Software, integrations and AI
Tool calling, write safety, evals and cost control on .NET and Azure
I integrate AI assistants with existing software. The server checks permissions and spending limits for tool calls. Evals in CI check for regressions when prompts, models or tools change.
LCP < 1.5s
Performance First
>99.95% SLA
Reliability
Multi-region
High Availability
What I work with
What I reach for, and what I have run in production.
Agents in Production
The gap between a working demo and a system you can leave running
An agent in production works on real data and spends money on every model call. I define which actions need approval, how to stop a run and how to check behaviour after a change.
Tool Calling
I connect tools to the domain services the product already uses, with the same validation and permissions.
Write Safety
I define what each tool may change and which actions need explicit approval before they run.
Evals
I run a fixed set of cases in CI on every prompt, model or tool change to catch regressions before deployment.
Cost Control
Token accounting per run and per tenant, with the caps and fallbacks that keep an agent loop from turning into an unbounded bill.
Platform and delivery experience
Financial data services and deployment pipelines
FinTech Platform Delivery
Built and evolved multi-tenant services processing high-frequency financial data, with delivery guarantees that hold through broker and consumer restarts.
CI/CD Delivery Modernization
Moved legacy delivery pipelines to GitOps workflows with repeatable deployments.