Services
Most engagements follow the same arc: understand where AI fits and how it will be governed, decide where it should run, then put it into production. Each service stands on its own, and each builds on the one before it.
Service 01
Most organizations already have people using AI, with or without a policy. A discovery engagement establishes where AI can help, where it shouldn't be used, and what controls need to be in place before it scales. We interview leadership and department heads, map the workflows that matter, and turn what we learn into decisions your team can act on.
Governance here is practical: an AI use policy your people can follow, clear ownership for AI-assisted decisions, and a record of what each AI system was allowed to know and do. We work alongside your legal and compliance function, which continues to own regulatory interpretation.
Service 02
For many regulated businesses, the question isn't whether AI is useful. It's whether design files, customer records, or financial data can be sent to a public AI service at all. Private AI keeps the models and the data inside your security boundary, running open-weight models on dedicated infrastructure.
It also changes the economics. Capacity-based infrastructure has a cost you can forecast, rather than a metered bill that grows with every new user. And because the models are open-weight, you aren't tied to a single vendor's pricing or product decisions.
Service 03
A roadmap only matters once it's running. We deliver pilots first, measure them against the outcomes the roadmap set, and expand what works. Adoption is planned alongside the technology, so governance keeps pace with use rather than trailing behind it.
The technology underneath
Our services are built on technology we develop in the open, so governance is something you can inspect rather than take on trust.
An open specification (Apache 2.0) for machine-readable governance context. SCS turns policies, standards, and decisions into versioned, reviewable artifacts that AI systems can use and auditors can check.
The runtime that delivers governance context to AI agents and records what each agent knew when it acted: agent identity, policies delivered, and context version, for every request.
A runtime for agentic workflows. paepae manages the context of multi-agent applications as they run and reports into the control plane, so agent-to-agent work stays inside the same governance as everything else.