Same outcome, different evidence
Business success is defined by you, not the platform. But each cloud, platform and framework exposes different traces, tools and evaluation features, which shape how evidence is collected.
SERVICES
Independent evaluation services for agents built on major clouds, enterprise software, data platforms, model providers, open-source frameworks and evaluation platforms. We scope testing around your agent's behavior and business outcomes, whatever the stack.
Business success is defined by you, not the platform. But each cloud, platform and framework exposes different traces, tools and evaluation features, which shape how evidence is collected.
Cloud and platform evaluators are useful, but they need your scenarios, rubrics and expert calibration before their scores support a decision.
McKinsey describes a gap between broad generative AI adoption and limited bottom-line impact, and sees agents embedded in workflows as a way through. Those agents need workflow-level testing.
Evaluation for agents built with Amazon Bedrock AgentCore and Bedrock Agents Classic, including tools, knowledge bases and multi-agent setups.
Explore serviceEvaluation for agents built on Microsoft Foundry, Azure OpenAI and Copilot Studio, using native evaluators alongside your own checks.
Explore serviceEvaluation for Gemini-based agents built with Gemini Enterprise Agent Platform and the Agent Development Kit, including trajectory and final-response assessment.
Explore serviceEvaluation for Agentforce agents: subagent routing, actions, CRM record updates and grounded answers, tested in your sandbox.
Explore serviceEvaluation for agents and agentic workflows built in AI Agent Studio, including task completeness and tool use.
Explore serviceEvaluation for Joule agents: skill selection, business-rule accuracy and grounded answers in your SAP processes.
Explore serviceEvaluation for agents built with Agent Bricks and MLflow, with LLM judges calibrated to your subject-matter experts.
Explore serviceEvaluation for Cortex Agents: tool selection, text-to-SQL accuracy, search grounding and answer correctness.
Explore serviceApplication-specific evaluation and model-migration comparisons for agents built with Claude.
Explore serviceApplication-specific evaluation and model-migration comparisons for agents built with OpenAI models, the Responses API and the Agents SDK.
Explore serviceAgent and prompt test suites with the open-source Promptfoo CLI: assertions, side-by-side comparisons and CI gates.
Explore serviceTest-style agent evaluations with the open-source DeepEval framework: task completion, tool correctness and grounding metrics.
Explore serviceRetrieval and agent evaluations with the open-source Ragas library, from faithfulness to tool call accuracy.
Explore serviceSelf-hosted datasets, experiments, LLM-as-a-judge and code evaluators, and human annotation with open-source Langfuse.
Explore serviceDatasets, trajectory and final-response evaluators, judges aligned with your experts and experiments that compare every change in LangSmith.
Explore serviceGrounding and hallucination evaluations calibrated to your domain, using Patronus AI evaluators where they fit.
Explore serviceFunctional quality testing for knowledge assistants and agents: contradictions, omissions, inappropriate refusals and business-rule failures.
Explore serviceDatasets, scorers and experiments organized so that every change is compared against a reviewed baseline.
Explore serviceApplication-specific metrics and regression tests with Confident AI and the open-source DeepEval framework.
Explore serviceOffline evaluation experiments and judge calibration with Arize AX and Arize Phoenix.
Explore serviceAssertion-based tests and side-by-side prompt and model comparisons wired into your development workflow.
Explore serviceWe write success criteria in business terms first, then translate them into checks that fit your platform's interfaces.
We work only within the environments, data and permissions you approve, and confirm current product features during discovery.
The same evaluation method, evidence standards and deliverables apply whichever cloud, platform or framework your agents run on.
Start with one workflow, clear success criteria, and an evaluation plan your team can use.