Retail teams are rich in data but poor in throughput.
Category, supply chain, and finance leaders are expected to move faster every quarter. Yet a huge share of their capacity disappears into low-value operational work:
That isn’t strategy. It’s glue work.
And it creates a hidden tax that shows up as lost sales, margin leakage, slow execution, and burned-out teams.
Most retailers don’t have a “data problem.” They have a closure problem.
Work gets stuck between systems, teams, and approvals. Exceptions pile up. Outcomes dissolve into “someone will handle it” instead of “it’s closed, written back, and proven.”
This is the Throughput Problem in retail operations.
In most retailers, a single operational decision touches five to ten tools because work is scattered across:
ERP + supplier portals + email + Excel + BI + shared drives + Teams.
Every handoff adds delay. Every context switch adds errors. Every exception creates an open loop.
That is the Integration Tax: the cost of running operations across tools that don’t naturally work together.
It forces people to become the integration layer.
It forces people to become the Human API.
Many retailers tried automation. Most got some wins… and then hit a wall.
Three structural barriers explain why:
So the backlog grows, the easy wins are already taken, and the Human API work stays.
Most AI in enterprise still “helps you work”:
Then a human still has to execute everything across systems.
Retail doesn’t need more suggestions.
Retail needs closed work: executed end-to-end, written back into the right systems, and packaged with proof you can forward.
Retail operations run on a patchwork stack.
Tools were bought at different times, built by different vendors, and connected by… people.
The result isn’t just inefficiency. It’s latency and leakage.
duvo.ai is an AI agent platform built by retail operators that runs operational workflows end-to-end across the patchwork stack:
This is not “automation for automation’s sake.”
Our aim is to be known as:
The system that runs operational work end-to-end with governance, verified write-backs, and forwardable proof.
Retail teams will not accept “trust me” automation.
So we build control in from day one:
Autonomy gives speed.
Governance makes it safe.
You need both.
The value shows up quickly because it returns time and reduces errors immediately.
Examples of what Duvo has already delivered in retail workflows:
That’s not “tasks touched.”
That’s capacity returned, with work closed and written back.
A mission worth building around has to be measurable.
Here’s ours:
Make repetitive, cross-system operational work in retail self-running - and give teams back at least one day per week, with proof.
Not as a consulting project.
Not as a long integration programme.
As a governed AI workforce that closes cases in your systems, every day.