Serving paths you can operate.
Cloud and DevOps for production AI — private serving and delivery designed for the platform team that stays after the pilot ends.
The business problem
Notebook-only models
No operable path
Cost and quality opaque
Serving placement matrix
Where inference should live — mapped against residency, control, and operational cost.
| Signal | Public endpoint | Private VPC | On-prem / air-gap |
|---|---|---|---|
| ResidencyWhere data may leave | Often unclear | Boundary-aware | Strict stay-local |
| Operational control | Vendor cadence | Your release loop | Full ownership |
| Cost visibility | Invoice surprises | Instrumented units | CapEx + ops load |
Memorable operations moment
One loop the platform team owns
Release, private serve, observe, and decide — ship, hold, or roll back — without heroics.
Gates before glory
CI, IaC, and checks are part of serving — not a side project.
Decide with signals
Latency, cost, and quality feed the next release — or the rollback.
Cloud architecture
Serving inside your boundary
Edge entry, private serve, and model runtime — wired to CI/CD and observability your team can run.
Residency by design
Inference lives where policy requires — not where a demo was fastest.
Release loops you trust
Deploy, observe, roll back — without heroics.
How we approach delivery
Map where inference must live, then build the loop
We design serving, release, and observability for the constraints you cannot negotiate away.
Operate before optimize
A serving path your team can run beats a clever architecture nobody trusts.
Cost visibility
Unit economics are instrumented — not guessed after the invoice.
Design a serving path
Share residency, scale, and who operates inference today.
How we deliver
Name the boundary
Residency, network, and who must operate inference after go-live.
Stand up the loop
Private serve, release gates, observability, and a rollback path.
Hand off ownership
Runbooks, IaC, and pairing so your platform team inherits the loop.
Why Choose Konic Labs for Cloud & DevOps
Private serving expertise
Pipelines platform teams inherit
AI-specific operations
Honest cloud choices
Related Case Study
Related Insights
Cloud & DevOps — FAQ
- Do you only work on AWS?
- AWS is our primary cloud for private serving paths. We work inside your boundary where possible — and say plainly when a requirement needs a different shape.
- Can you take over an existing deployment?
- Often, yes — starting with observability and release safety. We will be direct if a rewrite is cheaper than rescue.
- How does this connect to AI Automation?
- Automation and agents need a serving path someone operates. Cloud and DevOps is frequently the spine that makes specialization production-safe.
Design a serving path
Share residency, scale, and who operates inference today. We will map a delivery loop your platform team can own.