Run ten discoveries with the rigor you'd put into one.
You approve every line before it's locked.
Noema runs enterprise ERP discovery end to end — multi-site, Oracle EBS → Cloud and D365 F&O. The AI drafts every finding, flag and process map. The consultant disposes of each one before anything is locked or shown to a client.
Not a transcript — a structured, classified, exportable process model. Try it: switch As-is / Target and the site lens above.
You're thinking: I can't let an AI improvise in front of a client.
Correct. So nothing the AI produces is final. Every draft carries a confidence badge, every item carries its provenance, and low-confidence items are flagged for human verification — findable in a dense list, not buried.
The partner is escalated to, never replaced. The AI does the mechanical 80%; your judgment scales over the rest. That's the spine: the AI drafts, you dispose.
- →Hallucination — answered by confidence badges, provenance, and human-verify on low-confidence items.
- →Craft — moldability keeps the senior in the loop; the platform does the breadth, not the judgment.
A discovery flow, not a pile of feature cards.
Intake to deliverables, in sequence. Every finding becomes a classified discovery item — kind × domain × scope — that has to reach a disposition. Nothing dangles. This is the line between a discovery platform and a notetaker.
One item. Three chips. A disposition it must reach.
"Finding", "requirement", "gap", "open question" aren't separate buckets — they're states of one item that classifies and moves. An item can change type as understanding sharpens, keeps its identity and its trail, and must end somewhere.
- kindlifecycle role — open question, requirement, gap, decision, risk, variant…
- domainwhat it's about — data, process, governance, integration…
- scopewhere it applies — global, region, or a named site.
The same item — same id, same trail — wherever it appears: a process node, a fit-gap row, an open point.
Keep the senior interviews. Delegate the breadth.
Per stakeholder, the principal sets the interview owner: principal-led for the few that need judgment, platform-conducted for the broad set. Every item still reaches a disposition — nothing dangles because it was delegated.
That's the capacity story, and it's where the ROI is self-evident: the same partner covers ten discoveries at the rigor of one. For independents, it's how one person runs an engagement that used to need a team.
The judgment calls — kept in senior hands.
The breadth — conducted to the rigor you set.
Voice in, structured out. Every line the AI extracts is a draft discovery item — accepted, edited, or rejected by a human, with the transcript span kept as provenance.
The output is something you'd actually hand a client.
Real Oracle and D365 taxonomy. A fit-gap assessed per site. An open-points register that names who must decide. Native xlsx, pptx and docx — edited in-platform, versioned, re-exported as often as you need.
Cloud routes requisitions through approval groups and rule sets; value-threshold routing is standard — adopt as delivered, configure per region.
The explicit line between delegated work and principal work — what only the partner can close.
Only what's true today.
Built on Anthropic's Claude. Enterprise deployment options — including for Microsoft 365 environments — are scoped per engagement.