02 · Offer
AI Agent Engineering
Agents, skills and integrations — built to run in production. We build the agent and everything it needs to work in your company: deterministic skills, MCP servers, integrations into ERP, CRM and documents, guardrails and an eval suite — on cloud models or fully private ones.
The problem
A demo agent takes an afternoon. An agent that touches your ERP, your customers or your documents needs a defined role, scoped tools, tested building blocks, a human approval step — and an answer to what happens when it is wrong. Most agent projects stall exactly there: between the impressive prototype and the first day in production.
What we deliver
- Agents with one clear role, scoped tools, hard limits and an escalation path to people
- Skills: small, deterministic, tested and versioned building blocks for look-ups, validations and postings
- MCP servers and APIs that give agents controlled access to your systems — exactly the functions they may use
- Integrations into ERP, CRM, document stores and mail — and plain workflow automation where no agent is needed
- An eval suite with real cases, prompt-injection and tool tests, run before every release
- Your choice of models: cloud models, private models in your infrastructure, or a mix with routing between them
- Documentation and handover: architecture, runbooks and the human approval steps
How it runs
Audit → Build → Retainer: the same line for every offer, tailored to this one. You decide after each phase whether to continue.
- 01
Audit
A short scoping audit for the chosen process: inputs, decisions, systems, approvals and the cases we will test against. Skipped if the readiness audit already covered it.
- 02
Build
One agent at a time into production: skills, integrations, guardrails and evals, released through quality gates with your team in the loop.
- 03
Retainer
New skills, model updates, cost control and monitoring on a release cadence — the agent evolves with the process instead of being hot-fixed.
Matching industries
Where this offer meets ground we know from the inside.
Questions
Which models do you build on?
On whatever fits the data and the task: strong cloud models, open models running in your own infrastructure, or a mix where routine work stays local and harder cases escalate. Every model is tested against the agent’s eval suite before it goes live.
What is an MCP server — and do we need one?
The Model Context Protocol is an open standard for giving agents controlled access to tools and data. An MCP server exposes exactly the functions an agent may use, nothing more. We use it where it simplifies access control and reuse; it is not an end in itself.
Can the agent act on its own?
Only within the limits you set. Every action that changes data or reaches people outside your company can wait for a human approval step. Which actions run alone and which need sign-off is defined up front — and tested.
Do you also build plain automations?
Yes. Where a deterministic workflow does the job, we build that instead — cheaper to run and easier to audit. Not every use case needs an agent.
Talk it through in 30 minutes.
Bring one process and your stack. We come prepared and tell you honestly whether an agent pays off — and which offer is the right start.
Or write to us: office@novaeon.studio