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OODARIS AI is an agentic OS for retailers.
We move merchants, planners, and supply teams off spreadsheet-era MFP / MP&A suites and into a governed network of AI agents that:
- Sense demand across POS, e‑commerce, marketing, and external signals
- Optimize buys, pricing, and inventory across channels and regions
- Orchestrate decisions with explainable guardrails and human‑in‑the‑loop workflows
All of it runs on a Semantic & Canonical Data Fabric that keeps every agent in sync with your real systems.
We ship production systems with audited impact, not toy demos.
- +2–8pp gross margin improvement ranges across audited omnichannel pilots
- 60–75% fewer stockouts on priority SKUs in enterprise rollouts
- 50–200% annual ROI, with 4–8 month payback windows
- 62% fewer manual hours on planning workflows in validated pilots
See the full benchmarks, guarantees, and methodology on our website.
At the core is the OODARIS loop — Observe → Orient → Decide → Act → Reflect → Iterate → Serve — implemented as a governed, multi‑agent system grounded in BDI (Belief‑Desire‑Intention) architecture.
Key building blocks:
-
Retail DNA
Built by former merchants and planners. Agents ship with retail-native concepts, not generic LLM prompts. -
Semantic & Canonical Data Fabric
Maps and matches data from POS, e‑com, ERP, marketing, logistics, and finance into a shared semantic blackboard. -
Agent Cohort & Orchestrator
Specialized agents (demand, price, inventory, finance, procurement, etc.) collaborate over the blackboard. An orchestrator routes work, enforces guardrails, and narrates decisions. -
Governance & Explainability
Coordinator, critic, and storyteller agents audit each other and emit human‑readable rationales for every action.Retail data → Semantic & Canonical Data Fabric → Agent Cohort → Humans-in-the-loop (POS, e‑com, ERP, CRM, etc.) (Demand, Price, Inventory, Finance) (Merchants, Planners, Ops)
We ship a roster of specialized agents that cooperate in real time across the retail lifecycle.
| Domain | Example agents | What they help you do |
|---|---|---|
| Customer & Market Intelligence | Trend Intelligence Scout · Market Insights Analyst · Demand Intelligence | Spot emerging trends, benchmark competitors, and improve demand forecasts. |
| Merchandising & Experience | New Product Catalyst · Assortment Curator · Pricing Strategist · Promotions Director | Launch new items, localize assortments, steer price & promotions with proof. |
| Planning & Finance | MFP Planner · OTB Controller | Synchronize merch & financial plans, protect cash and margin. |
| Supply & Fulfillment | Inventory Optimizer · Replenishment Director · Procurement Navigator | Balance inventory, automate replenishment, and improve sourcing economics. |
📝 Performance ranges and detailed playbooks for each agent are available at
https://oodaris.ai/en/agents
OODARIS is grounded in published research and real deployments.
-
Foundations of Agentic AI for Retail
A book introducing the BDI framework and OODARIS loop for autonomous retail systems. -
Research & publications
Deep dives on:- BDI architecture in retail contexts
- The OODARIS loop methodology
- Multi‑agent coordination patterns
- Demand sensing, inventory optimization, and agentic pricing
👉 Explore the research and links to papers: https://oodaris.ai/en/knowledge
This GitHub organization is where we expose the pieces of our platform that make sense to share publicly:
-
Reference architectures & diagrams
High‑level views of the Agentic OS: data fabric, agent cohort, and governance layer. -
SDKs & integration kits (as they are released)
- Client libraries for integrating with the OODARIS Agentic OS
- Example adapters for common retail systems (POS, ERP, e‑com, marketing)
-
Labs & examples (as they are released)
- Notebooks demonstrating agent behaviours in synthetic retail environments
- Evaluation harnesses for margin, stockout, and working‑capital metrics
If you’re evaluating OODARIS for your retail stack today, reach out and we’ll connect you with a governed pilot environment rather than a toy demo.
We are a senior, calm team shipping production multi‑agent systems for enterprise retailers.
A few principles we hold:
- Golden workflow: Plan → Contracts → Code → Tests → Docs → Rollout. Every change follows this path.
- Typed & observable by default: Strongly‑typed inputs/outputs, structured logs, traces, and dashboards before we ship.
- No heroics: High trust, high ownership, realistic scope. We solve hard problems with focus, not chaos.
Interested in building the Agentic OS for retail with us?
Open roles: https://oodaris.ai/en/careers
Retailers
- Run a governed pilot on your own data
- Validate impact on margin, stockouts, and working capital
- Move from pilot to full rollout in weeks, not years
Partners & platforms
- Explore joint solutions and integrations
- Combine OODARIS agents with your data / SaaS platform
- Co‑develop new agent domains for retail
Researchers & educators
- Collaborate on agentic AI in retail
- Turn BDI + OODARIS frameworks into applied systems
- Bring real‑world case studies into your courses and programs
- 🌐 Website: https://oodaris.ai
- 🧠 Research & publications: https://oodaris.ai/en/knowledge
- 🧑💻 Careers: https://oodaris.ai/en/careers
- 💼 LinkedIn: https://www.linkedin.com/company/oodaris-ai/
- ✉️ Email: contact@oodaris.ai
Every day you wait, margin and working‑capital leaks keep compounding.
If you’re serious about autonomous retail, get in touch.