DevOps and engineering operations
We help teams ship and run software more reliably: CI/CD, environments, monitoring, logging, and production practices for LLM/AI solutions.
More reliable releases, clearer service operations, and a working setup for apps and LLM systems.
Capabilities
- CI/CD, Docker / Kubernetes
- Monitoring, logging, observability
- Platform engineering
- LLMOps, RAG, internal AI assistants
- LLM governance and security
Typical pains
- Releases and operations depend on manual engineering effort.
- Observability is insufficient for stable production support.
- LLM contour is launched without an explicit production process.
Deliverables
- Target delivery and operations contour.
- Baseline CI/CD and observability setup.
- Governance practices for LLM production lifecycle.
How we approach it
- We prioritize the highest operational bottlenecks first.
- Changes are staged across tooling and process layers.
- Support and ownership rules are formalized for operations.
What changes
- Manual release risk is reduced via repeatable delivery flow.
- Operational control improves through observability.
- LLM workflows are integrated into broader engineering operations.
FAQ
Where should we start: CI/CD or monitoring?
We start where operational risk is highest, then expand to adjacent parts of the contour.
Is this suitable for smaller engineering teams?
Yes. The scope can be adapted to team size and current process maturity.
Can we focus only on LLMOps?
Yes, though LLM reliability usually improves faster when aligned with core delivery operations.