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Enterprise OS

An operating system, not another tool stack.

Deploy an autonomous AI-agent network with enterprise-grade security and SLA guarantees. Cut operational costs while retaining full control.

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Paid discovery, fixed scope. No free pilots.

  • For 100+ employee companies
  • Zero risk & compliance
  • 99.99% SLA

One screen for the C-suite: agent fleet, compliance, savings and SLA.

Trusted by

  • Global logistics group · 1,200 staff
  • Retail chain · 640 staff
  • Fintech platform · 300 staff
  • Healthcare network · 2,100 staff
  • Industrial manufacturer · 4,000 staff
Platform

Three pillars of Enterprise OS

Network, control and accountability — not three modules but one loop: agents execute, humans decide, the SLA records the outcome.

Scale without hiring

Agent network delivers an entire department’s volume: orchestrator breaks down goals, specialized agents operate 24/7 in your systems.

Department workload · 0 hires

Zero risk & compliance

All irreversible actions pass human review: isolated permissions, RLS and audit trail record every decision.

100% compliance

Guaranteed uptime

Enterprise SLA with fixed scope, agreed response windows and measurable impact. No surprise outages.

99.99% uptime

Economics

How we save you $100k+ a year.

Modelled on a 100+ person company: ten subscriptions, a support department and manual bridges between systems. One loop removes the duplication, not just the hours.

≈ $100kmodelled saving per year

Illustrative model for a 100+ person company, not a guarantee. Exact numbers are fixed after discovery: your systems, ticket volume and team load.

Before

Today
Tools
10 SaaS subscriptions
Ops headcount
6 people on routine
First response
4 hours
Annual cost
$312k

After

Enterprise OS
Tools
1 Enterprise OS
Ops headcount
2 people on control
First response
under a minute
Annual cost
$212k
Security & compliance

Security is not an add-on. It’s the foundation.

The loop is built around auditability, isolated permissions and zero retention: the agent stays inside the boundaries you set, and a human confirms anything irreversible.

A.R.G.U.S. Threat Detection

A dedicated security loop inspects every network action: anomalies, out-of-scope attempts, suspicious sign-ins. It blocks before execution, not after the incident.

Checks before execution

SOC 2 Type II (in progress)

Access control, logging and incident response are documented for a SOC 2 Type II audit. Status: in progress — we show the control scope, we do not promise a certificate.

Audit in progress

Zero-Retention Data Privacy

Your data is never used to train public models and does not stay with the provider after processing. Storage stays in your perimeter, under your policy.

Never trained on your data

Rollout

Four steps from audit to SLA

Paid discovery fixes the scope, architecture fixes the estimate, the pilot fixes the metric. Then the SLA starts, with agreed response windows.

  1. Week 1

    Discovery & Audit

    One workflow, end to end: systems, ticket volume, bottlenecks, cost of routine. You get an integration map and a success metric.

  2. Weeks 2–3

    Architecture

    We design the agent network, permission boundaries and HITL points. Scope and estimate are fixed before the first line of code.

  3. Weeks 4–6

    Pilot deployment

    One workflow in production on a limited loop. We compare the metric against the baseline and report numbers, not a demo.

  4. Ongoing

    Scale & SLA

    We expand to neighbouring workflows and switch on the 99.99% SLA and a response policy with accountability for the outcome.

Questions

What buyers ask before signing

Will it integrate with our legacy systems?

Yes, via custom API gateways and an integration layer we build during discovery. The agent network runs on top of your systems of record, not instead of them: anything with an API or a database is connected; if it has neither, the gateway runs on your side.

How do you prevent AI hallucinations?

Through our HITL architecture: critical actions are deterministic, every write goes through a verified operation, and irreversible steps require human approval. The model proposes, the control loop executes.

What happens to our data?

It stays in your perimeter or your own cloud account. We do not train on it, and retention is set by your policy — including zero retention at the model provider.

What does it cost?

Paid discovery with a fixed scope, then architecture and SLA priced to the workflow. There are no free pilots: the first step is a paid audit so the numbers are real.

Next step

Bring one workflow.

We will show where the hours go and what the agent network takes over: discovery, architecture and an SLA with fixed scope.

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Discovery · Architecture · SLA