L3
OODARIS — the AI planning layer
MFP, OTB, assortment, allocation, markdown, OODIE, and exception triage run on governed, model-agnostic AI infrastructure.
MFP · OTBAssortment · AllocationMarkdown · OODIE
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OODARIS helps merchants, planners, and allocators turn data into action by bringing planning, merchandising, and allocation together in one place, with clear recommendations and guardrails.
From demand forecast through price optimization, one governed loop that keeps planning, merchandising, and execution connected.
Retailer-first operating model
Targets, assortment, allocation, and pricing do not need another dashboard layer. They need connected context, clearer calls, and approvals that move with the work.
Clear recommendations
Guardrails and approvals
Decision-ready data
Learn from results
Our approach
Connect the decisions that drive margin, availability, and sell-through, with guardrails and governance built in.
Explore the questions your technology, AI, and data leaders bring to an Agentic OS evaluation.
Start with the systems, controls, and teams already in place. Frame the evaluation around integration, ownership, and a staged path to adoption.
What to review together
OODARIS adds a governed decision layer above the retail systems you already operate. A canonical context aligns the entities and measures that agents and models need to work together.
Systems of record remain authoritative.
MFP, OTB, assortment, allocation, markdown, OODIE, and exception triage run on governed, model-agnostic AI infrastructure.
Agent-driven canonical mapping normalizes products, locations, calendars, and measures while preserving tenant isolation, lineage, and role-based access.
Keep SAP ECC or S/4HANA, D365, Oracle Retail, NetSuite, Shopify, APTOS, POS, data warehouses, object storage, and custom sources in place.
Core workflows
The platform is grounded in the decisions that shape margin, availability, and sell-through.
Connect signals, assumptions, and business context so the team can act on the forecast, not just inspect it.
Demand Intelligence Agent
Keep targets, OTB, constraints, and versioned decisions connected without living in spreadsheet reconciliation.
Real-time budget reallocation across categories. Prevent over/under buying automatically. Maximize working capital efficiency.
MFP Planner · OTB Controller
Make merchant trade-offs clearer and keep assortment intent visible as execution work moves downstream.
Identify winners and losers in real time. Optimize category breadth versus depth. Increase sales density.
Assortment Curator · Demand Intelligence
Move from exception overload to clearer, explainable actions with stronger store-level context.
Store-specific demand prediction. Automated transfer recommendations. Size curve optimization.
Inventory Optimizer · Supply Coordinator
Review, approve, and track pricing actions with better thresholds, context, and follow-through.
Elasticity-based price optimization. Automated markdown timing. Competitive price monitoring.
Pricing Strategist · Demand Intelligence
The public architecture exposes the core contracts between data, decision services, controls, and execution. The architecture review maps their topology and operating requirements to your environment.
Canonical contracts align products, locations, calendars, and measures. APIs and event paths connect ingestion and controlled writeback while systems of record remain authoritative.
Identity, RBAC, tenant boundaries, encryption, policy gates, and named approval paths govern who can view, recommend, approve, and execute.
Environment separation, availability targets, failure handling, and rollback paths define how decision services are deployed and recovered.
Trace IDs connect source inputs, model and agent execution, approvals, writeback, and outcomes in a replayable decision record.
We will map OODARIS against your current environment and focus the discussion on system boundaries, data movement, controls, deployment, and operating ownership.