AI products
RX Software reviews the product around the model: its evidence, data boundaries, failure behaviour, operating cost and ability to earn user trust.
Production questions
AI quality is a product property, not a single model score. The useful questions cross technical behaviour, user consequences and operating reality.
A model response that looks plausible is not the same as a product outcome that can be measured. We help identify representative tasks, failure modes and acceptance criteria for the people using the product.
We trace what enters prompts, logs, storage and third-party services. The review looks for data leakage, weak account boundaries, excessive retention and assumptions about provider behaviour.
Models and providers can be slow, unavailable, rate-limited or unexpectedly different after an update. A production product needs timeouts, fallbacks, monitoring and a support path that users can understand.
Token usage is only one part of the cost. We consider retries, retrieval, storage, evaluation, monitoring, customer support and the engineering work needed to keep the system dependable.
The production test
Define intended behaviour, limits and the conditions that require human judgement.
Measure output quality, latency, cost and failure patterns with useful context.
Give users and operators a safe path when the model or provider behaves badly.