is consistent every time | Manual re-entry introduces typos and mismatches |
A no-code tool like Zapier or Make often covers simpler cases fine - custom integration work tends to make sense once volume, complexity, or a missing native connector outgrows what those tools handle well.
What this changes for the business
- Data updates in one system without someone manually repeating the update in another
- Failed syncs get flagged immediately instead of being discovered when reports stop matching
- New tools can be connected into the existing stack instead of operating as an island
Who needs this
A tool with no pre-built connector
If the tool exposes an API but no native integration exists, custom connector work is usually the fastest real fix.
Teams that have outgrown Zapier or Make
Once sync volume or logic complexity increases, a no-code tool's cost and rigidity often stop making sense.
Related work
We're still building out published proof for this specific service — ask us directly and we'll walk through relevant examples.
Common questions
Not usually - most API integrations connect through each system's public API rather than touching underlying source code. Access needed is typically limited to API credentials and, for webhook setups, permission to configure an endpoint.
Most API providers version their APIs and give notice before breaking changes, which is what monitoring is for - we get an alert if calls start failing so it can be fixed before it causes a data gap.
Yes - rate limits are a design constraint we account for upfront, using batching, queuing, or webhook-based triggers instead of constant polling, depending on what the API supports.
It depends on the case. For simple, low-volume syncs, a no-code tool is often fine and cheaper to maintain. Custom integration work earns its cost once you need logic, volume, or error handling those tools weren't built to handle.
We use whatever the API supports properly - OAuth, API keys, or signed tokens - and credentials are stored securely rather than hardcoded, following the security practice each platform's own documentation recommends.
Got two systems that should talk but don't?
Tell us which tools are involved and we'll tell you honestly whether a custom connector makes sense or a simpler tool would do.
Talk to us →