Cephos is building the context layer that resolves, syncs, and packages operational truth so humans and agents can act reliably — even when the world is fragmented, partially offline, and moving faster than systems stay synced.
The Problem
The AI stack has matured fast at the model and orchestration layer. But in the physical economy — field operations, industrial workflows, supply chain, robotics — the real bottleneck is upstream. Context arrives stale, fragmented, contradictory, and often not at all.
Systems reflect the world as it was, not as it is. Critical updates are batched, delayed, or siloed in people's heads.
Truth is scattered across devices, people, systems, and local observations with no single source of record.
Edge environments go offline. Agents that assume connectivity fail silently — or not so silently.
Multiple data streams contradict each other. Without provenance and resolution logic, agents can't know what to trust.
The Solution
Cephos sits between the messy real world and the agents trying to act in it. We resolve fragmented state, handle degraded connectivity, track provenance, and package operational truth into something machines can reliably use.
We're entering through the workflows where the pain is most undeniable — degraded, edge-like operations where agents fail today without us. But the long-term company is the runtime that real-world agents depend on.
Merge conflicting signals from multiple sources into a single, trusted world-state with full provenance.
Designed for intermittent connectivity. Context stays usable and consistent whether you're online or not.
Every fact carries a lineage. Agents know where context came from, when it was observed, and how much to trust it.
Context delivered in structured, machine-usable formats — so agents can act, not just retrieve.
Building now
In most physical industries, operational data lives in sensor feeds, spreadsheets, and hand-written notes — not clean databases. Cephos builds the centralised control layer that ingests and standardises this fragmented data so agents can act on it.
We're entering through evaluation: before agents can be deployed in these environments, builders need to test them against the conditions they'll actually face — stale data, conflicting records, sources that go offline mid-task. Our sandboxes make that possible.
Ingest fragmented operational data from any source into a unified context snapshot that agents can reason over.
Inject the degradation that real physical environments produce — so your test conditions match what agents will encounter in production.
Run structured scenarios against degraded context. Measure whether agents answer correctly, flag uncertainty, and handle imperfect information.
Why now
The next wave of agent infrastructure will not be won at the model or orchestration layer alone. In the industries that still run the physical world, the bottleneck is operational context: what is true right now, what changed, what conflicts, and what can be trusted.
Whoever owns that layer becomes part of the substrate.
Where we play
We're starting where the pain is acute and the status quo is clearly broken. The platform extends wherever operational context is the limiting factor for automation.
Disconnected crews, dynamic job sites, equipment state that only lives on-device.
Sensor networks, legacy systems, and shop floor realities that don't match the ERP.
Multi-party, multi-timezone, multi-system — state diverges before ink dries.
Physical agents need grounded, real-time world-state to act safely and correctly.
Grid-edge assets, partial telemetry, and operations that can't wait for sync.
Our thesis
Generic agents are not enough for the industries that still run the world. They break when state is stale, partial, conflicting, delayed, or trapped in people's heads.
Whoever owns the layer that turns that mess into usable, trusted world-state becomes part of the substrate.
Edge operations are just the first place where the pain is undeniable.
Get involved
We're working with early partners in field operations, industrial automation, and supply chain. If you're dealing with the context problem and want to solve it together, reach out.