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We build AI systems that handle business workflows while keeping people in control of key decisions.

Cloudcor Intelligence takes one workflow your team repeats every week and turns it into a working system: agents do the legwork, you approve the decisions, everything gets logged.

Start a conversation See a system running →
A team working alongside agent dashboards in a modern office
costfeed.coLive agent-assisted price intelligence
Lobi EcoAgent-managed Amazon operations
Trading systemLayered controls for risk and execution
What we do

One workflow at a time, done properly.

Most AI projects fail the same way: someone builds an impressive demo, it never connects to how work actually happens, and six weeks later nobody's using it.

We start smaller. Pick the workflow that eats the most of your week: quoting, listings, reporting, bid prep, whatever it is. We map how it actually moves: who touches it, where it stalls, which decisions genuinely need a human. Then we build a system around that map. Agents handle the repetitive middle. The judgment calls come to you as an approval, usually a Discord message you can answer from your phone.

You end up with something your team runs on Monday morning. The transformation deck can stay closed.

See how it works Read case studies →
A cross-functional team at a whiteboard mapping the nodes of an operating workflow.
In practiceA live approval gate: the system proposes, the operator decides.
How it works

How an engagement runs.

Three stages. The first is a workshop that gives you a useful map before any build begins.

01
Stage 1

Map it

Before writing any code, we sit with whoever actually does the work and map the process: inputs, hand-offs, decisions, failure points. You get the map either way. It is useful even if we stop here.

02
Stage 2

Build the loop

We build a first working version wired into your tools, with approval points where risk lives. It goes into use immediately, on live work, so we find out fast what is wrong with it.

03
Stage 3

Run and tighten

Live systems drift. We watch the logs, tune the quality, tighten oversight where it is loose and remove it where it has proved unnecessary. When the system is stable, we look at the next workflow.

See how Cloudcor Intelligence works
A principle

Autonomy has to be earned.

Every step in a system gets an autonomy level matched to its risk. New systems start conservative. As a step proves itself in the logs, it earns more rope.

Read the methodology
Human checkingMatched to risk
High · 1
Recommend
Agent proposes; a human chooses every time.
Medium · 2
Approve
Operator approves; agent then executes.
Low · 3
Act & report
Acts within bounds; reports outcomes for review.
High-risk steps never run unsupervised. Everything else earns its autonomy over time, and every action at every level is logged.
Systems we run

Systems we run in public.

The best evidence for this way of working is that Cloudcor runs its own operations on it. These are live systems, warts included.

All case studies →
Agent-assisted digital products

costfeed.co

A live UK price-tracking platform operated as an agent-assisted system. Agents support the data pipelines, reporting, and site operations, while decisions go to a human operator.

Public · costfeed.co
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Agent-assisted e-commerce operations

Lobi Eco

An Amazon FBA brand managed end to end by a multi-agent system: listings, content, creative, and ads, with every consequential change passing through an approval channel.

Cloudcor operation · Amazon FBA
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Governed autonomy

Trading system governance

A domain where the system is explicitly forbidden from acting alone. Layered risk gates decide what it may recommend, what it may do, and what it must never touch.

Build log · Governed autonomy
Read case study →

Each system starts with a defined workflow, clear authority, and a record of what happened.

First engagement

Start with one workflow.

The Agent Workflow Sprint takes one high-value workflow from map to working pilot. Fixed scope, fixed price, and a deliverable you keep even if the engagement ends there: the workflow map, the operating design, and a running system.

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Insights

What we are learning from systems in use.

Read the blog →
E-commerce OperationsMay 2026

How a Sustainability Store Stopped Drowning in Amazon Admin

Read article →
Governed AutonomyMay 2026

The Trader and the Engineer

Read article →
Digital ProductsMay 2026

The Three Stages of a Data Business

Read article →
Take the next step

Got a workflow that's outgrown the way you run it?

Tell us what it is. The first conversation is free, and you'll get an honest answer on whether it's a good fit for this approach. Plenty of workflows aren't.

Start a conversation Read case studies →