Policy layer for compliance decisions
When compliance logic spreads across workflows, applications and spreadsheets, every policy change becomes harder to maintain, test and audit.
Knowledge brings decision logic into one governed policy layer - without replacing your existing stack. Applications, workflows and AI agents provide their current context. Knowledge determines what the policy requires, what information is still needed, and what decision applies.
Caller sends context
Knowledge evaluates applicable rules
Returns verdict + cited rules + normative_hash
Every call recorded for audit reconstruction
Does this sound familiar ?
- A policy change means finding every workflow, application and spreadsheet where the logic was copied.
- Your onboarding asks for information "just in case" - even when most of it never affects the decision.
- Cases that could be resolved deterministically still end up in manual review.
- A regulator asks you to reproduce a decision from 18 months ago, and reconstructing the exact policy version takes weeks.
- Your AI agent works - until Legal asks how you guarantee which policy it will apply before taking action.
Different symptoms. Same underlying problem : the policy that determines a decision is coupled to the systems that collect information, orchestrate the process or execute the action.
What Knowledge changes
One governed policy layer. Many callers.
Your applications, workflows and AI agents send a context. Knowledge returns a deterministic verdict with the rules that determined it and a replayable audit trail.
One layer, many callers
Web forms, mobile apps, back-office systems, workflows and AI agents can all consult the same governed policy layer. Policy logic no longer has to be reimplemented by every caller.
Deterministic verdicts
Same context, same policy state, same decision. Each verdict identifies the rules that determined it. No LLM variance at the decision boundary.
Replayable audit
Each consultation records the normative policy state behind the decision, so historical decisions can be traced back to the rules and policy state that produced them.
Progressive collection
Knowledge determines what additional context is required to reach the current decision - so callers don't need to collect information merely "just in case".
Works with your existing stack
No rip-and-replace. Five modes to choose from.
Knowledge does not replace your workflow engine, your KYC vendor, your OMS or your legacy decision code. It inserts alongside them.
Already have a decision engine ?
Feed existing decisions and context into Knowledge to apply additional governed policy without replacing the underlying engine.
Need to enforce a new control ?
Put Knowledge before execution for a selected decision or policy. The existing system remains in place ; Knowledge governs whether the action can proceed.
Want to validate first ?
Knowledge evaluates the same cases in parallel without controlling the production decision. Compare outcomes before giving it authority.
Launching a new domain ?
Knowledge handles the new flow, the rest stays on the legacy. No impact on today's flows, full control on the new one.
Building something new ?
Knowledge is the decision layer from day one. Install a vertical pack, calibrate the thresholds, working in weeks.
Built for real decision domains
See Knowledge applied to concrete compliance decisions.
Wealth
Structured Products distribution
Product eligibility, client suitability, cross-border rules, portfolio concentration. Four policies, thirteen rules and a working reference integration.
See the Wealth walkthrough →KYC / KYB
Onboarding decisions
Progressive information requirements, jurisdictional rules, PEP and sanctions outcomes, source-of-wealth requirements and escalation decisions - while keeping existing identity and verification providers in place.
See the KYC walkthrough →The founding cohort
Bring us one decision to solve. Founding status comes with it.
Bring one decision that is difficult to change, automate or audit today. Knowledge runs against success criteria agreed upfront, in an adoption pattern that fits your existing stack. Founding-customer pricing, direct product influence, clean exit if the numbers don't land. Three engagements in the founding cohort.
See the design-partner engagement →