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.
Context-optimized semantic views
A governed map of your retail data model, so business terms resolve to the same fields every time.
Verified query library (36+)
Production-tested queries for the questions retail and CPG teams actually ask, expandable to your own.
Retail math enforcement
Margin, incrementality, baseline, sell-through, and OTB calculated the right way, not approximated.
Super-Agent orchestration
A controlling agent that runs every request through the six-step engine and refuses to guess.
Conversational access
Plain-English questions from the people who own the decision, no SQL and no ticket.
Governance and lineage
One definition per metric, role-based access, and a traceable path from answer back to source.
Measurable Business Impact
Our Retail Intelligence Connected engagements deliver quantified results:
Speed
Self-serve answers in seconds instead of a multi-day IT queue.
Cost
Aanalysts and engineers stop building one-off extracts and get back to real work.
Trust
One governed definition per metric ends the dashboard-versus-dashboard debate.
Risk
Enforced math and validation keep wrong numbers out of executive decisions.
Time to value
A stalled pilot becomes a production analytics platform in about three weeks.
Personas / Departments
Chief Data Officer / VP Data & Analytics
Own a governed intelligence layer that every pillar and tool can build on, instead of another point solution.
Head of Pricing & Revenue Management (Retail & CPG)
Get true incremental promo ROI and margin answers on demand, calculated consistently.

Merchandising, Buying & Planning leaders
Ask range, assortment, sell-through, and open-to-buy questions directly, without waiting on a report.
CFO and Finance & Commercial Analytics
Trust the number in the deck, with a definition and a source behind every figure.
Partner Ecosystem
Infocepts Retail Connected Intelligence is built on Databricks 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.
Case Study
How a Global Media & Events Company Built a 360-Degree, Privacy-Safe View of Its Audience
Read MoreFAQs
What is a retail semantic layer?
It is a governed mapping between everyday business language and the exact fields, joins, and calculations in your data. It lets teams ask questions in plain English and get answers that use correct retail math, kept consistent across every team and tool.
How is this different from a generic text-to-SQL or copilot tool?
Generic tools guess at your data model and your retail math, which produces confident wrong answers and timeouts on complex joins. This framework runs every question through a governed semantic layer, a verified query library, and enforced retail calculations, so the answer is accurate and repeatable.
Do we have to replace our current BI or data platform?
No. The framework layers on top of your existing data platform and BI investment. It governs how questions are answered rather than replacing where your data lives.
How does it prevent wrong or hallucinated numbers?
Every request runs through a six-step orchestration engine that maps language to governed definitions, applies correct retail math, and validates the result before returning it. If a result falls outside expected ranges, it is flagged, not served.
How fast can we go live?
Most teams move from pilot to production in about three weeks, starting with a defined set of metrics and the verified query library, then expanding coverage.
Who uses it day to day?
Merchants, planners, pricing and RGM teams, supply chain leaders, and finance, alongside the data and analytics team that governs the definitions.















