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Voxd

AI Answer Quality & Reliability Testing

Find the weak answers before your customers do.

Evaluate AI answers against representative tasks and agreed quality criteria.

The opportunity

The problem we help you solve

An agent can sound confident and still miss the point, rely on the wrong source or fail when a question is phrased differently. A handful of successful demonstrations does not reveal those patterns.

Voxd builds evaluations around the tasks and questions that matter to your service. We include incomplete, difficult and out-of-scope cases, then assess the responses against agreed criteria. You receive a clearer picture of what the system does well, where it fails and which improvements deserve attention first.

What changes for your team

Replace impressions with evidence

Evaluate representative questions consistently instead of relying on a few memorable successes or failures.

Understand recurring failure modes

Distinguish missing knowledge, retrieval problems and response behaviour so fixes address the right layer.

Make change easier to judge

Use the evaluation set as a baseline for reviewing future updates to information, instructions or models.

What we deliver

What Voxd can deliver

01

Evaluation-set design

Collect representative tasks, difficult cases and the expectations for an acceptable answer.

02

Quality assessment

Check factual support, relevance and failure handling against the agreed scope.

03

Prioritised findings

Document patterns and recommendations with examples your team can inspect.

Why Voxd

We understand the implementation behind the policy.

Voxd’s delivery work includes human approval in iGlobal’s proposal workflow, consent-led introductions in GBM’s concierge and role-aware guidance within the Waitrose supplier portal. These are concrete examples of oversight designed into a user journey.

We bring that engineering perspective to governance engagements, helping your responsible teams connect policy to system behaviour. We can support their assessment and evidence gathering while leaving legal interpretation and formal sign-off with the appropriate advisers and accountable owners.

How we work

From a policy document to working controls

  1. 01

    Understand the exposure

    We identify the tools, systems and proposed uses in scope, who is affected and which internal requirements apply.

  2. 02

    Agree the framework

    We work with the relevant owners to define responsibilities, review thresholds and practical guidance matched to the use cases.

  3. 03

    Put controls into practice

    We help translate requirements into workflows, access rules, approval steps and evaluation processes that teams can operate.

  4. 04

    Review and adapt

    We establish review points for changes in the system, supplier or business use, with a route for recording and addressing issues.

Before you get started

Before you get started

Can you test an agent built by another supplier?

Yes, subject to suitable access and an agreed scope. We establish what can be evaluated independently and what needs additional system information.

Will passing the evaluation guarantee every answer?

No. An evaluation measures performance on the selected cases. It provides useful evidence and regression checks, with limits determined by its coverage.

Put your agent’s answers to a more realistic test.

Bring the questions it must handle well and the failures you already suspect.

Discuss your AI project