Case Intake
AI KYC workflow platform
AI-powered preparation for every Source-of-Wealth review. Source-of-Wealth review.
AICorros turns fragmented client evidence into source-linked narratives, wealth breakdowns, timelines, evidence matrices, gap lists, and review-ready exports for human bank staff.
Platform modules
Generate case intelligence from the evidence up.
Claim Extraction
Material figures, dates, ownership logic, and assumptions become inspectable objects.
Evidence Matrix
Every important claim is tied to support, gap, source, page, value, and reviewer action.
SoW Narrative
Drafts stay source-linked so review comments can be resolved without rebuilding the pack.
Export Pack
Narrative, table, timeline, matrix, gaps, and appendix move into bank workflows together.
Pilot Metrics
Cycle time, rework, challenge patterns, and adoption are measured from day one.
AICorros powers review-ready, source-linked work in private banking, from RM intake to CLM challenge and export.
Automate preparation. Preserve human judgment. Govern every material claim.
SoW narrative
Draft the story only after the evidence and calculations are connected.
The first-pass MVP must make the Source-of-Wealth narrative, wealth breakdown, evidence matrix, and timeline strong before expanding into lighter modules.
Shared workflow engine
One operating model, tuned for onboarding and periodic review.
Create a clean case object before drafting starts.
The RM or support user opens a case, chooses approved documents or a synthetic demo case, and defines the client, trigger event, entities, and review boundary.
System prepares
Reviewer sees
Evidence standard
Every material claim keeps its source, page, value, status, and reviewer action.
Manual drafting can produce polished narratives that are difficult to audit. AICorros makes the evidence trail visible before export, not after an exception.
Wealth events
Turn old profiles into current, challenge-ready review objects.
Periodic review can become a full rewrite when standards rise, evidence is stale, or CLM challenges assumptions that were once accepted.
Control posture
The product prepares and checks the pack. The bank still decides.
AICorros is not final approval, risk rating, STR decisioning, client acceptance, or replacement of RM, CLM, FCC, compliance, or bank approvers.
Case, claim, evidence, benchmark, rule, source, and version objects.
Exports remain blocked until reviewer actions and material gaps are recorded.
Synthetic or public data only before legal, IP, and confidentiality clearance.
Real data requires approved model, privacy, retention, logging, and security posture.
Buyer economics
Give investors the bank budget case, not only the product story.
The model starts with one private-bank department or booking center: 80 active users, 480 submitted SoW case packs, 7,200 hours freed, US$0.66m gross annual benefit against US$0.44m AICorros recurring spend — a 1.5x gross ROI with roughly 8-month payback.
Net annual benefit after bank tokens
US$220,000
AICorros monetizes seats, platform floor, workflow usage, and governance support while the bank keeps AI spend in its approved tenant.
Annual case packs480
Review-ready packs432
Hours freed7,200
Gross benefitUS$660,000
AICorros recurringUS$440,000
Payback8.0 months
Gross ROI1.5x
Year-one ROI1.3x
Department platform license lands at US$153k-638k per year before usage fees.
Seat subscriptions plus a platform floor, US$102-319 per submitted case pack, and US$32k-102k annual governance support keep the first purchase at booking-center scale.
Bank-borne Azure/OpenAI spend keeps CISO and data controls cleaner.
The token/API bill stays with the bank tenant, while AICorros keeps the software revenue tied to workflow adoption and governance support.
2030 base case reaches US$13.2m revenue and US$12.3m ARR proxy.
The model assumes 16 production customers by 2030, gross margin rising from 41% to 83%, EBITDA break-even in 2028, and US$5.7m EBITDA in 2030.
US$1.5m base-case pre-seed funds the proof investors will underwrite.
Use of funds prioritizes product development (40%), engineering leadership (25%), legal/security/compliance (15%), and customer discovery (10%), raised after legal/IP clearance and a working prototype.
Near-term path
Build the August demo around three golden cases and measurable workflow lift.
The first sponsor conversation should focus on review-cycle reduction, fewer avoidable CLM loops, visible evidence discipline, and a clear data boundary.
Request pilot conversation