Observability
- Unified telemetry layer
- Drift and cost dashboards
- One-hour Enterprise SLA
AI OPERATIONS & MANAGED SERVICES
MLOps, integrations, managed services, and multi-cloud optimization that keep AI accurate, compliant, and cost-efficient after launch.
Most agencies can launch an AI pilot. Far fewer can keep it working six months later.
The accuracy you validated in testing is not the accuracy you get in production once data shifts. The cost you budgeted in year one is not the cost you pay in year two once usage grows.
And the compliance posture you achieved at launch is not the posture regulators will expect next cycle. Operations is where AI programs live or die.
#1
Reason AI programs stall after launch: no operational model
40%+
Cost reduction achievable through inference optimization
1-Hour
Enterprise-tier SLA response time, 24/7
3
Managed service coverage tiers: Standard, Enhanced, Enterprise
AI Operations follows a four-phase journey drawn from our Managed Services practice:
Monitors AI systems for accuracy, latency, cost, drift, and fairness through unified observability and alerting.
Manages incidents, regressions, outages, and cost spikes through runbooks, change control, and root-cause resolution.
Improves performance and reduces cost through tuning, routing, batching, and quarterly optimization reviews.
Keeps AI aligned with changing regulations, platforms, and mission requirements through continuous upgrades and re-validation.
An always-on AI operations package that keeps your models accurate, compliant, and cost-efficient long after launch.
Launching AI is easy. Sustaining accuracy, compliance, and cost efficiency is what makes programs succeed long term.
Models naturally degrade over time, making continuous monitoring and retraining essential.
Right-sizing, routing, and tuning can significantly lower AI costs without reducing performance.
AI systems require SLAs, monitoring, and operational rigor just like production infrastructure.
Launching AI is easy. Sustaining accuracy, compliance, and cost efficiency is what makes programs succeed long term.
Models naturally degrade over time, making continuous monitoring and retraining essential.
Right-sizing, routing, and tuning can significantly lower AI costs without reducing performance.
AI systems require SLAs, monitoring, and operational rigor just like production infrastructure.
Let us run your AI so your team can stay focused on serving constituents, members, and communities.