Cookbooks · FMCG · Distributor and modern-trade operations
Three agents approved the promotion. The deduction still had no owner.
18 October 2026 · FinAnalytic Editorial · 4 min read
Reference implementation. An illustrative business scenario showing how FinAnalytic would approach the problem. It does not describe a completed client deployment or measured results.
The sales assistant finds the promotional email. The finance agent finds the invoice. The claims assistant finds the retailer’s debit note. All three produce a confident summary. At month-end, the commercial controller still cannot tell whether the deduction should be accepted, challenged or investigated.
Every answer was local to its own task
Imagine an FMCG brand reviewing deductions from a distribution partner. One assistant treats the latest sales email as an approved promotion. Another applies an earlier rate card. A third marks a claim as valid because supporting paperwork exists.
These are illustrative failure modes, not claims about an actual deployment. The issue is that the agents have different evidence boundaries and no shared definition of commercial authority. Their output has moved the reconciliation work onto the controller.
Begin where the commercial agreement becomes a claim
Our Forward Deployed Engineering approach would bring sales operations, finance and distribution stakeholders around a representative set of deductions. We would examine which agreement was effective, which products and periods it covered, and how an exception was approved.
The aim would be to expose the real handoff. Sometimes the missing input is a document; sometimes it is a decision that was never formally recorded. An agent cannot recover approval authority merely by reading a persuasive email.
Resolve the language before resolving the money
A business requirement resolver would unpack “check this deduction” into the counterparty, product scope, relevant dates, agreement and claimed basis. A compact domain ontology would link those concepts without treating similarly named customers or overlapping promotions as interchangeable.
Calculations would run through validated business logic. The language model could help locate and explain evidence, but its narrative would not replace the arithmetic or the designated approval process.
Use a shared case instead of three separate verdicts
For complex cases, a Deep Agents-based harness could support a coordinated investigation that retains the claim, unresolved questions and source references across steps. Specialists could contribute findings within a common case rather than issue independent approvals.
The design would distinguish “evidence located”, “commercial interpretation proposed” and “decision authorised”. New evidence would trigger a controlled review of the relevant finding. The choice of harness would need to earn its place against a simpler workflow in testing; additional agents bring their own cost and coordination burden.
The controller needs a decision packet
The proposed packet would show the deduction under review, the agreement it may relate to, the disputed assumptions and the next responsible owner. An incomplete case should remain incomplete. The system should not accept or reject a claim just to close a queue.
Pilot value would be assessed through reviewer time, aged unresolved deductions, repeat handling, incorrect recommendations and amounts ultimately accepted or recovered. Recovery would count only when realised and attributable. The business case should include the cost of reviews and integrations, alongside any improvement in resolution.
Bring one difficult handoff into focus
FinAnalytic’s Applied AI Solutions work begins with the people, process and evidence behind a business problem. For fmcg · distributor and modern-trade operations, a useful starting point is one recurring exception, an accountable business owner and a measurable baseline.
Research basis & further reading
- LangChain: Deep Agents capabilities and execution model
- Anthropic: effective harnesses for long-running agents
- W3C: ontology concepts and relationships (OWL 2 Primer)
Sources checked 18 October 2026. The operating scenario and proposed design are FinAnalytic’s illustrative interpretation; the references do not validate a FinAnalytic deployment or its results. Cover illustration generated for this article.