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Granary.

Agentic planning and assortment platform purpose-built for grocery retail · runs smart replenishment, perishable inventory management, and category optimisation across Smart Bazaar + Smart Point in the 11-store Mumbai pilot. The grocery counterpart to Impetus.

Live · Phase 1 · 11-store Mumbai pilot Building · Command Centre · SAP integration · scale-up pipeline Roadmap · STP · CDT · Consensus Forecasting
Phase 1 · live · 28 - Apr - 2026
Forecast scale
48M
rows · 12K SKUs × 4K stores
Pilot stores
11
Mumbai · 10 segments · Food + HPC
Sponsors
Ashwik K · Damodar M
RRL counterparts
Advait Pandit · Ved Antani

What's running. What's being built. What's next.

Running today
Live
  • ML Forecasting on Databricks · 12K SKUs × 4K stores · 48M-row daily refresh · MAPE 41% (from 55%+ baseline · research)
  • Cortex Planning · Assortment Intelligence + MBQ Automation + Range Review · Phase 1 across 11 Mumbai stores · 10 segments (Food + HPC)
  • Top 250 SKU availability checklist · auto-derived · live with store ops
  • Rules Engine · operator-tunable · audit-grade
  • Command Centre · 5 of 37 routes wired · Home/Dashboard · Category Overview · Range Review · Delist Detail · Requests
Building this quarter
Building
  • Command Centre · 5 of 37 screens running on live data · 27 in design · daily updates
  • SAP integration · dev complete across SAP / RDIP / Cortex · IRM whitelisting in test this week
  • ODBC + Databricks · pipeline in finalisation · gates 3K-4K-store scale-up
  • DC Demand Forecasting POC · NCR · 100+ stores · vendor ordering
  • UAT closure · Smart Bazaar + Smart Point validating Cortex delist recommendations
Next horizon
Roadmap
  • Straight-Through Processing · 80–90% routine assortment auto-processed · teams handle exceptions only
  • Customer Decision Trees · shelf arrangement from shopper purchase patterns
  • Consensus Forecasting · maker-checker · seasonal auto-handling · statistical store clustering
  • MBQ + planogramming integration · MDQ values from shelf-aware stock targets
  • Fresh FNV shrinkage tracking · screens-data integration for waste + perishable visibility

Modules running today.

The Granary modules currently running across the 11-store Mumbai pilot. Engine layer (ML Forecasting, Cortex Planning) has been live since 13 - Nov - 2025 with daily updates. The Command Centre is the unified operator surface that consolidates these — five operator screens running on real data today (Home / Category Overview / Range Review / Delist Detail / Requests).

ModuleStatusAnchor outcome
ML Forecasting EngineLiveon Databricks12K SKUs × 4K stores · 48M rows · MAPE 41% (from 55%+ baseline · research)
Cortex Planning WorkbenchLivedaily updatesEnd-to-end Assortment + Inventory Planning · 11-store pilot
Assortment IntelligenceLiveRange Review · Classification matrix CX/CY/CZ · Margin-vs-Volume quadrants · multi-select delist with reason classification
MBQ AutomationLiveArticle-level stock targets per store · replaced state-level manual approach
Top 250 SKU availability checklistLiveAuto-derived top SKUs · shared with store ops for shelf validation
Rules EngineLiveOperator-tunable · audit-grade

What operators see.

Six surfaces from the Command Centre. Five tagged Live (real article + sales data; running across the 11-store pilot). One tagged Building (Baseline Forecast screen is in build; the underlying forecasting engine is Live on Databricks).

Granary Command Centre · Home with Exceptions and DOH Distribution Heatmap
Home · Exceptions + DOH heatmap
Live

Filter strip (Zone / Format / State / City / Store / Segment / Category / Period) · Exception cards (Zero Sales · Negative Inventory · High DOH · High Markdown) · DOH Distribution Heatmap with per-bucket inventory cost. The exception-driven homepage that surfaces what needs operator attention first.

Granary Command Centre · Range Review with Classification Matrix and Margin vs Volume quadrants
Range Review · Classification + Margin-vs-Volume
Live

CX / CY / CZ revenue bands across A / B / C demand stability tiers · Core Stars · Niche Premium · Rationalize · Traffic Drivers quadrants with No-of-SKUs / %-Margin / %-Volume. The decisioning frame for what's strategic, what's reviewable, what to delist.

Granary Command Centre · Category Overview for Drinks with sales trend, gross margin, region-wise performance, overstocked stores
Category Overview · Drinks
Live

Sales Trend YoY · Gross Margin Performance · Region-wise Performance · Overstocked + Understocked stores. Category-manager view with drilldown from format to individual store.

Granary Command Centre · Delist workflow modal with 9 reason codes
Delist workflow · reason classification
Live

9 reason-codes for every delist decision: High inventory holding cost · Product discontinued · Quality/defect · Supplier reliability · End of seasonal lifecycle · Regulatory/compliance · Strategic portfolio optimization · Negative or low profit margin. Audit trail by design.

Granary Command Centre · Baseline Forecast article list view
Baseline Forecast · article-week view
Building

Article-week forecast across the 11-store pilot. Read view live in SIT; full forecasting screens (consensus, override, scenario) in build. The forecasting engine on Databricks is Live and feeding this view.

