Kora
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Governed AI workflows for regulated finance.

Run the operations your regulators watch as workflows your firm controls, where AI handles the routine path, people approve what matters, and every run leaves audit-ready evidence.

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A back-office operations desk: hands working through a printed reconciliation report with a pen, a stack of case folders beside it, monitors of data rows and a muted chart and a shelf of binders softly blurred behind.
§ 01 · The approach

Financial services

Kora runs financial-services operations as governed workflows: reconciliation, reporting, attestation, and settlement execute under a released process version, with scoped permissions, human approval gates, and a hash-chained, replayable evidence record shaped for DORA, the EU AI Act, and model-risk expectations.

01

Operations under release control

The process that runs in production is the released version, and changes ship through the same reviewed release path, so an auditor can see exactly which version handled a given run.

02

Evidence built at run time, not after

Every run records inputs, decisions, approvals, and outcomes into a hash-chained, replayable record. The evidence is produced by execution, not reconstructed by a compliance team before an exam.

03

AI proposes, a person decides

Agents handle the routine path and prepare recommendations, and a person holds approval on the actions that carry regulatory or financial risk.

§ 02 · Related use cases

See it in practice

Concrete workflows teams in this industry put into production.

§ 03 · FAQ

Questions, answered.

What teams ask when they evaluate Kora for this problem.

Critical processes get release control, run-time observability, and a hash-chained, replayable record on every run. That gives you the operational-resilience evidence DORA expects and the record-keeping the EU AI Act Article 12 calls for, available per run rather than assembled after the fact.

Yes. The runtime installs from a Docker Compose bundle and runs customer-controlled: on-prem, in your own cloud account, or fully air-gapped, so sensitive workloads and their data stay inside your control.

No. Agents recommend and route, and a person approves the actions that carry risk. The record shows both the recommendation and the human decision.

Yes, inside guardrails a supervisor can inspect. In Kora an agent works under a released process version with scoped permissions, a person approves the actions that carry regulatory or financial risk, and every run leaves a hash-chained, replayable record. The question shifts from whether the model can be trusted to whether the control can be shown, and the control is in the process.

Per run: the released process version that executed, every human, system, and AI action, the approvals with their owners, and the outcome, hash-chained and replayable. Control evidence is produced by execution rather than assembled in the weeks before an exam.
§ 04 · Next step

Bring one regulated process.

In a demo, bring an operation your regulators watch: a reconciliation, a reporting chain, a review queue. We will run it as a governed workflow and show the hash-chained evidence record it leaves.

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