Enterprise AI / LLMOps

Govern AI before
it governs your risk

Mativyx builds the operating layer for production AI: evaluations, prompt and model versioning, observability, guardrails, red-team testing, release gates, compliance reporting, and incident response.

Operational Controls

Production AI needs software engineering discipline

✅

Model Evaluation

Golden datasets, scenario tests, adversarial prompts, factuality checks, business-rule validation, and human review workflows.

📝

Prompt Management

Version prompts, tools, retrieval configuration, system instructions, and model parameters with release history.

🔍

AI Observability

Trace prompts, model calls, retrieved context, tool actions, cost, latency, quality scores, failures, and feedback.

🛡

Guardrails

Safety filters, data-loss controls, role-based policies, refusal behavior, structured output validation, and tool-use restrictions.

🔬

Red-Team Testing

Test for prompt injection, sensitive data leakage, hallucination, unsafe tool use, policy bypass, and workflow abuse.

📋

Governance Reporting

Dashboards and review packs for AI usage, quality, incidents, risk classification, approvals, and control effectiveness.

Operating Model

A lifecycle for every AI capability

  • Intake: classify use cases by business impact, data sensitivity, user exposure, and automation risk.
  • Build: create prompts, retrieval, tools, model routes, evaluation data, and release criteria.
  • Release: approve only when quality, safety, latency, cost, and governance checks pass.
  • Operate: monitor drift, incidents, user feedback, model changes, and business outcomes.

Who needs this

  • Teams moving from AI pilots to production
  • Regulated enterprises with compliance needs
  • Organizations using multiple LLM providers
  • AI systems that trigger workflow actions
  • High-volume AI products with cost pressure

Move AI from pilot risk to production control.

We can audit your current AI pipeline and implement evaluation, observability, and governance controls.

Audit AI Governance