AI EaaS

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Questions Every Enterprise AI Team Must Answer Before Production

Manual reviews and subjective testing cannot catch every hallucination, regression, safety issue, or performance drop before release.

Are Your AI Responses Accurate and Grounded?

Evaluate accuracy, relevance, consistency, and grounding across real-world user scenarios before responses reach production.

Will Updates Break Existing AI Behavior?

Test how new models, prompts, data sources, and retrieval logic affect output quality before every release.

Can You Detect Risk Before It Reaches Users?

Identify hallucinations, unsafe responses, bias, prompt injection exposure, and compliance risks before deployment.

Can You Prove It's Ready?

Generate measurable quality scores, test evidence, and release-readiness reports that support confident production decisions.

Why AI Evals Matter

Traditional software testing validates whether an application behaves according to predefined rules. AI systems operate fundamentally differently.

Large Language Models and AI agents generate probabilistic outputs, reason across enterprise data, invoke tools, execute workflows, and continuously evolve through changing models, prompts, and knowledge sources.

Without rigorous evaluation, organizations face risks such as:

Hallucinated or inaccurate responses

Retrieval and grounding failures

Prompt injection vulnerabilities

Sensitive data exposure

Unsafe or non-compliant outputs

Tool misuse by AI agents

Production regressions after model updates

Erosion of customer and employee trust

AI Evals provide the evidence necessary to confidently answer a critical question:
"Can we trust this AI system in production?"

WHAT WE DO

Evaluate Every Layer of Your Production AI Stack

AI quality cannot be measured by a single score. WCT evaluates every layer of your AI ecosystem from responses, retrieval, prompts, models and agents to safety, and release readiness to give your teams a complete view of production AI performance.

Response Quality

Ensure AI responses are accurate, relevant, complete, and aligned with business expectations across real-world interactions.

Safety & Security

Detect hallucinations, bias, toxicity, prompt injection risks, sensitive data exposure, and policy violations before they impact users.

AI Agents

Assess tool usage, multi-step reasoning, workflow execution, and decision-making to ensure agents perform reliably in production.

RAG Systems

Verify retrieval quality, grounded responses, contextual relevance, and citation accuracy to improve trust in AI-generated answers.

Models & Prompts

Compare models, prompts, and configurations to identify the combinations that consistently deliver the best outcomes.

Release Readiness

Continuously validate AI before every release with automated testing, regression detection, and governance checks that support confident deployment.

OUR APPROACH

Our AI Assurance Framework

At WaferWire, we view AI evaluation as an ongoing engineering discipline rather than a one-time testing exercise.Our AI Assurance Framework creates a continuous quality flywheel that measures, validates, monitors, and improves AI systems throughout their lifecycle.

01 Assess

Define quality expectations and establish measurable baselines.

We evaluate existing AI applications, copilots, RAG solutions, and AI agents against business outcomes, operational requirements, and governance expectations.

Services include:

AI quality maturity assessment
Production readiness reviews
Risk identification and mitigation planning
Evaluation strategy design
Quality scorecard definition
Governance baseline creation

02 Validate

Build comprehensive evaluation assets and automated testing capabilities.

We develop golden datasets, synthetic test scenarios, domain-specific rubrics, ground-truth datasets, and regression suites that provide objective quality measurements.

Services include:

Golden dataset engineering
Synthetic enterprise data generation
Evaluation framework design
Assertion and rubric development
Safety and compliance testing
Model benchmarking

03 Operationalize

Embed AI Evals into the engineering lifecycle.

We implement continuous evaluation pipelines that validate every AI release before production deployment.

Services include:

Continuous AI testing
Regression detection
Prompt evaluation automation
RAG validation pipelines
Agent workflow testing
Release readiness gates
CI/CD integration

04 Govern

Establish enterprise-wide AI assurance programs.

We help organizations create centralized governance and monitoring practices that support long-term AI adoption at scale.

Services include:

Enterprise AI scorecards
Executive reporting
Compliance monitoring
Risk posture assessments
Human-in-the-loop validation
AI lifecycle governance

Engagement Models

Choose the engagement model that best aligns with your AI maturity, business priorities, and operational needs.

Evaluate

Operate

Scale

AI Eval Readiness Assessment

Identify quality risks, maturity gaps, and production readiness challenges.

Maturity assessment
Risk analysis
Quality scorecard
Evaluation roadmap
Governance recommendations

AI Eval Foundation

Establish evaluation frameworks, golden datasets, and automated testing for priority AI solutions.

Evaluation framework
Synthetic test datasets
Scoring model
Evaluation pipelines
Executive scorecards

Enterprise AI Assurance Program

Scale AI quality and governance across multiple AI applications, copilots, agents, and business units.

Enterprise AI governance model
Continuous evaluation platform
Release gate framework
Monitoring dashboards
Compliance reporting
AI assurance operating model

Not sure which model fits your AI maturity?

Book an AI Evals consultation.

Find the Right Engagement Model

Why WCT

Why Enterprises Choose WCT for AI Assurance

Organizations require more than AI testing. They need a trusted partner capable of operationalizing AI quality across engineering, governance, and production operations.

AI Engineering Expertise

Deep experience building and modernizing AI, data, and cloud solutions on Microsoft platforms.

AI Reliability Engineering

Focus on measurable quality, release readiness, continuous validation, and production monitoring.

Responsible AI & Governance

Embedding security, compliance, governance, and risk management into every stage of the AI lifecycle.

Microsoft Ecosystem Alignment

Experience with Copilot, Azure AI, Azure OpenAI, Microsoft Fabric, Azure Data Services, and enterprise-scale Microsoft deployments.

Enterprise Operationalization

Ability to move organizations from isolated AI pilots to scalable AI assurance programs supporting enterprise-wide adoption.

Outcomes That Matter

From Assumptions to Measurable Confidence

WCT helps teams replace subjective AI reviews with measurable quality evidence, risk visibility, and release-readiness insights so AI systems can be deployed, improved, and scaled with confidence.

Without Continuous AI Evals

Decisions rely on manual testing and subjective feedback.
Every release introduces uncertainty.
Problems are discovered after deployment.
AI readiness is based on assumptions rather than objective evidence

With WCT AI Assurance

Every release is validated against measurable quality standards.
Risks are identified before they impact users or business operations.
Performance is continuously monitored as AI evolves.
Changes are benchmarked to ensure every update moves AI forward.

Ready to Know if Your AI Is Production-Ready?

Get an expert-led assessment of your AI application, RAG system, copilot, or agent to identify quality gaps, safety risks, and release-readiness improvements before production.

The longer AI quality remains unmeasured, the harder it becomes to detect hallucinations, regressions, compliance gaps, and unsafe responses before they affect users.

Book Your Free AI Readiness Assessment

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WCT (WaferWire Cloud Technologies) partners with organizations to build AI-ready systems where human judgment thrives, technology serves people, and progress creates shared prosperity