Managed AI / Data / Platform
Provide an ongoing engineering and operating cadence for production AI, data, and platform capabilities after the initial implementation.
How do we keep the capability reliable, secure, observable, and improving after the first production release?
A production capability has no clear technical stewardship model.
Monitoring finds issues but there is no recurring improvement loop.
Release, security, data quality, and reliability work are managed separately.
The internal team needs operating leverage without generic staff augmentation.
What we deliver
Typical architecture path
Inspect a working reference before implementation.
Operational Intelligence Control Tower
A multi-site operations workspace for production, downtime, quality, energy, warehouse, fleet, exception ownership, and AI-assisted action planning.
View solutionAI Productionization & ModelOps
A ModelOps workspace for production deployments, model versions, evaluation gates, traffic allocation, drift, latency, errors, release actions, and governance evidence.
View solutionReliability & Resilience Command Center
A reliability workspace for service topology, incidents, SLOs, error budgets, RTO/RPO, dependency failure simulation, runbooks, and recovery evidence.
View solution