Merchandising and supply back office
Agents that complete multi-step back-office work inside your systems.
What this fixes
Supplier onboarding, price files, claims and invoice matching absorb a large team that spends its day moving data between systems.
Process-level automation where an agent plans, calls tools, reads and writes to enterprise systems and escalates when it is unsure, for reconciliation, onboarding, procurement, claims triage, and the long tail of exceptions that classic RPA scripts could never hold. Each agent has a defined scope, a permission set and an approval gate.
Supplier and item onboarding
Price file ingestion
Claims and deductions
Invoice and receipt matching
Where it earns its place
How we build it
Foundation check
Before any buildWe inspect the systems, the data behind them and the quality of the records this capability will depend on, then write down what has to be fixed before anything is built.
Narrow first release
First releaseOne workflow, one team, real traffic, measured against the baseline we captured before we started.
Controls and evaluation
Runs in parallelGuardrails, approval gates, evaluation sets, logging and the evidence pack your auditor and your regulator will ask for.
Scale and hand over
After sign-offAdditional workflows, sites or languages, then runbooks and training so your team can operate it without us.
What has to be right first
- A documented process with its real exception paths, not the idealised diagram.
- APIs or stable interfaces for every system the agent must touch.
- Service accounts with least-privilege scopes.
- A ground-truth set of completed cases to evaluate against.
Guardrails and KPIs
A human owns every consequential decision
Agents draft, route and execute reversible steps. Anything that moves money, changes a record of consequence or affects a person's rights stops at a named human approver with the reasoning attached.
Every action is logged and replayable
Inputs, retrieved context, model version, output and the human decision are written to an immutable log, so an auditor can reconstruct any single interaction months later.
Data stays where your regulator requires
In-country, in-region or on-premise deployment, with the model portfolio right-sized to the workload instead of routing everything to a frontier endpoint abroad.
Accuracy is monitored, not assumed
A held-out evaluation set runs on every model or prompt change, with drift alerts and a documented rollback path when quality moves.
KPIs it moves
- • Straight-through case completion
- • Cycle time per case
- • Exception and escalation rate
- • Cost per transaction
- • Control breaches, target zero
Integrations
Proof in this sector
Proof in this sector
Anonymised clientsEnterprise reporting and applied AI across merchandising and stores
Global retail chainDemand forecasting and fresh-waste reduction
Grocery retailer in the GulfAssortment and markdown intelligence
Fashion retailer in the Nordics