Models update
Providers release new versions and retire old ones. A model change can shift tool use, tone and accuracy in ways a quick check won't reveal.
RECURRING SERVICE
Keep testing as your agents change.
Scheduled evaluations and expert analysis for teams that need a consistent quality process without building a full evaluation function in-house.
Agents don't stay still
Your business changes
Prices, policies, products and approval rules change. An agent that was right last quarter can be confidently wrong today.
Small edits add up
Prompt tweaks, new tools and knowledge updates accumulate. Without a fixed benchmark, gradual drift goes unnoticed.
A recurring evaluation cycle
Regression testing
Run an agreed suite on a schedule or before selected releases. Compare against a recorded baseline and flag meaningful changes by workflow.
Approved production sampling
Evaluate selected, approved interaction samples in batches. Include random and targeted samples; report selection bias and never treat sampled scores as all-user performance.
Emerging failure analysis
Group new failures, validate them with reviewers and promote representative cases into the regression dataset so they stay fixed.
Model and version comparisons
When a provider releases a new model or you plan a change, run a side-by-side comparison on the same reviewed cases before switching.
Business-rule refresh
When policies change, we update expected outcomes and rubrics so the benchmark keeps reflecting how your business actually works.
Judge recalibration
Periodically recheck AI judges against fresh expert labels, so automated scores stay trustworthy as the agent and data evolve.
Monthly quality report
What changed
Tested versions, dataset changes, coverage and results. Gains and regressions explained with supporting examples.
What matters
Findings prioritized by business impact, recurrence and affected workflows. Critical failures separated from noisy score movements.
What to do next
Recommended fixes, owners, retest scope and evaluation backlog updates, reviewed together in a scheduled working session.
Agree the service boundaries
Cadence and capacity
Agents covered, run frequency, dataset size, reviewer capacity, reporting rhythm and the change-request process, agreed in writing.
Customer responsibilities
Maintain test access, flag business-rule changes, provide approved samples and assign an owner for decisions and remediation.
Reports on a set rhythm
Each cycle ends with a quality report covering what changed, what matters and what to do next, followed by a working session with your team.
Why teams choose managed
Evaluation expertise without the hire
Calibrating judges, curating datasets and reading noisy results is specialist work. We provide it at the cadence you need.
A benchmark that grows
Each cycle adds confirmed failures and new scenarios, so the test suite gets more valuable over time.
Consistent records
Every run records configuration, dataset version and evaluator version, giving you a traceable quality history.
Make your next decision with evidence.
Start with one workflow, clear success criteria, and an evaluation plan your team can use.