Reliability engineering meets innovative AI
Production reliability and applied AI, integrated in the same operating model.
A.M. Tech Consulting integrates site reliability engineering and applied AI in that model — so production is observable, delivery is repeatable, and AI runs as production software with an owner.
Start with the operating problem
Match the failure in the business to the engagement.
| If this is happening | Operational impact | Engage |
|---|---|---|
| Incidents, unclear health, releases you cannot trust | Lost availability, reactive operations, weak SLOs | Reliability operations → |
| Architecture that cannot support the next stage of the business | Slow change, technical debt, stalled modernization | Systems architecture → |
| Manual delivery, inconsistent deploys, long cycle time | Missed commitments, engineering time spent on toil | Delivery operations → |
| AI interest with no production path | Demos that never enter the operating model | Applied AI & development → |
Engagement model
How the work runs
Current operating constraints, systems in play, and what “in production” has to mean.
Technical and operational baseline: architecture, reliability, delivery, AI readiness.
The system is implemented against that baseline — software, pipelines, observability, applied AI.
Runbooks, metrics, and ownership so operations can carry it without a standing dependency.
Proof of thinking
Reliability
Author of SLIs and SLOs Demystified (Packt, 2025). Prior work in large-scale incident operations and production platforms.
Software
Hands-on engineering across services, cloud, and native applications — design through delivery, not advisory-only.
Applied AI
Applied AI is core to the practice. It belongs in the operating workflow, with evaluation and a fallback when the model is wrong or down.