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OODARIS AI

Autonomous Retail Decisions. Governed. Explainable. Live in 4–8 weeks.

WebsiteAgentic OSResearchCareersLinkedIncontact@oodaris.ai

Retail AI Agents Agentic OS for Retail Canada


👋 What we build

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.


📈 Outcomes we’ve proven

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.


🧠 The OODARIS Agentic OS (at a glance)

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)


🤝 Agents in the loop

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


📚 Research → production

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


🛠 For developers & data teams

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.


🧪 How we build

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


🚀 Work with us

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

📬 Contact

Every day you wait, margin and working‑capital leaks keep compounding.
If you’re serious about autonomous retail, get in touch.

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