01
A bounded use case and evaluation set
We define what the workflow may prepare, what it must never decide and how useful output will be judged.
Services
02 · AI workflows with human control
Put AI inside a controlled business workflow—not in charge of the business.
Assistants grounded in business knowledge, image processing, structured extraction, qualification and editable reply preparation.
Brief your projectThis is the right move when…
The problem is already visible in daily work.
01
The team repeatedly reads, classifies or extracts the same kinds of documents, images or enquiries.
02
Good replies depend on business context spread across files, inboxes and experienced colleagues.
03
AI could prepare work, but privacy, accuracy and final responsibility must remain explicit.
What gets delivered
Not a specification pack. A working production boundary.
02
Business context and structured outputs
Relevant knowledge, files and case data are supplied in a controlled form, with outputs shaped for the next real action.
03
Review, permissions and audit trail
People can inspect, edit and approve sensitive output, with clear roles and traceable state changes.
04
A production workflow, not a chat demo
The assistant is connected to the interface, data and operational step where the work actually happens.
Delivery model
Three explicit decision points.
- 01
Scope
The outcome, risks and first-release boundary are written down.
- 02
Build
Focused engineering with working increments and direct decisions.
- 03
Launch
Production release, verification, documentation and a clear handover.
AI output is treated as prepared work, not unaccountable truth. High-impact decisions and outgoing communication remain reviewable, editable and owned by a person.
Relevant client system
Varga Antik: AI prepares the intake; the expert keeps the decision.
Images and first-contact context become a structured working record while valuation and commercial responsibility stay with the human specialist.
Read the related case studyCommon questions
The important boundaries, before the brief.
Can you use our private company knowledge?
Yes, when access, retention and permission boundaries are agreed first. The design starts with who may see which source and output—not with a model demo.
How do you reduce hallucinations and unreliable output?
By narrowing the task, grounding it in approved context, requiring structured output, testing representative cases and keeping human approval where errors matter.
Are we locked to one AI provider?
The workflow and data boundary are designed as the durable product layer. Provider-specific capabilities are isolated where practical so the business is not built around one prompt.
Can it run without human approval?
Low-risk internal steps may be automated after testing. Decisions, commitments or sensitive external messages keep an explicit human owner.
€10k–30k · Founder-led delivery
Start the brief with the operational problem.
Describe what happens today, where time or revenue is lost and what must work differently. The first reply will clarify fit, primary risks and the sensible next step.
Brief your project