Most API integration work goes wrong in the same three places: auth fails silently when tokens rotate, retries cascade into rate-limit shutouts, and there’s no visibility into what’s happening when things break in production. We build integrations where those three things are solved before you see them.
What this looks like in practice
We start by reading the upstream API’s docs as if our job depends on it (because it does), then design the integration around the real failure modes — not the happy path. Auth is baked into the bootstrap. Retries use exponential backoff with jitter. Rate limiting is enforced client-side, not just respected when the upstream pushes back. Logs go where you can read them.
For a concrete example: the CoachRogue overlay is a Riot API integration we built that handles account-switching mid-stream, polls live game state every few seconds without burning the rate budget, and writes overlays as static HTML files so an OBS Browser Source can read them without a hosted server. That’s the pattern.
Who this fits (and who it doesn’t)
Fits: small businesses with one specific integration to build (CRM ↔ accounting, marketplace ↔ inventory, internal API ↔ external partner). Research teams that need data movement infrastructure around an experiment. Teams whose existing integration breaks when usage scales.
Doesn’t fit: building a brand-new public API for someone else to consume — that’s its own engagement. Needing 50 integrations done in parallel — go bigger.
The first conversation
We need to see the upstream API docs and a sketch of what data needs to move where. From that we can give a fixed-scope estimate inside an hour.