The unified platform for enterprise engineering teams.

Entirely inside your own infrastructure: private VPC, on-prem, or fully air-gapped, on AWS, Azure, GCP or your own data center. There is no vendor-hosted control plane and no shared multi-tenant service. You run a single-tenant deployment you control end to end. For EU buyers, that means an EU region or your own EU data center, so data never has to cross the Atlantic to reach a US-based processor.

No. Applications, data, models and logs stay inside your perimeter, with zero data egress. The only outbound path is a frontier model API, and only if you explicitly choose to call one. Cut outbound traffic entirely and the platform keeps running.

Yes. You choose where kis.ai runs, including an EU cloud region or your own EU data center. Combined with zero data egress, nothing crosses into a US-based processor unless you explicitly choose to call a frontier model API.

AI Dev Studio is what your teams build with: Anica, AI App Forge and AI Platform Engineering. The Runtime is what your applications run on in production: AI services, backend services, DevSecOps and AI-managed infra. They are one system, but you can adopt them independently: run existing apps on the Runtime alone, or use the Studio to build faster. Most teams start with a single use case on a single machine, not a platform-wide rollout, and expand from there.

The platform is architected to meet the control requirements behind SOC 2, HIPAA, GDPR, PCI DSS, DORA and FedRAMP: every action is written to an append-only, tamper-evident audit trail with provenance on each artifact, so you can reconstruct which model decided what, on which data, months later. You still run your own audits and certifications; kis.ai gives you the evidence to pass them, not a certification on our behalf. kis.ai runs inside your own infrastructure with no vendor-hosted control plane, which also removes the third-party ICT concentration risk DORA is designed to catch. Credit scoring and insurance underwriting are classified high-risk under the EU AI Act, and the same audit trail and model provenance are the documentation that classification requires.

Yes. The paid proof of concept runs in your environment against criteria you set, and your security, risk and compliance stakeholders are welcome on every call. We'd rather surface their requirements before production than after.

Applications you build on kis.ai interoperate with the systems you already run: existing databases and data sources, identity and SSO, APIs and CI/CD. Existing apps run alongside new ones on the same Runtime, so you integrate rather than rip and replace.

kis.ai is licensed as a platform you host, so the compute and the models are your own. There is no per-token metering on your private models and no data-egress or data-volume penalty. Cost tracks the infrastructure you choose, not your usage: a single GPU instance for one focused use case costs far less than a full on-prem cluster for a platform-wide rollout. Talk to our solutions team for licensing specific to your deployment.

Yes. You own the applications, your data and your fine-tuned model weights as IP, and they already live in your environment. There is no vendor cloud to exit and no egress penalty, because none of it was ever outside your perimeter.

We start with a paid proof of concept on your own infrastructure, against success criteria you set. Rollout is staged: install the Runtime in your environment, connect identity and data, then build. The fastest teams have taken a first application to production in a matter of days.