Your assessments, run as software.
AI reads the material, asks the right people the right questions, and writes the first draft. Your people approve every finding. The report is ready in days, not weeks.
A consulting engagement, run as software.
Everything you receive goes in. A structured body of knowledge grows in the middle. The deliverable renders out of it, and a person confirms every step that matters.
Everything goes in
Documents, interview transcripts and questionnaire answers are read by agents and indexed. Every claim keeps the exact place it came from: the file and the quote, or the person and the date.
Knowledge grows as a graph
Findings, risks, decisions and open questions are connected records, not paragraphs in a file. When two sources disagree, the contradiction becomes visible work instead of a silent choice.
The report is a projection
Deliverables build themselves from the graph and stay current as the knowledge moves. Delivery is a versioned snapshot, with a human approval gate in front of it.
Who it is for
Two audiences run the same engine. The method, the questions and the brand are always yours.
Your method, delivered as software
You sell a method: risk, compliance, ISO, due diligence. Engagement Studio turns it into software your whole team can run, under your brand.
From interviews to a clean specification
You gather requirements, prepare tenders, analyze processes. Engagement Studio turns interviews into a clean specification, with contradictions caught early.
Working with clients, not for yourself? We sell through partners. Your brand, your client, our engine.
Let's meetThe problem
Sound familiar?A few senior people carry the method in their heads. Every project starts from a blank page. Interview notes end up in files nobody opens again. And when the client asks "where does this number come from?", nobody is sure anymore.
Or the other version: the requirements sit in forty documents, and no two of them agree.
How it works
- 01
Start from a template
It sets the questions, the checks and the report format. Use ours or build one from your own method.
- 02
AI reads and asks
It reads the documents, then asks what is missing, in interviews or through a simple link your client opens. No account needed.
- 03
People decide
AI proposes findings. You confirm, edit or reject each one. One named person signs off before anything reaches the client.
- 04
The report writes itself
It grows as you work. When you sign off, it is ready to send.
What a finding looks like
Backup procedures exist but have not been tested in the last 12 months.
Every finding carries its source: a quote, a document, a name. Nothing enters the report until a person confirms it.
Built to be trusted with work somebody signs.
Sources over assumptions
Every record carries its evidence: the document and the verbatim quote, or the person and the answer. A claim without a source is a question, not a finding.
Shared context over isolated tools
All the work lands in one growing graph, so what one agent establishes the next one already knows. No agent calls another: the engine decides every step, which makes runs repeatable and auditable.
Approval over autonomy
Nothing reaches your client without a named person. Questions are reviewed before they go out, findings before they count, and the delivery itself passes a human gate.
Every agent run also shows what it read, what it changed and what it cost.
Read the technology pageWhat changes for your business
Speed
The first draft exists while the interviews are still running. A report that took weeks is ready for review in days.
Quality
Every finding carries its source. Contradictions surface during the work, not after delivery.
Capacity
Seniors stop writing and start deciding. The same team takes on more work, and the work stops depending on who is available.
Knowledge
Findings stay as searchable records, not paragraphs in last year's PDF. The next project starts ahead, not from zero.
It runs on our core. Access rules, the audit trail, workflow and the AI runtime are not built into this one module. They are the system underneath every solution we ship.
Inside OmnicornQuestions we hear first
Whose method is it?
Yours. The engine is ours; the questions, the checks and the brand are yours.
What if the AI gets it wrong?
You reject it. Nothing reaches a client without a named person's sign-off.
Do our clients need accounts?
No. They answer through a secure personal link.
Does client data train the AI?
No. Your data runs your projects. Where a provider's terms matter to you, your deployment can be pinned to models running on hardware you control.
Start with the engagement you repeat.
A past one works fine. In a working session we shape it in the system on your own method, so what you judge is your engagement, not a demo script.
Let's meet