An operating model aligned with data, IP and risk
NyxAI · Agent Pilot
AI agents that work inside the business.
A controlled pilot for one concrete business workflow — local, private or hybrid. With data protection, explicit roles, human approval and measurable outcomes.
Typical pilot scope: €20,000–40,000 excluding VAT · 4–6 weeks · one defined workflow
CONTROLLED AGENT LOOP
The agent works within defined tools and boundaries. People retain authority.
Approvals, fallbacks and traceable handoffs
Test cases, quality criteria and audit trails
A bounded scope instead of an uncontrolled platform bet
Why now
Delegate routine work. Retain responsibility.
Repeated searching, data entry and checking take time. A defined pilot shows which tasks an agent can handle — and where your team’s expertise or approval remains necessary.
AI literacy
Teams need practical rules and experience to operate AI systems safely.
Privacy & IP
Sensitive process logic and organizational knowledge should not flow uncontrolled into external model loops.
Measurable value
A pilot must be measured in time, quality, risk or throughput — not in a demo.
The pilot program
From one workflow to a defensible agent.
NyxAI combines agent engineering with sovereign deployment, evaluation and decision intelligence. The pilot ends with a usable prototype, evidence from realistic tests and an informed decision about the next step.
01
Workflow & target state
Define the process, roles, success criteria and human-in-the-loop.
02
Secure agent architecture
Connect models, data sources and tools with least-privilege access.
03
Prototype & evaluation
Test one agent on a representative dataset and improve it deliberately.
04
Handover & roadmap
Operating options, a practical AI literacy session and a recommendation for further testing or deployment.
Fast-to-validate use cases
Where a focused pilot creates evidence quickly.
Knowledge & document agent
Make policies, technical documentation and project knowledge searchable — with sources and permissions.
Service & case agent
Triage inboxes, tickets or cases, create summaries and prepare work for approval.
Planning & analysis agent
Connect signals, prepare scenarios and support decisions with traceable alternatives.
Local LLM agent
Operate sensitive workflows with a local or private model without ongoing dependence on external model APIs.
Designed for bounded, evaluable processes. Fully autonomous high-risk decisions are outside the first pilot.
Explore AI workflows and their business valueHow it works
Four steps. One clear decision.
- 01
Fit call
Review the workflow, data, accountability and expected value.
- 02
Scope
Define pilot boundaries, metrics, operating model and safety controls.
- 03
Build & test
Build, evaluate and document a controlled agent.
- 04
Readout
Receive evidence, risks, cost shape and a clear recommendation for the next step.
A clear frame
Small enough to decide. Relevant enough to matter.
A typical pilot sits in the €20,000–40,000 range excluding VAT, depending on data access, integrations and operating model. A binding scope follows the fit call.
- 4–6 weeks typical duration
- 1 workflow, 1 accountable team
- local, private cloud or hybrid
- evaluation and handover included
Next step
Which workflow deserves a controlled agent?
An initial idea is enough. Describe the task and the outcome you want. Together, we can assess whether an Agent Pilot or a different starting point makes sense.
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