No fallback—model outage stops business—teams then argue across ownership lines.
AI API Integration
Wiring AI is easy; controlling cost and degrading gracefully is hard.
Wire inference/embedding/speech APIs into flows—with limits and cost control.
Integration pains
These usually show up before a project starts—or right after a rushed launch.
Duplicate calls burn budget—it often surfaces only after production impact.
Sensitive data leaves without redaction—iteration and local integration slow down.
No eval set for quality—users feel it as inconsistent data or UX.
Degradable intelligence layer
Unified client; cache idempotent calls; timeout/circuit break; rule-based fallback; small eval set. Prompt/param strategy, timeouts/retries, cache and usage monitors. Privacy: what may leave your boundary is written down.
Prompt/param strategy, timeouts/retries, cache and usage monitors. Privacy: what may leave your boundary is written down.
- Scope written before coding
- Milestones you can accept
- Handover notes included
Highlights
What this engagement typically covers.
API adapter
Included in scope after we confirm stack, constraints and acceptance checks.
Timeout/retry
Included in scope after we confirm stack, constraints and acceptance checks.
Usage/cost monitors
Included in scope after we confirm stack, constraints and acceptance checks.
Privacy boundary
Included in scope after we confirm stack, constraints and acceptance checks.
What you get
- Integration module
- Config/secret notes
- Usage monitors
- Fallback strategy
- Eval notes
How we work
-
01
Scenario & privacy, with written stage outputs.
-
02
Vendor choice, with written stage outputs.
-
03
Integrate, with written stage outputs.
-
04
Trial observe, with written stage outputs.
Ready to lock scope?
Say text/image/speech needs and data-boundary rules—we'll propose.