Retail Connected Intelligence
Assortment & Pricing Optimization

Infocepts helps retailers stop losing revenue to mispriced products, misallocated inventory, and disconnected merchandising decisions. Infocepts Retail Connected Intelligence unifies assortment, pricing, supply chain, and store execution data – creating a single, trusted decision layer across every channel and format.

Proof Points

500K+

SKUs supported without accuracy loss

Daily

Pricing and assortment recommendations

Margin

Improvement at scale through fewer markdowns

Unity

Catalog governance across every decision

Problems Retail Connected Intelligence Solves

Retailers lose revenue every day to decisions made on stale data, siloed systems, and gut feel. Infocepts has seen this pattern across global retail and CPG clients – and built Retail Connected Intelligence specifically to solve it.

Mispriced Products at Scale

Pricing teams react to competitor moves weeks late. Markdowns happen because nobody saw the demand signal in time. Margin walks out the door every day.

Misallocated Inventory Across Stores

Stock sits where demand is not. Stores that need product cannot get it; stores that do not are forced into markdowns. The merchandising plan and reality drift apart.

Disconnected Merchandising Decisions

Assortment, pricing, supply chain, and store execution data live in separate systems. Every merchandising decision relies on a partial picture and a manual reconciliation.

Black-Box Recommendations Nobody Trusts

When merchandising teams cannot explain why a recommendation was made, they override it. Pricing and assortment intelligence that lacks explainability gets ignored.

Retail Connected Intelligence Core Capabilities

Infocepts Retail Connected Intelligence brings together assortment planning, pricing AI, MLflow-governed models, and Unity Catalog governance into a single solution – built for retailers that need accurate, explainable merchandising decisions at scale.

Assortment Planning

Continuous SKU-level assortment recommendations based on sales velocity, demand signals, and store-level performance.

Pricing Recommendations

Daily pricing recommendations that respond to competitor moves, demand shifts, and inventory positions across the network.

Margin Optimization

Identify margin opportunities at SKU, category, and store level – and reduce markdown exposure through earlier intervention.

MLflow-Governed Models

Every model is reproducible, version-controlled, and explainable – so merchandising teams trust and adopt the recommendations.

Unity Catalog Governance

Role-based access, lineage, and consistent data definitions across every merchandising decision and every market.

Omnichannel Scale

Supports stores, ecommerce, marketplaces, and franchise formats – and scales from 5,000 to 500,000+ SKUs without architectural rework.

Outcomes

When merchandising decisions run on one trusted, explainable decision layer, markdowns shrink, margin improves, and merchandising teams stop second-guessing the data.

Fewer Markdowns

Earlier intervention on slow-moving SKUs reduces markdown exposure across the catalog and across channels.

Higher Margin at Scale

Pricing and assortment recommendations grounded in real demand signals improve margin without sacrificing volume.

Faster Merchandising Decisions

Daily recommendations replace monthly batch cycles. Teams act on current signals, not last quarter's snapshot.

Trusted, Auditable Decisions

MLflow and Unity Catalog give every recommendation a clear lineage - so merchandising, finance, and audit can stand behind the numbers.

Personas / Departments

Chief Merchandising Officer

Wants merchandising decisions made on one trusted view - and explainable enough that category teams adopt rather than override the recommendations.

VP Assortment Planning

Wants SKU-level assortment decisions grounded in sales velocity and store-level demand - not gut feel or last year's plan.

Retail Connected Intelligence Personas Departments
VP Pricing

Needs pricing that responds to competitor moves and demand signals in real time, not on a weekly batch cycle.

CFO / VP Finance

Wants margin improvement that can be defended with data - and audit-ready governance behind every pricing and assortment decision.

Integrations & Deployment

Integrations / Data Sources
  • POS, ecommerce, and marketplace transaction data
  • Competitor pricing feeds and external demand signals
  • ERP, merchandising, and supply chain systems
  • Promotional calendars and store execution data
  • Databricks with MLflow and Unity Catalog
  • Existing pricing, assortment, and planning applications
Deployment: Cloud-native on Databricks. First production category typically live in 10–14 weeks; additional categories roll on faster as the foundation is reused.
Enterprise-Grade Security & Compliance
  • All data stays within your Databricks environment
  • Role-based access scoped by category, format, and market
  • Unity Catalog governance for lineage and definitions
  • Full model lineage and version control through MLflow
  • Audit logs for every recommendation and decision
  • Compliance with enterprise security standards

Partner Ecosystem

Infocepts Retail Connected Intelligence is built and integrates with the broader ecosystem of merchandising, pricing, and supply chain software partners – so deployment fits within your existing retail technology landscape, not around it.

Resources

Explore insights on assortment optimization, retail pricing AI, and merchandising analytics for retail and CPG organizations.

FAQs

Infocepts Retail Connected Intelligence is an assortment and pricing optimization solution built on Databricks. It unifies assortment, pricing, supply chain, and store execution data into a single decision layer – and uses MLflow-governed models to surface explainable, daily recommendations that help merchandising teams reduce markdowns, improve margin, and respond faster across every channel and format.

Infocepts Retail Connected Intelligence learns continuously from sales velocity, competitor pricing, and demand signals, and surfaces SKU-level pricing and assortment recommendations daily. By intervening earlier on slow-moving SKUs and responding faster to competitor moves, retailers reduce markdown exposure and improve margin at scale – typically without sacrificing volume.

Infocepts Retail Connected Intelligence is designed for Chief Merchandising Officers, VPs of Pricing, VPs of Assortment Planning, and CFOs who own merchandising outcomes. It serves retailers and CPG brands managing anywhere from 5,000 to 500,000+ SKUs across stores, ecommerce, marketplaces, and franchise formats.

Every recommendation produced by Infocepts Retail Connected Intelligence is backed by MLflow-governed models with full lineage. Merchandising teams see the drivers – sales velocity, competitor pricing, demand signals – behind every suggested price change or assortment move. This is why category teams adopt the recommendations rather than override them.

Yes. Infocepts Retail Connected Intelligence is built on Databricks specifically to scale across large catalogs – from 5,000 SKUs to 500,000+ – without compromising accuracy or explainability. The same decision layer serves stores, ecommerce, marketplaces, and franchise formats.

Infocepts Retail Connected Intelligence typically goes live for the first production category in 10 to 14 weeks. Additional categories and markets roll on faster as the Databricks data foundation is reused – most clients onboard new categories in 4 to 6 weeks.

Infocepts retail solutions are built on the Databricks Data Intelligence Platform because it provides the unified data, ML, and governance foundation these solutions require — Unity Catalog for lineage and access control, MLflow for reproducible model lifecycle, and horizontal compute scaling across large SKU catalogs. Infocepts is a Databricks Silver Partner with Brickbuilder Specializations in Retail, Consumer Goods & Travel — the partnership is grounded in production delivery, not just certification.

See Infocepts Retail Connected Intelligence live at Databricks Data + AI Summit 2026

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