Your supervisor does not trust AI by default — and you have asked the same questions yourself. Who authorised this action? Under what policy? What did the model actually do? Where is the evidence? CoreFi is designed to support compliance and risk officers governing AI workflows the way they already govern human operators — scoped permissions, transaction limits, policy gates, human-approval thresholds and one immutable audit record per workflow, available on request.
Whatever your jurisdictional perimeter — banking, payments, electronic money, consumer credit, asset-tokenization — the supervisor's questions about AI rhyme. CoreFi is designed to support compliance and risk teams who need to be able to say "yes" to the three below without crossing the vendor-into-licence line.
An agent without a written authority is an agent your supervisor cannot accept. CoreFi treats every agent like any other operator: scoped API tokens, role permissions, transaction limits, customer-segment rules and jurisdictional restrictions, defined ahead of the workflow.
The agent's scope is documentary, not implicit — available on request alongside the rest of the policy pack.
Every CoreFi workflow produces one immutable audit record: trigger, retrieved data, model and prompt version, plan, policy outcome, API calls, ledger effects, escalations, human decisions, final state.
The same record covers human and agent workflows, so a supervisor reviewing an AML case or a credit decision sees the full chain — not a model summary and a separate spreadsheet.
Policy gates run between the agent's plan and any side effect. Anything outside the scoped permission, the transaction limit, the segment rule or the jurisdiction is refused at the gate, with a structured reason and an escalation path.
For decisions that policy says a human must take, the agent prepares the case and the human approves — the audit record covers both.
Every CoreFi agent runs through the same seven-step lifecycle, on the same governed platform, with the same audit record. The lifecycle is designed to support a compliance and risk function that has to answer for what the agent does — not absorb a black-box system that operates outside their perimeter.
The agent reads the case, retrieves the relevant data through scoped APIs and produces a structured plan — not free-text. The plan is auditable and reviewable before any side effect.
The plan runs through policy gates: scoped permissions, transaction and exposure limits, customer-segment rules, jurisdictional restrictions and human-approval thresholds. Anything that fails the gate stops, with a structured reason.
Only the actions that passed the gate execute — through the same governed APIs a human operator would use. No agent has uncontrolled write access or out-of-band ledger authority.
Trigger, retrieved data, model and prompt version, plan, policy outcome, API calls, ledger effects, escalations, human decisions and final state — one immutable record per workflow, exportable in standard formats.
Anything outside policy, outside threshold or marked for human review is escalated with the full case context. The reviewer sees a structured packet, not a model conversation.
Outcome data feeds back into the agent under a documented evaluation regime. Changes to prompts, models or policy are versioned and reviewable; the audit record links the workflow to the version that produced it.
CoreFi is platform infrastructure; the licensed activity and the regulatory perimeter sit inside the customer's entity. The evidence below is what the platform produces as a by-product of running AI workflows, and what is available to support internal audit, second-line review and supervisory request. The detailed posture lives in /trust-center.
Per-workflow immutable record across every agent and human action, exportable through documented APIs in standard formats. Designed to support internal audit, external audit and supervisory request.
Scoped permissions, transaction limits, segment rules, jurisdictional restrictions and human-approval thresholds — defined ahead of the workflow and available on request as a documentary artefact, not an implicit configuration.
Model version, prompt version, evaluation regime and change history captured in the audit record. Designed to support model-risk-management style reviews aligned with your institution's framework.
Sanctions, PEP, ID verification, bureau data and similar integrations run through configured providers under your contractual perimeter. CoreFi orchestrates; the provider remains the source of record for the data it supplies.
Deployment shapes designed to support regional data residency and least-privilege access to customer data. Specific posture available on request and documented in /security-compliance.
Customer, account, ledger and audit data exportable in standard formats. Each adoption path in /implementation has a defined exit posture; Managed Platform includes off-boarding terms in the service contract.
Bring your model-risk-management framework, your audit committee's questions and the AI use cases your supervisor has asked you about. We will walk through how CoreFi's policy gates, scoped permissions and audit record map to your control framework — and what evidence is available on request for each control. We do not give legal or regulatory advice; we describe how the platform supports the posture your compliance team has to defend.