Index / AI Evaluation and Testing

AI Evaluation and Testing

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Index

Testing is how we give an attractive possibility something more demanding to answer to.

Find out what the experience can actually support

A successful demonstration answers a narrow question: the system produced that result under those conditions. A useful evaluation asks what happens across the tasks and circumstances people will bring to it.

We evaluate AI-enabled experiences against their intended purpose. The work examines usefulness, factual support, permissions, review effort and recovery, with the methods chosen for the situation.

You can engage us for a focused review or as part of designing, implementing and improving an AI product.

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Agree what good means for the task

What should someone be able to accomplish? Which facts or actions must be correct? What would make an output unusable even if it sounds polished?

We develop criteria with the people who understand the work. A content editor, support team and product owner may notice different kinds of failure. Their knowledge helps create an evaluation that reflects the task rather than only a convenient automated score.

AI Product Experiences connects this inquiry with the interaction. Software Testing and Quality Assurance continues to address the wider application's behavior.

Testing is how we give an attractive possibility something more demanding to answer to.

Include the cases that challenge the idea

Ordinary tasks matter. So do missing information, ambiguous requests, conflicting sources, restricted records and actions outside the system's authority.

We select cases that can reveal important weaknesses and distinguish observed results from broader conclusions. No finite test set establishes that every future response will be correct.

Human review and automated checks can contribute differently. We choose them around what is being judged, record the conditions and make the method understandable enough to repeat or challenge.

Examine a product answer together

When we evaluate assistance for a configurable product, we work with your team to identify the information governing valid combinations.

An answer about whether a ring setting accepts a particular stone must be examined against that information. We consider supported combinations, unsupported ones and requests that omit something necessary to decide.

Does the experience seek clarification? Does the explanation match the source? Can the person understand the limitation and continue usefully? A confident sentence with an attractive reference is not enough.

Product Configurator Development and Product Information Management help keep valid relationships and product facts distinct from generated explanation.

Evaluate the complete interaction

An answer can be technically acceptable and still impose too much checking work. We examine task completion, review burden, response time, cost and the person's ability to correct or reject a result.

For systems allowed to act, evaluation also examines permissions, confirmations and what happens when an operation fails or is retried. Responsible AI Implementation establishes those controls; testing provides evidence about their behavior.

Security testing, regulated-use assurance or specialist assessments require the appropriate scope and expertise. We keep them visible rather than imply that a general evaluation certifies the whole system.

Make change testable

Prompts, models, source content, retrieval behavior and application code can all change an experience. We define a repeatable basis for comparing versions where useful, including which conditions must stay consistent.

Test Automation can support recurring checks. Human evaluation remains necessary where the question concerns meaning, judgment or an experience that the automated checks do not adequately represent.

The report should explain what was tested, what was observed, what remains uncertain and what we recommend next. A finding is useful when it can inform a decision.

Our process follows Discover → Define → Explore → Design / Develop / Market → Learn → Advance → Discover. Evaluation begins before release and remains connected to learning during use.

Bring us the system, the proposed change or the concern you want to understand. We will help turn it into questions that can be investigated and acted upon.

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Start a conversation.

Tell us what you’re working toward and where you could use help. We’ll reply by email.

Tell us a little about yourself or your organization, what you’re trying to accomplish and what’s getting in the way.