Flaibot for Retail & Consumer Goods

Connect product performance to the evidence behind it.

Flaibot connects products, sales, inventory, suppliers, and commercial records so teams can investigate performance across channels. Compare the same products and periods across systems, then examine the records behind the change.

flaibot / relationship layer
Investigate product performanceIllustrative model
Selected entityProduct

Connect source records around the same product, then follow the relationships and evidence.

IdentityRelationshipsProvenance
One connected context
ProductSalesInventorySuppliersPromotionsShipments

Where Flaibot helps

Follow the question across your systems.

Bring the relevant records, relationships, and definitions into the same investigation.

01

Investigate sales changes

Compare product and channel performance alongside promotions and availability.

02

Examine stock availability

Link inventory, inbound shipments, and order records to investigate gaps.

03

Reconcile product definitions

Connect product variants and identifiers across commercial and operational systems.

Ask across your data

Start with a question that spans systems.

ASK FLAIBOTExample question

Which products lost sales during the promotion period, and what inventory and shipment records are associated with them?

See the connected context

This investigation brings these entities and records into the same context:

ProductSalesInventorySuppliersPromotionsShipments

The relevant definitions, time scope, calculations, and source documents stay attached to the finding. Missing or conflicting evidence remains visible.

Built for review

Keep the evidence attached to the answer.

Keep the entity, time period, and meaning consistent across every step.

  • Consistent contextResolve identities and definitions across your structured data and documents.
  • Traceable evidenceBring calculations and source records into the same investigation.
  • Visible uncertaintyMake missing, conflicting, or unresolved evidence clear to the reviewer.

Your data. Your next question.

Start with one question your systems cannot answer together.

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