Measure how often your production AI is wrong, makes things up and what it costs. Evals built from real cases, guardrails and model cascades, with monitoring.
Your company put AI into production, but nobody knows how often it's wrong, makes up an answer or a number, or what each task costs. According to IBM, only 25% of AI initiatives delivered the expected return.
We build a test set from your real cases; measure hallucinations, unsupported numbers and answers without citations; add guardrails and deterministic checks where errors are expensive; and tune the model cascade for cost. Everything becomes an automated suite that runs on every change, with a monitoring dashboard.
We collect real inputs and expected answers from one AI workflow.
We measure errors, hallucinations, unsupported numbers and cost per task.
Guardrails, deterministic checks and model cascades go where they matter most.
The suite runs on every change, and a dashboard tracks quality and cost.
Errors measured, not guessed. An accuracy and hallucination rate you can track over time.
Lower cost per task. Cheaper models where they're good enough, expensive ones only when needed.
Safe changes. Every prompt or model change runs against the suite before it reaches production.
What we measure
Metrics are agreed before we start. With the numbers in hand, you decide whether to move to production.
Pricing
From US$ 5,000 per workflow (estimate); custom quote after a free assessment
Billing: fixed price or a share of measured savings, with a cap.
Every project is quoted in writing after a free assessment, in US dollars or euros.
Entry offer
from US$ 5,000
Timeline: 2 to 3 weeks
Starting price for the scope described. Larger volumes and extra integrations go into the proposal, always in writing before work starts.
Industries where this service comes up most:
Every project is quoted after a free assessment, based on scope, volume and the systems involved. To start with a fixed scope, the “Reliability and cost evaluation of one AI workflow” offer starts at US$ 5,000 and takes 2 to 3 weeks. You get a fixed-price proposal in writing before any work starts.
The pilot takes 2 to 3 weeks. Typical scope: one AI workflow in production.
With real cases from your workflow and expected answers: every response is checked against the source, and any number without a source counts as an error. The result becomes a suite that runs on every change.
Yes, as an option: 15 to 25% of the measured savings, with an agreed cap and a single owner on your side. The default is a fixed price.
Who builds it
AI engineer · Joinville, Brazil
Five years of software development and AI systems in production. The person who handles your project is the one who designs it and writes the code.
Free assessment
Tell us how the process works today, the rough volume and the systems involved. If it makes sense, you'll get a pilot proposal with scope, timeline and metrics.
Tell us about the process, the rough volume and the systems involved. You'll hear back from the engineer who would build it.
Lower AI spend without losing quality: model cascades, caching, local models and per-task measurement.
From “we want to use AI” to a measured pilot in production, with security and privacy built in.
LLMs running on your own servers, tuned to your vocabulary, with no sensitive data leaving the building.