AI governance and security: operating models as production software

An AI prototype that works in a demo and a reliable AI system in production are very different things. What separates them has a name: LLMOps.

Just as software needs DevOps, AI systems need a discipline to measure, control spend and protect. Without it, AI becomes unpredictable and expensive.

Observability: knowing what happens

Traces of every request, logging of responses and quality metrics in production. You can't improve —or trust— what you don't measure.

Cost and security under control

Cost per request spikes if no one watches it. And security includes protecting against data leaks and attacks like prompt injection.

The pillars of LLMOps

• Continuous evaluation and regression detection
• Monitoring of cost, latency and errors
• Defense against prompt injection
• Traceability and compliance (GDPR)

At AxisOne we help operate AI with guarantees: observability, AI FinOps and security. If you already have AI in production and want it reliable and predictable, we'll support you.