AI that does the work.

Chat assistants answer; Onky acts. It executes across the systems you run: updates the CRM, chases the invoice, posts the summary to Teams, and builds the tools it is missing. Every action passes through Onky's policy engine, the Kernel, with a full audit trail, your data never reaches a third-party AI lab, and the whole platform can run inside your own infrastructure.

It builds it. The Kernel, our policy engine, saves the task with its context, builds the missing tool, and runs it through policy checks. The original task then resumes and completes, and the new tool becomes a governed capability your whole organisation can reuse.

The company brain is Onky's governed picture of how your organisation works: processes, owners, handoffs, and tools, assembled from the systems you connect and kept current by the work Onky executes. Access is role-based, audited, and under your retention control. It is what lets agents act with context instead of guesses.

Yes, exclusively. Every model call is logged and policy-checked by the Kernel, our policy engine. Open-weight models are what the guarantees rest on: no frontier AI lab sees your prompts or trains on your work, so your IP and your data stay yours, and no model vendor sets your pricing, so costs stay under your control. It is also why Onky can run in your cloud, on-premise, or air-gapped, where proprietary-API models can't follow.

Wherever your rules say it has to: on Onky's managed cloud today, with private VPC, on-premise, and air-gapped deployments available on request. The models are open-source: your data never reaches a frontier AI lab and is never used to train models. Access is role-based and logged, retention is under your control with deletion on request, and Onky signs a DPA as your data processor at pilot signing, with every subprocessor disclosed in it.

Yes. Because Onky runs open-weight models, the whole platform travels: your cloud, your own data centre, down to air-gapped. Today it runs on Onky's managed cloud. Private VPC is next on the roadmap, and on-premise and air-gapped deployments, with Onky's policy engine, the Kernel, fully inside your own perimeter, are available on request. Book a demo and we will scope it with you.

Onky is built around what the Act asks operators to demonstrate: a complete audit trail, transparency over automated decisions, and human oversight through your policy gates. Every build, deployment, and model call runs through Onky's policy engine, the Kernel, and is logged end to end. Onky does not certify your compliance; it gives you the governed architecture and the evidence.

Shadow AI is what happens when employees use AI tools outside governed channels. Onky closes that path by being the governed channel: every model call, build, and deployment runs through the Kernel, our policy engine, and every connector is governed by default via MCP. Nothing operates outside your policies or your audit trail.

Access is invitation-only today: we are running private pilots. It starts with a 30-minute call to understand your needs. Then, during onboarding, Onky discovers which tools your teams are missing and which agents and automations they need. From there you just start using it: whenever something new pops up, Onky builds it, so your team stops losing time to repetitive tasks.