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Nexoqoby nexoqoai.tech

AI QualityOps infrastructure for teams building agents, LLM applications, RAG systems, and autonomous workflows.

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© 2026 nexoqoai.tech. Nexoqo is the AI QualityOps platform.

Make production AI measurable, testable, and dependable.

Customer Support solution

Evaluate support agents across the complete customer workflow.

Test whether a support agent understands customer intent, retrieves the right information, follows company policy, and completes or escalates the task appropriately.

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Scenario design · Workflow evaluation · Regression analysis

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Evaluation coverage

Test the decisions behind every support outcome.

Build realistic scenarios around expected behavior, edge cases, required actions, and the criteria that determine whether the workflow succeeded.

01

Intent understanding

Include this behavior in repeatable test scenarios and evaluate it against criteria defined for the workflow.

02

Account and help-center retrieval

Include this behavior in repeatable test scenarios and evaluate it against criteria defined for the workflow.

03

Policy compliance

Include this behavior in repeatable test scenarios and evaluate it against criteria defined for the workflow.

04

Action selection

Include this behavior in repeatable test scenarios and evaluate it against criteria defined for the workflow.

05

Escalation behavior

Include this behavior in repeatable test scenarios and evaluate it against criteria defined for the workflow.

06

Unsupported claims

Include this behavior in repeatable test scenarios and evaluate it against criteria defined for the workflow.

Who it serves

Quality signals for the teams responsible for support AI.

Bring the people building, validating, and operating the AI system into one measurable quality process.

  • AI engineers
  • Software engineers
  • Product managers
  • QA and quality engineers
Quality outcome measurable
Define expected behaviorAlign scenarios with the workflow and its users.
Evaluate the complete pathMeasure actions and intermediate steps, not only final text.
Compare against a baselineReview quality signals before and after each change.

Conceptual QualityOps workflow; no customer performance data is shown.

Measure whether the agent reaches the intended result while following policy and using the approved workflow.

Related capabilities

Build the supporting quality workflow in Nexoqo.

Connect this solution to the evaluation capabilities that measure agent behavior across development and production.

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AI Agent Testing

Test autonomous and semi-autonomous agents against realistic task scenarios, evaluating both the final result and the sequence of actions used to reach it.

Task understandingInstruction followingTool selection

RAG Evaluation

Measure Retrieval-Augmented Generation systems across both the quality of retrieved context and the quality of the generated answer.

Context relevanceRetrieval precisionRetrieval recall

Production Monitoring

Evaluate real production conversations and agent traces to surface low-quality interactions, repeated failures, unusual behavior, and quality degradation.

Production trace scoringLow-quality interactionsFailure patterns

Release Quality Gates

Establish minimum quality thresholds that help teams determine whether an AI release is ready for production.

Pass rateWeighted evaluation scoreSafety thresholds
Customer Support AI quality

Define the evaluation criteria your workflow needs.

Discuss how Nexoqo can structure scenarios, quality signals, and release checks around your AI system.

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