AIOps and MLOps engineering — the systems and practices that keep AI workloads running reliably in production. Monitoring, evaluation, retraining, incident response, and cost governance applied with the rigor production demands.
AI in production behaves like a distributed system, except the components are non-deterministic and degrade silently. Without proper operations, AI systems get progressively worse without anyone noticing — until a customer-impacting failure surfaces months of accumulated drift. We build the operational backbone that prevents that scenario.
Discuss your project ↗Every engagement gets shaped to fit, but these are the building blocks we rely on.
Latency, error rates, hallucination flags, content moderation alerts, and cost per request — observable in dashboards your on-call team trusts.
Automated test suites running against production traffic samples. Regressions surface before customers report them.
Scheduled and trigger-based retraining for ML models. Drift detection, dataset versioning, and rollback procedures all in place.
Runbooks for common AI failure modes — rate limits, hallucinations, prompt injections, data breaches. On-call playbooks tested in tabletop exercises.
Per-feature, per-team, per-customer cost attribution. Budget alerts, model routing, and quota enforcement to keep spending predictable.
Logging, data retention, access controls, and audit trails for regulated industries. AI operations that pass SOC 2, HIPAA, or PCI as required.
Two decades of engineering practice, sharpened by the realities of production AI.
Retries, circuit breakers, dead-letter queues, idempotency. The boring infrastructure patterns that prevent AI outages.
Hallucination rates, response quality scores, and user feedback aggregated into dashboards. Quality is debatable when measured.
AI bills don't surprise you. Per-feature attribution, monthly budgets, and routing rules enforced at the gateway.
Runbooks for the failure modes we've seen across dozens of production AI deployments. You inherit the playbook, not just the system.
Let's discuss how this fits your business. We reply within one working day.
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