Agentic AI
The prototype works in a demo. No one knows how it behaves on real inputs, what it costs per month, or what stops it from taking the wrong action.
When to bring us in
- You have an AI prototype that needs to become a dependable service
- Repetitive internal work spans several tools and handoffs
- You can't measure whether an agent's answers are good
- LLM costs are unpredictable
- You need clear limits on what an agent is allowed to do
What we do
- Agents and LLM workflows connected to your internal tools and data
- Evaluation sets that measure quality before and after changes
- Guardrails: tool permissions, input handling, output validation, human approval steps
- Cost control: model choice, caching, limits and budgets
- Deployment, monitoring and logging for agents in production
How it runs
- inputInput
- guardGuardrails
- agentAgent
- toolsTools
- reviewReview
- monitorMonitor
What you get
- A working agent or workflow, deployed in your environment
- An evaluation set and the scripts to run it
- Documented guardrails and permission boundaries
- Cost and quality monitoring with alerts
Ways to engage
Assessment
A fixed-price review of what you run today. You get a written report and a prioritized plan.
Build
We implement the plan with your team, in your repositories and accounts, and hand it over documented.
Ongoing support
Optional, after handover: a retained block of engineering time for changes, upgrades and incidents.
Questions about Agentic AI
What happens to our data when an agent uses an LLM?
You decide before we build: which data an agent may see, which model providers and regions are acceptable, what gets logged, and what is never sent. Those limits live in code and in the docs.
How do you know an agent is working well?
By testing it. We build an evaluation set from real examples, run it before every change, and monitor quality and cost in production. Not a fit if you need guaranteed answers from a language model; no one can promise that.
Who owns the code and the accounts?
You do, from day one. Everything lives in your repositories and cloud accounts, under your access control. If we stopped tomorrow, nothing would stop running.
Tell us what you're running.
A few lines about your stack is enough. We'll reply to set up a short intro call, then send a written proposal with a fixed price.
