On-Prem & Hybrid

Agentic AI that runs inside your perimeter

Put autonomous agents to work on your most sensitive workflows without shipping the data anywhere. We deploy inference, retrieval, and orchestration on your hardware — or a hybrid split you control to the byte.

  • Data plane stays on your hardware
  • Open-weight or licensed models
  • Locked-down egress by default
  • Audit-ready data-flow evidence
0 bytes
of regulated data leaving your perimeter
100%
of agent actions logged with lineage
CPU→GPU
right-sized to the workload, not the hype
1 path
from hybrid to fully air-gapped
// deployment models

Three places agents can live

Same agents, same governance — the difference is where the data and the model weights physically sit.

// the data boundary

The data plane never crosses the line

The trap with most "enterprise AI" is that the clever part — the model, the embeddings, the retrieval — lives on someone else's infrastructure, and your documents go to it. We invert that. The data plane runs where your data already lives.

In a hybrid deployment, the only thing that can optionally leave is a thin control plane: anonymized telemetry, version pins, and health signals. Prompts, documents, embeddings, and outputs stay inside your network, and egress for the data path is denied at the firewall, not by policy alone.

  • Inference & embeddings hosted locally
  • Control plane is opt-in and data-free
  • Egress denied at the network layer
  • Per-tenant key management you hold
// how we deploy

From your racks to running agents

A measured rollout that keeps your security team in the loop at every gate.

01

Map

We inventory your data classes, network zones, and compliance obligations, then draw the exact boundary the agents must respect.

02

Size

We benchmark candidate open-weight and licensed models against your workloads to right-size hardware — CPU, GPU, or hybrid burst.

03

Harden

We deploy into your environment, lock down egress, wire approval gates, and turn on full action logging and lineage.

04

Operate

We monitor cost, latency, and quality, expand the agent fleet, and keep evidence current for your auditors.

Managed SaaS AI vs. on-prem & hybrid

Why teams with regulated data choose to keep the model close.

Managed SaaS AIOn-prem / hybrid with Automatic.co
Where data livesVendor cloudYour hardware or your VPC
InferenceOff your networkInside your perimeter
EgressImplicit and broadDenied at the firewall by default
Model choiceVendor's rosterOpen-weight or licensed, your call
Audit evidenceTrust the SOC reportYour own logs and data-flow maps

Frequently asked questions

What does "hybrid" actually mean here?

Sensitive data, retrieval, and inference stay on your hardware; only non-sensitive control-plane traffic — health checks, anonymized metrics, version metadata — can optionally reach a managed layer. You decide where the line sits, and the data plane never crosses it.

Do we need GPUs, or can agents run on existing servers?

Both work. Many internal workflows run well on quantized open-weight models on CPU or modest GPUs you already own. For heavier reasoning we right-size on-prem GPU nodes, and a hybrid pattern can burst non-sensitive work to a VPC you control.

How do you prove data never left our perimeter?

Network egress is locked down at deploy time, every agent action is logged with full lineage, and we provide architecture diagrams, data-flow maps, and audit-ready evidence your security and compliance teams can hand to assessors.

Can a hybrid deployment later become fully air-gapped?

Yes. We architect for that path from day one — the same agents, models, and retrieval stack run with the managed control plane removed, so tightening from hybrid to on-prem or air-gapped is a configuration change, not a rebuild.

Bring your perimeter. We'll bring the agents.

One working session to map your data boundary and the on-prem or hybrid architecture that respects it.