Decision Engine for Financial Services
Automated Decisions Your Teams Can Govern
Enable domain experts to inspect and approve business logic fast and secure. Co-author logic with AI. Your team validates it. Run it deterministically. No code required.
- Built for risk-owned decisions
- Human-validated business logic
- No AI in the live decision
AI makes delivery faster. It does not remove accountability.
The logic moves faster than review
AI can draft rules, workflows, and application code quickly. But if the decision logic ends up buried in code, the risk owner is forced to validate through summaries, tickets, screenshots, or developer explanations.
The wrong people become the control point
Engineering can validate implementation quality. Risk and business experts need to validate policy intent, thresholds, exceptions, edge cases, and customer-impacting outcomes. Those are not the same review.
Evidence is scattered
When the decision is split across documents, code, tests, application logs, and model behavior, it becomes hard to show which version was approved, which inputs were used, which branch fired, and why a specific outcome happened.
Give teams a platform for fast and governed decision-making
Leapter is the agentic development platform for business logic. Co-author with AI. Maintain full control.
Conditions, thresholds, branches, calculations, validations, and decision paths are all laid out as visual diagrams domain experts can read and verify.
Use AI to co-author the logic, assist you with any iterations to the logic itself, and create test runs. All without losing control.
Every run can show the approved version, the inputs, the branch path, the output, and the reason the decision took that route.
For the people who answer for automated decisions
Risk Managers
See how business-critical logic is represented, changed, approved, and traced. Make decision logic reviewable by the teams that own the risk.
Decision Risk Managers
Bring consistency to decisions that cut across apps, channels, agents, and workflows. Keep the approved logic in one place and make each execution traceable.
AI Risk Managers
Separate AI-assisted drafting from deterministic execution. Make clear where AI supports design and where approved business logic takes over.
Credit Risk and Model Risk Teams
Support reviews of credit policies, decision paths, test coverage, and outcome evidence with logic that is visible, versioned, and replayable.
Compliance and Policy Owners
Translate policy into logic your team can inspect and maintain. When a policy changes, review the change in the logic itself, not only in a release ticket.
Risk Technology and Engineering
Give risk owners a governed authoring and validation layer while engineering keeps stable integration through APIs, services, workflows, and agents.
Start with decisions where explainability matters
Credit risk
Risk-rating, eligibility, referral, affordability, limit, and policy-threshold logic that must be reviewed before it affects customers or exposure.
Insurance underwriting
Eligibility, exclusions, referrals, coverage rules, and underwriting guidelines that need business-owner validation when products or policies change.
KYC, AML, and compliance routing
Screening and escalation logic where consistency, evidence, and human sign-off matter more than model improvisation.
Pricing and eligibility
Rate factors, product eligibility, discount criteria, and exception rules that need to stay consistent across customer channels and internal tools.
Developers can check the code. Risk owners must check the decision.
A generated implementation can pass technical tests and still be wrong for the business. A threshold may be outdated. An exception may be missing. A referral path may contradict policy intent. A control may fire too late. The decision may be technically correct and operationally unacceptable.
Leapter moves validation closer to the people who know what the logic is supposed to mean. Developers and AI systems can help create the first draft, but the accountable experts verify the decision path, challenge edge cases, approve the version, and keep evidence for later review.
From policy to approved decision logic
Describe or upload the policy
Start with a credit policy, underwriting guideline, KYC procedure, pricing rule, or decision example.
AI drafts the Blueprint
Leapter turns the source material into visual decision logic: conditions, branches, calculations, and outputs.
Experts inspect and test
The accountable owners review the logic, adjust thresholds, run real and edge cases, and check the outcome path.
The approved version runs
Applications, services, workflows, and agents call the approved Blueprint. The live decision is deterministic and traced.
What you can show after a decision runs
No platform can remove accountability for automated decisions. Leapter gives the accountable team clearer evidence:
- Which Blueprint version was approved.
- Who approved it.
- Which inputs were used.
- Which branch path fired.
- Which output was returned.
- Which tests ran before approval.
- What changed between versions.
That is the difference between asking someone to trust generated logic and giving them a decision record they can read.
Bring one decision your risk team needs to trust.
Choose one example: a credit policy, underwriting rule, KYC path, pricing criterion, eligibility decision, or compliance workflow. In a strategic briefing, we will show how it becomes a Blueprint your experts can read, test, approve, and trace.