Core replacement is a multi-year, multi-million bet most CIOs cannot reasonably take. CoreFi is designed to coexist with the legacy core and modernize one workflow at a time — under permissions, policy gates, human approvals and a single audit trail. The legacy stays system-of-record for what has not moved; CoreFi takes over the journeys where it earns the right to.
The platform is built so the legacy ledger keeps doing what it does — system-of-record for unmigrated workflows — while CoreFi handles the journeys that have moved across. Agents operate inside CoreFi’s governance plane; the legacy is integrated, not replaced. The migration boundary is per workflow, not per system, so progress is incremental, reversible at the routing layer, and auditable.
Until a workflow is fully migrated, the legacy ledger remains authoritative. CoreFi reads and writes through integration adapters; the institution never loses access to its existing books, reports or operator screens.
Workflows that have moved across — onboarding, lending decisions, servicing tasks, treasury operations — run on CoreFi’s real-time core and governed AI control plane. Agents act under permissions, policy gates and human approval routing.
CoreFi records its side of every workflow case-by-case — trigger, retrieved data, plan, policy outcome, API calls, human decisions. Legacy events feed in through integration adapters so the case record remains traceable across the boundary.
Each workflow follows the same four phases: discover what it does, observe in shadow, run in parallel, and only then cut over. The institution decides which workflow earns the next phase — based on evidence from the previous one, not a fixed program-management deadline.
Map the legacy workflow end-to-end: the data it touches, the integration points, the operator screens and batch jobs around it, the controls that already apply. Output: a scoped target workflow and a measurable success definition before any code moves.
CoreFi receives the same inputs as the legacy through integration adapters but produces no side effects. Agent recommendations and policy outcomes are recorded against real traffic so they can be compared with what legacy actually does — without changing what customers experience.
CoreFi handles a defined slice of the workflow live — a customer segment, a product line, a geography — while legacy stays system-of-record. Outcomes are reconciled per case; risk and operations sign off; the slice grows on evidence, not on a Gantt chart.
For the migrated slice, CoreFi becomes the system-of-record. The legacy path drains down or stays as a historical read source. Cutover is per workflow, so the rest of the bank continues unaffected; the next workflow re-enters Discovery on its own timeline.
CoreFi connects to the legacy through the integration surface the bank already runs — APIs, events, file imports and operator-facing exports. The legacy is not asked to be rewritten; the bridge is on CoreFi’s side.
CoreFi calls the legacy through whatever API surface it exposes — REST, SOAP, JDBC views, mainframe gateway services. Adapters live inside CoreFi; the legacy schema does not change for the migration.
Where the legacy emits events (Kafka, MQ, change-data-capture streams), CoreFi subscribes and keeps its working state in sync. Where it does not, CoreFi polls through the API layer and treats the response as the event.
Batch files — positions, reconciliations, regulatory extracts, end-of-day cuts — are first-class inputs and outputs. CoreFi consumes legacy files for shadow and parallel phases, and produces them for downstream systems that still expect the legacy format after cutover.
CoreFi exports metrics, logs and audit events to the bank’s existing observability stack on request. Reconciliation between CoreFi and legacy outcomes during shadow and parallel phases is exposed as a dashboard for risk and operations.
Every phase is designed so that “back to legacy” is an operational decision, not a project. CoreFi’s control plane keeps the institution in charge of when a workflow moves forward, when it pauses, and when it reverts — and writes every step into the case record.
If a parallel slice or post-cutover workflow needs to be returned to the legacy path, CoreFi re-routes new cases to the legacy integration adapters. State already written by the authoritative system — CoreFi for cutover workflows, legacy for unmigrated ones — is not unwound by the switch; any reconciliation needed is scoped in the reversal runbook prepared with the workflow before parallel begins; detail available on request.
Phase transitions — promoting a workflow from shadow to parallel, expanding a parallel slice, cutting over — require approval from two named owners on the bank side. The approval is logged against the case the way any other policy gate is.
Through shadow, parallel and cutover, CoreFi keeps a case-level record — trigger, retrieved data, agent plan, policy outcome, API calls, human decisions, final state — that is structured to reconcile with what legacy records on the same case. The format is designed to support a bank’s supervisory review process; mapping to a specific bank’s audit standard is scoped during Discovery.
Bring one workflow you would migrate first if the risk envelope held. We will scope Discovery against your legacy core, name the integration adapters, and define what shadow and parallel would look like on your traffic before you commit anything to a program.