Deploy AI-driven micro creditworthiness checks.
Karini AI agents run every credit check, show which ones failed instead of one score, and apply your credit SOP. Analysts focus on the cases that need judgment.
- Written for
- Credit Director
- Also in the room
- Controller and credit analysts
- Governed by
- Credit Management SOPCM-OPS
Consistency is the first thing to break under load.
Credit teams don't fail on the hard cases. They fail on ordinary ones under load: two analysts, same account, different answers, and no record of the rule either used.
That's a control weakness. A score of 68 speeds up the queue, but doesn't say which check failed.
The agents, in the order they run.
Four agents. Every check in your SOP runs and reports separately. Exposure is calculated against the limit, then the SOP rule releases the order or routes it to the right approval level.
A held order lists each check, passed or blocked, so the analyst sees exactly what failed.
See it in action.
A held order shows each check, the exposure math and the SOP rule that held it, one click from that SOP section.
The reviewer releases, approves a partial amount or overrides one check. Each action is logged with the reviewer's approval level.
Same thresholds as order intake. A different decision.
Compare with the Order and Quotes Processing credit table. Same conditions, but at 150% to 200% of the limit, order intake escalates and this SOP holds.
Neither is wrong. One protects a waiting customer; the other protects the business. Two SOPs, one platform, no code.
One extra rule here: three or more failed checks hold the order at any exposure.
Credit management rules
From the reference credit SOP. On your ERP, the thresholds are yours.
| Scenario | When it applies | Decision | Approval | SOP section |
|---|---|---|---|---|
| Exposure at or below 100% of limit, with no adverse signal | AUTO_RELEASE | No approver required | Credit Scenario Dispatch | |
| Exposure 100% to 110%, clean aging, days to pay stable | AUTO_RELEASE | No approver required | Credit Scenario Dispatch | |
| Exposure 110% to 150%, no aging deterioration | ESCALATE | Level 2 | Credit Scenario Dispatch | |
| Any balance in the 61 to 90 day bucket, or days to pay worsened by more than 25% | ESCALATE | Level 2 | Credit Scenario Dispatch | |
| Exposure 150% to 200% of limit, or three or more blocking checks | HOLD | Level 3 | Credit Scenario Dispatch | |
| Exposure above 200% of limit, or an order above $100,000 | HOLD | Level 4 | Credit Scenario Dispatch | |
| Any balance 90 days or over, active collections, or a returned payment in the last 90 days | HOLD | Level 3 | Credit Scenario Dispatch |
AUTO_RELEASEReleased and posted by the agent.ESCALATESent to the approver at the level the SOP sets.HOLDNothing moves until the blocking condition clears.How to get started.
Four steps. Only the first needs your process owner.
Review your SOP with a Karini AI engineer
Our forward deployed engineer works with your process owner and queue team to turn your SOP into a clear spec: rules, thresholds, approval levels and gaps.
The gaps matter most. Where your SOP is silent, the queue is being worked from memory.
You bring
The SOP that governs the process today, in whatever state it's in.
Connect the workflow and your ERP
Your SOP becomes the workflow the agents follow. We connect through APIs, governed screen access where there's no API, and email intake.
Your ERP stays the system of record. Nothing is migrated or replaced.
You bring
An environment to connect to, and the person who owns access.
Test against your own history
Every rule runs on your past exceptions first. You see which rule each case hit, and fix the SOP where it's wrong.
Fixing it here costs an SOP edit, not a reversal.
You bring
A sample of closed cases, including the awkward ones.
Deploy to production
Live in your environment, behind your approval levels, with the audit trail on from day one.
The next use case starts at step one with its own SOP, not a new project.
Bring your SOP. We'll run it against your queue.
Pick one use case. If the rules are written down, agents can follow them. If not, we write them together in the first session.
