The Hybrid Intelligence for enterprise edge and physical AI.
Local first. Cloud only when it counts.
One command. Every edge constraint, handled.
Existing serving systems optimize single-model token speed in the datacenter. Fluxion Edge is built for the constrained, multi-model, multi-user reality of the edge.
A real agent stack, on the hardware you already own
LLM, embedding, and guardrail models share one device without competing for memory — so a full agent stack fits on the 16/32 GB machines already in the building.
You don't run NVIDIA everywhere. Neither do we.
The same engine runs across chip families — Intel, AMD, Qualcomm, Apple Silicon — with no hand-ported builds and no CUDA lock-in.
Some work can't leave the building
Sensitive work stays on-device by default. The cloud is reached for only when a task genuinely needs it and policy allows it.
Many users, one machine, no interference
Every inference session stays isolated from the next, with latency that stays predictable when the box is under load.
Cross hardware
Cross agentic apps
Day 0/1 model support
Hybrid intelligence, across the enterprise.
Latency budgets, data boundaries, cost ceilings — most real workloads have a limit that rules out sending them to a frontier API. Fluxion is how capable agents run inside those limits, on the hardware the work already lives on.
Real-time loops stay local
Anything on a millisecond budget runs where it happens, and keeps running when the network doesn't. The slower, heavier thinking goes to the cloud on its own schedule — never in the critical path.
Private by default, not by configuration
Regulated and confidential work never leaves the machine it started on. A frontier model is reached for only on the hardest asks, and only for work that carries nothing sensitive.
Always-on agents at no marginal cost
Agents that run continuously are unaffordable per-token. On hardware you already own, the next million tokens cost nothing — so the agents worth leaving on can stay on.
Which model, on which chip, for which task.
Nobody can tell you what an agent will actually do on the hardware you're about to buy — how fast it responds, how well it does the job, what it costs to run all day. We're building the independent ranking that answers it: model × hardware × agentic benchmark, measured the way these workloads really get deployed.