Spec-driven integration: how AI turns voice memos into production iPaaS code
A look at the pipeline that takes a two-minute voice memo and turns it into a deployed, monitored integration in days, not months.
The traditional integration project starts with a discovery call, a requirements doc nobody reads, and a statement of work measured in months. We compressed that into a pipeline that starts with a single artifact: your spec.
Step 1 — Capture
You describe the outcome in plain language: the source system, the destination, the frequency, the shape of the data, and what “done” looks like. Voice or form — whichever is faster for you. We transcribe and structure it into a machine-readable spec.
Step 2 — Confirm
A senior architect reviews the spec with AI assistance, fills the gaps, and sends it back to you in one page of plain English. You approve the scope before a line of code is written. No misread requirements doc, no scope drift.
Step 3 — Build
This is where AI changes the economics. The confirmed spec drives code generation, connector configuration, and test scaffolding. The architect reviews, hardens, and handles the edge cases AI gets wrong. A typical build that an industry team quotes at 8–12 weeks ships in 1–3.
Step 4 — Run
We deploy into isolated, per-tenant runtime in our cloud and wire up dashboards automatically: runs, errors, latency, throughput, and a live cost projection. You watch it work. We operate it.
The spec is the contract, the source of truth, and the thing AI accelerates. That is why we call it spec-driven integration.