For forty years, software was built for people clicking buttons. Agentive AI asks for something else — software where people and agents work as peers: graph-native, governed to the action, and yours to inspect. Most teams bolt a chatbot onto the old world. We engineer the new one, from the substrate up.
Knowledge as a typed graph your agents can read, write, and reshape — not facts trapped across a dozen silos. That substrate is jvspatial.
Every action staged, authorized, and audited — human, agent, or connector. Trust isn't bolted on after the fact; it's how the runtime works. That runtime is jvagent.
The whole stack is on GitHub. Inspect it, run it, build on it — and never get locked in to a black box.
We don't bolt AI onto old systems. We engineer the substrate, the runtime, and the agents as one — researched, open, and built to do real work.
We study what makes an agent work in the real world — the architectures and failure modes hiding behind the demos.
We build the stack in the open — jvspatial for the graph substrate, jvagent for the agent runtime. Production frameworks, on GitHub, free to inspect and run.
We craft and operate Selphs on that stack — grounded, governed, human — live where your customers already are.
Integral is the platform expression of everything we build toward: a typed knowledge graph with an agent-authorable schema, a single authorization gate that fail-closes for agents, and one audit stream across every action — human, agent, connector, or system. The canonical place your agents read from and write to. Built on jvspatial and jvagent, it turns a whole organization into one where people and AI agents operate as peers.
Explore AI Transformation“One graph. Every action, governed.”