Service
Managed services
Running what has been built — applications, cloud platforms and AI systems — under an agreed scope and clear responsibilities.

Software becomes a liability the moment nobody is responsible for it. Managed services exist to make that responsibility explicit — what is monitored, who responds, how quickly, and what happens when something needs to change rather than merely be restored.
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AI systems add obligations conventional application support does not cover: evaluation suites have to be re-run, retrieval quality drifts as content changes, models are deprecated by their providers, and inference cost moves with usage. We treat those as first-class operational duties.
Support scope, hours and response commitments are agreed per engagement rather than published as fixed tiers.
What you get
- Explicit ownership and response commitments
- AI quality maintained rather than assumed
- Predictable operating cost
What's included
Application support and maintenance
Cloud and platform operations
DevOps as a service
Managed AI operations
Inference cost management
Continuous improvement
Where this applies
- A system live with no clear owner
- An AI deployment nobody is evaluating
- A small team unable to cover both change and support
- Rising cloud or inference costs with no attribution
Technologies
- AWS
- Azure
- Kubernetes
- Docker
- ServiceNow
- Python
Engagement models
- Support retainer. Agreed hours and response commitments for a defined scope.
- Managed AI. Ongoing evaluation, tuning, model migration and cost management.
- Platform operations. Cloud and pipeline operations under an agreed service scope.
- Transition and takeover. Structured takeover of a system built elsewhere, including documentation.
Related services
Ready to talk about Managed Services?
Tell us about the process or problem, and we'll tell you plainly whether this is the right starting point.
Or reach us directly at info@ontogenesistechnologies.com · +91-9999101853
