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Services · AI Platforms
AI Platforms
We design, ship, and run AI products end-to-end — chat-native interfaces, retrieval pipelines, evaluation harnesses, and the boring infrastructure that keeps them on.
i
The problem
What we keep seeing.
Most AI products fail not on model quality but on the surrounding system: retrieval, evaluation, cost, latency, and the user interface that makes it trustworthy.
ii
Our approach
How we engage.
- 01
Architecture review covering retrieval, model routing, observability, and unit economics.
- 02
Iterative prototypes against your real data, with golden sets and automatic regression tests.
- 03
Production hardening: rate limits, prompt isolation, audit trails, and SOC-friendly logging.
- 04
Hand-over with runbooks, eval harness, and a 90-day operate-and-improve plan.
iii
Stack
Tools we reach for first.
We are pragmatic — these are defaults, not religion. We choose for the project, not the portfolio.
iv
Outcomes
What you walk away with.
01
Deployable in weeks, not quarters.
02
Measured quality, not vibes.
03
Predictable per-request cost at scale.
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Adjacent disciplines