Case study · Onboarding
AI supplier onboarding
Onboarding that creates a usable supplier master, not a PDF graveyard.
The challenge
New suppliers arrived through email threads and shared drives, so the same vendor was often keyed more than once. Diversity, risk, and banking data were collected late and stored apart, and much of it was still incomplete by the time the first purchase order was due. Approvals stalled while buyers chased missing supplier documents.
Approach
- Structured onboarding tied to a single supplier record
- Category-aware questionnaires and document collection
- Validation and de-duplication before a record goes active
- Clean handoff into performance and risk without re-keying
- Audit trail kept on the record from the first request
Results
- Faster time-to-active supplier
- Fewer incomplete masters at go-live
- One master record instead of duplicate vendor entries
- Diversity and banking data captured up front, not chased later
- Audit-ready evidence on the record
Modules used
More case studies
Case study · National Fuel
National Fuel achieves 98% data accuracy
Supplier data accuracy above 98%, with expected gains in RFP and onboarding efficiency.
Case study · Greenberg Traurig
GT Law cuts invoice management time by 27%
Invoice management efficiency improved 27%, with supplier data accuracy above 98%.
Case study · Travel + Leisure Co. · Video
Data processing cut by more than half
Data processing time cut by more than half, with clearer reporting and faster decisions.
Next step
Show us the mess.
We'll show you the record.
Thirty minutes with someone who has run procurement, using your data, framed for a similar working session.
A working session, not a pitch
Bring a raw spend export or supplier list and see your own data.
Replace or orchestrate
We'll say which path fits, including when neither one fits yet.
No homework required
Messy files are fine. Cleaning them up is the product's job.
