OteroQA
Servicio · AI & LLMs

QA for AI & LLM evaluation

AI systems aren't tested like regular software: they can hallucinate, bias or answer the same question differently. We evaluate your chatbots, agents and LLM features against batteries of real cases (accuracy, hallucinations, bias and consistency), with metrics, not intuition.

01 / The service

What is AI QA and LLM evaluation?

AI QA is the discipline of testing systems that use language models (chatbots, assistants, agents and LLM features) whose behavior is not deterministic. Unlike classic software, the same input can produce different, made-up or biased answers. We measure how reliable your AI is against real cases, with objective criteria and scores.

We design evaluation batteries (evals) that put your model through representative and adversarial prompts, and score each response for accuracy, hallucination, bias, tone, safety and consistency. We combine automated verification with expert human review and deliver where and how much your AI fails, with examples.

02 / Why it matters

An AI that sounds convincing is not the same as a correct AI

LLMs generate plausible text even when it's false: they hallucinate data, leak information, answer the same question differently and carry biases. In production that's reputational, legal and trust risk. Evaluating your AI with real cases and metrics, before and after each model or prompt change, is the only way to know if it improves or worsens.

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evaluation cases per battery
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responses scored per criterion
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report with failures and examples
03 / Benefits

What you gain by evaluating your AI methodically

Before

Without AI evaluation

Hallucinations that reach the user
You don't know if a change improves or worsens
Biases and inconsistent answers
Legal and reputational risk
With OteroQA4/4

What you gain by evaluating your AI

Hallucinations under control

We detect and measure when your model makes things up, so it doesn't reach production as if it were true.

Every change, measured

We compare model and prompt versions with the same battery: you know if each change raises or lowers quality.

Consistent and fair answers

We evaluate bias, tone and consistency so your AI answers everyone equally well.

Confidence to launch

We give you objective quality and safety metrics to ship your AI without crossing your fingers.

04 / How we work

Our process, step by step

oteroqa · eval battery
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01

Defining criteria and cases

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We agree what your AI should do and build a battery of real and adversarial cases with the expected answer.

02

Designing the eval battery

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We prepare the evaluations and scoring rubrics: accuracy, hallucination, bias, tone, safety and consistency.

03

Execution and scoring

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We run your model through the cases and score each response combining automated verification and human review.

04

Hallucination and bias analysis

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We identify failure patterns (what it hallucinates, where it biases, when it contradicts itself) and measure their frequency and impact.

05

Report and continuous evaluation

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We deliver the metrics with examples and leave the battery ready to re-evaluate on every model or prompt change.

running pipeline…running
05 / Why choose us

We understand how models fail, not just how to use them

We're an ISTQB®-certified team that evaluates AI systems methodically: reproducible batteries, clear rubrics and human review. We know where LLMs hallucinate and bias, we build evals you can re-run in your CI and explain every result in your language, with the exact case and response.

ISTQB® certifiedLLM · RAG · agentsReproducible evalsES / EN support
06 / What's included

What the service includes

Custom evaluation batteries (evals)
Hallucination detection and measurement
Bias, tone, safety and toxicity
Consistency and non-determinism
Model and prompt comparison
Continuous evaluation in CI/CD
Let's start

Request an evaluation of your AI system

Tell us what AI you have (chatbot, agent or LLM feature) and what worries you. We reply in under 24h, in Spanish or English, with a tailored proposal.