Enterprise AI / LLMOps

Govern AI systems before
they reach production

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 from pilot activity to production control.

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

Audit AI Governance