Governed AI systems
Put AI on your most sensitive data – without losing control of it.
Koralis AI builds governed intelligence systems that move organisations from fragmented AI experiments to workflow-integrated, policy-checked and auditable AI – without unmanaged SaaS dependency, tool sprawl or data-governance risk.
Proof on your own data. No public pricing. Governance by construction.
Your teams can already run AI across your data. Few organisations can answer the question an auditor, regulator or board eventually asks. Governance gets bolted on after the fact, so it's manual, brittle and easy to bypass – and AI makes it worse.
“Who accessed this data, under what policy, and why were they allowed to?”
Governance, built into the architecture
Koralis builds AI systems where data access, reasoning, audit and workflow controls are properties of the architecture – not policy documents or after-the-fact reviews. The result is AI that's useful and controlled: connected to your real workflows, auditable by construction, and yours.
Kovac · Enterprise
A deterministic governance kernel
For regulated, data-intensive organisations: a kernel that sits between AI and enterprise data, so every action is policy-checked, signed and recorded.
Explore Kovac →CoAct · Mid-sized business
Governed native AI capability
The same governed engine, productised: build AI tools on your own data using templates and connectors, with control and auditability built in.
Explore CoAct →From intent to audit trail – by construction
- 1
Intent captured
A person, workflow or AI agent requests an action.
- 2
Policy evaluated
Checked against identity, ontology, permissions and clearances.
- 3
Plan signed
Approved work is compiled into a cryptographically signed execution plan.
- 4
Execution scoped
Engines and connectors run only within the plan's bounds.
- 5
Audit recorded
Decision traces, lineage and approvals captured as queryable artifacts.
Representative flow – illustrative, not a product screenshot.
Built by people who've done this at scale
Koralis is founded by Dylan Banks and Marko Krznaric, combining board-level commercial strategy with deep AI-systems architecture – including experience across enterprise data platforms and regulated environments. We're live with a design partner in commercial real estate, using governed, auditable data operations on real workflows.
Start with proof, not a pitch
A focused Proof Pilot deploys Kovac against one of your real datasets in two weeks – a live decision trace, a signed pipeline your stakeholders approve, and an audit timeline on your data. For mid-sized teams, a Quick-Start stands up one governed workflow in days.
Tell us what you're trying to govern
We'll come back with the most useful next step – a walkthrough, a conversation, or a focused proof on one of your own datasets.