Granary Command Centre · Home extended dashboard with metric tiles and brand performance
Home · extended dashboard
Live

Total Sales · Markdown · Margin · Active SKUs · Availability · ROS · DOH metric tiles · Overall Performance (CY vs LY) · Brand Performance top-50 · Sales Trend Analysis. The morning-briefing view category managers and store-ops open first.

From data to autonomous action.

Layer 01 · Data / ML
Live

Databricks-native.

Sales · inventory · supplier · loyalty · POS feeds. ML pipelines on Databricks. 48M-row daily refresh.

Layer 02 · 3D Twin
Roadmap

Digital store mirror.

Planogram · shelf · capacity · expiry digitised. Simulate before deploy. Pairs with planogramming tool integration on the roadmap.

Layer 03 · Agentic
Live

Cortex agents.

Assortment Intelligence · Forecasting · Rules Engine · Replenishment. The decisioning brain — daily updates.

Layer 04 · Experience
Building

Command Centre.

Operator surface. Category-manager + buyer + store-ops dashboards. Exception inbox. Decision audit trail. Five operator screens running on live data; 27 more in design.

What you'll hear about next.

Threads in active execution as of 28 - Apr - 2026. Each carries a Building pill — work is well-defined, gating step is named, owner is in the room.

Cortex → SAP integration
Building

SAP API testing · IRM whitelisting closing this week.

Dev complete across SAP · RDIP · Cortex. IRM raised for IP whitelisting; on close, end-to-end Assortment Listing/Delisting flow Cortex → SAP via RDIP enters test. Closes the loop from decision to execution in SAP.

ODBC + Databricks pipeline
Building

Scale-up gate · 11 stores → 3K-4K stores.

Direct ODBC connection to Databricks views in finalisation. The explicit gate to scaling beyond the 11-store pilot — once sorted, real-time data refresh opens scaling to 3,000–4,000 stores.

DC Demand Forecasting POC
Building

NCR · 100+ stores · vendor ordering use case.

Distribution-centre level demand forecasting for vendor ordering. Fresh and dairy forecasting integrated and running on database directly. Validation underway; success extends to additional regions.

UAT closure
Building

Smart Bazaar + Smart Point validation.

Format and Category teams validating Cortex-generated delist recommendations against current manual decisions. Driving toward sign-off; consolidating findings across both formats.

Top 300/1000 SKU availability · expansion
Building

Beyond the 250-SKU checklist.

Expanding the deployed Top-250 availability checklist with automated OOS reason classification, photo evidence, and auto-triggered replenishment actions. Moves the surface from "what's missing" to "what's missing, why, and what we did about it".

Granary's Agentic L4 evolution.

The Command Centre is Granary's Agentic L4 evolution — a 13-module vision spanning the SENSE → PLAN → SOURCE → MOVE → EXECUTE → SELL → OPTIMIZE value chain. Foundation is live with daily updates. Roadmap durations are engineering estimates from the 30 - Apr - 2026 Command Centre Status Report.

ModuleBuiltStatus
01 · Command CentreDashboard + morning briefing · Exception cards · DOH heatmapBuilding
02 · Store IntelligenceRoadmap · ~3 weeks
03 · Assortment PlanningRange Review · Classification matrix · Margin-vs-Volume quadrants · Delist workflowBuilding
04 · Demand ForecastingEngine on Databricks (Live · 12K SKUs × 4K stores · MAPE 41%, research) · Baseline Forecast read viewEngine Live · UI in build
05 · Inventory ManagementDOH + risk APIsBuilding
06 · Supplier ManagementRoadmap · ~2 weeks
07 · Pricing IntelligenceRoadmap · ~3 weeks
08 · Fresh CommandRoadmap · ~2 weeks
09 · Supply Chain OpsRoadmap · ~3 weeks
10 · Store ExecutionRoadmap · ~2 weeks
11 · CalendarRoadmap · part of ~4-week bundle
12 · Capital EfficiencySome inventory metricsBuilding
13 · AdminMock UI pagesBuilding

What L4 will look like.

Two previews from the in-build Command Centre that sketch the agentic loop being built — system surfaces a decision queue, operator picks multiple SKUs in a single action, system books the request with reason and audit trail. SIT-wired today; the broader L4 surface is the upcoming Granary version per the table above.

Granary Command Centre · Requests list with All / Pending / Approved / Rejected tabs
Requests · decision queue
Building

All / Pending / Approved / Rejected tabs across 19 of 19 requests · 7 columns (ID · Time · Requester · Type · Category · Store Count · Article Count · Reason · Status). The intended system-of-record for every assortment decision flowing into Cortex.

Granary Command Centre · Range Review with multi-select bar · 4 of 50 selected
Range Review · multi-select action
Building

"4 of 50 selected · Select All · Delist · Export (4)" floating action bar. Operator works at scale (1,258 pages of articles in this view); each delist booking will carry the reason classification from the modal at §02 surface 4.

The math behind ML Forecasting.

Fynd-authored research paper covering the modelling approach behind Granary's ML Forecasting Engine — LightGBM gradient-boosted trees with quantile regression for prediction intervals, applied to 12K SKUs × 4K stores at 48M-row daily refresh. Authors: Sachith Cheruvatur · Om Wadera · Mayank Jain.

Read inline

Transforming Retail Forecasting with Quantile Regression

Team · see /organisation/