Banking

AI inside the bank, built by people who have run one.

We have run core banking, payments and settlement, treasury, credit, digital banking, cloud and data platforms, and the committees that govern them. We build AI that clears risk, compliance and audit, not just the demo.

Workflows we take on

Where the hours go in banking

Document extraction, screening review, periodic refresh, with every decision traceable.

Credit & lending operations

Decision support

Application assembly, financial spreading, covenant monitoring, first-draft credit memos.

Collections & servicing

Customer conversations at scale

Voice and chat agents for early-stage collections and servicing, with escalation and full recording.

Operations QC & reconciliation

Quality, control and compliance

Review every transaction and exception instead of a sample; report the system's own accuracy.

Monitoring of communications and transactions; drafting of regulatory responses.

Internal operations

Internal operations

IT intake, branch support queries, management reporting.

What makes it different

Things we plan for from the diagnostic, not the go-live.

  1. Model-risk and AI-governance expectations from the regulator [name: BoT, MAS, etc.] shape what can go to production and how it must be documented.
  2. Core systems are old, central and shared. Integration is the work; we plan for it from the diagnostic.
  3. Every automated decision needs an explanation an auditor accepts. We build the trail before the interface.
In production

Our first engagements are in progress. We publish results only with the client's name and permission.

Not in banking? Most of these workflows have a twin in your industry. See the problems we take on

Bring us the workflow that costs you the most.

Tell us what it is, who does it today, and roughly how many hours it takes. We'll come back within a week with a view on whether AI changes it, and how we'd prove it.