AI Transformation · Pegasus Agentic OS
Six layers that turn signals into decisions and decisions into results, in every function: designed by Pegasus, built inside the tools you already own, and improved every week. Not a platform to license: a framework we build in your stack and hand over.
Six layers, in plain terms
Runs in your tools · You own code, config and data · Reviewed weekly
Written for
CEOs, COOs and CIOs deciding how AI should run the business
The question you came with
Is this a platform we rent, or an operating model we own and can keep?
Part of Enterprise AI Transformation
The operating model. Six layers that show where AI belongs in your business, and in what order to build it.
See the whole programmeSix problems, one in each layer. Find yours, then see how it gets fixed.
AI acts on stale signals, or none at all.
Fixed in Signal 02Nobody trusts the system of record, so everyone keeps their own spreadsheet.
Fixed in Context 03Your best people spend their week on admin.
Fixed in Agents 04Work waits between teams with no owner and no clock.
Fixed in Flow 05The number depends on who you ask.
Fixed in Pulse 06Everything you automated is as good as it will ever be on day one.
Fixed in LoopHow Agentic OS compares with a typical AI agent platform.
| Question | Typical AI agent platform | Pegasus Agentic OS |
|---|---|---|
| Where it runs | On the vendor's platform | Inside your CRM and tools |
| Who owns it | You rent access | You own the code, config and data |
| How it improves | Vendor roadmap, often a black box | Weekly evaluation report you can read |
| Data foundations | Assumed to be clean | Fixed first: Context is a layer |
| Scope | One function or channel | The whole enterprise, signal to result |
| If you part ways | Rebuild from scratch | Keep everything, documented |
Every layer is part of one AI Transformation programme, built through the foundations, build and revenue services. The Loop feeds what we learn back into Signal every week.
One legal workflow through all six layers: a contract request becoming a signed, recorded agreement, today, in week one, and twelve weeks in.
A typical legal workflow. Your own baseline and targets are measured in the AI transformation review.
What each layer does, what we build in it, and which service delivers it.
Sense
Know what needs attention, and why now.
The events that should start work, watched continuously: a new invoice or order, a contract up for renewal, a regulatory change, a risk alert, a customer signal. Each one matched to an owner and a reason.
Unify
One current record for every customer, supplier, contract and employee.
Agents are only as good as the record they read. We connect your systems of record, clean what is there, and keep every field current with its source and permissions.
Execute
AI agents do the busywork. People make the calls.
Matching, first reads, checks, triage and first drafts, done by agents inside your tools in every function, with sources shown and a person approving anything that matters.
Orchestrate
Every request moves to the right owner, on a clock.
Approvals, handoffs and routing wired together so nothing waits in an inbox: by role, risk level and capacity, with response clocks and escalation.
Measure
One number per team that everyone trusts.
Dashboards that reconcile with the systems they come from, built on definitions each function signed off, with every result traced to the workflow and agent that produced it.
Improve
Every system gets sharper every week.
Most automation is as good as it will ever be on launch day. We evaluate every system weekly on your real cases, test changes before release, and review results with your team monthly.
Most clients start with one layer where the leak is biggest, then add the next as the first pays for itself.
No. It is the framework we use to design and build your agentic operating model. Every layer is built inside the tools you already run, such as your ERP, CRM, data warehouse, ticketing and Teams or Slack, so there is nothing new to license.
No. Most teams start with the layer where revenue leaks most, often Context or Flow, and add the others as each one proves itself. The review tells you where to start.
Each system has a test set built from your real cases. Every week we score it, ship tested changes, and send you a short evaluation report. Once a month we review results with your team.
You keep everything: the code, configuration, documentation and data, all in your accounts. Nothing depends on a login only we hold.
Where Pegasus Agentic OS fits your industry, what to read next, and the tools involved.
Start with a fixed-fee AI transformation review. We map your stack against the six layers and tell you where to start, whether or not you hire us.