About
AI that does real work, built the way enterprises need it.
Pegasus Ark started in 2022 to close the gap between AI that impresses in a demo and AI that runs real work. We find where AI pays back across your enterprise, fix what it depends on, and put governed agents into production in your own stack.
# What Pegasus publishes, so you can check itscope: in writing, before any buildtools: yours first # a new tool only when there is a real gapownership: workflows: you code: your repo admin_access: you, from day onefindings: yours, whether or not you hire uswhere_we_lose: named, so you can rule us out earlysince: 2022Since 2022
Why we started
We started Pegasus in 2022, as AI moved from research papers to every boardroom agenda. The models were improving fast. What was not improving was how often AI made it out of the pilot and into the work.
The reasons were rarely the AI itself. The data underneath was wrong, nobody owned the workflow, legal and risk were asked to approve something at the last minute, and nobody measured whether it paid back.
So we built Pegasus around those reasons: one programme that fixes the foundations, designs the controls with the people who sign them off, and measures every workflow against a baseline. AI Transformation is the whole of what we do, not a service on a list.
How we work
Six habits that shape every engagement, whatever we build.
- 01
Outcomes, not activity
We measure every workflow against a baseline taken before we start. If the number does not move, we say so.
- 02
Written down, not assumed
Scope, definitions, permissions and decisions are written before anything is built, so nobody has to remember what was agreed.
- 03
Yours from day one
Code in your repositories, admin access in your name, data in your systems. You can carry on without us at any point.
- 04
Controls are part of the build
Approvals, audit trails and off switches are designed in with legal, risk and audit, not added at the end.
- 05
Ship weekly, improve continuously
Small releases you can see every week, and agents that are reviewed and tuned after they go live.
- 06
Plain language
No jargon in our findings or proposals. If a board member cannot follow it, we rewrite it.
Are we the right fit?
We would rather tell you early than waste a quarter. Here is how to tell.
We are a good fit if
- You want AI running real work in production, not another pilot
- You can name a business owner for each workflow
- You want legal, risk and audit involved early, not at the end
- You want to own what is built: code, data and access
- You are a mid-market or enterprise organisation working across several functions
- You prefer evidence and a baseline over a vendor's ROI slide
We are probably not the right fit if
- You need a demo for next week's board meeting and nothing after it
- You want a software reseller or a single tool installed
- You cannot give us access to systems or a decision-maker
- You want to skip governance and deal with it later
- You are looking for the lowest hourly rate rather than a result
- Scope
- In writing, before any build
- Tools
- Yours first. A new one only when there is a real gap
- Ownership
- Workflows, code and admin access handed over
- Findings
- Yours, whether or not you hire us
- Where we lose
- Named, so you can rule us out early
Find your path through Pegasus
Six people usually sign off on enterprise AI. Pick yours and we show you what to read, in order, and what to ask us.
AI transformation for the agentic engine era
Start with a fixed-fee AI transformation review. We map your systems, data and teams against the six layers of Pegasus Agentic OS and name the first workflows to hand to agents. You keep the findings whether or not you work with us.