MicrosoftLive sourceProductionEvidence: Medium65/100

o9 streamlines supply chain planning and logistics with AI-driven insights

o9 Solutions, a major enterprise AI software provider, expanded its collaboration with Microsoft to integrate Azure OpenAI Service directly into its Digital Brain platform for supply chain and logistics optimization. By harnessing Azure OpenAI’s advanced large language models including GPT-4, o9 is able to transform both structured and unstructured enterprise data such as emails, documents, and chats into actionable planning intelligence. The integration enables powerful semantic search, natural language querying, and construction of intelligent digital assistant workflows leveraging agent frameworks and retrieval-augmented generation (RAG) approaches. This allows planners to use conversational queries to access real-time operational insights, automate workflows, and streamline decision-making within logistics and supply chain operations. As these AI-driven functions interact with o9’s proprietary Enterprise Knowledge Graph (EKG), they deliver increasingly relevant domain-specific answers, eliminate knowledge silos, and promote hyper-automation in planning processes. This collaboration is already impacting companies in Japan, providing them with real-time tools for smarter supply chain operations.

Organization
o9 Solutions
Industry
Logistics
Location
Japan
Published
April 2024

Reported outcomes

Strategic outcomes

Better decisions & insightImproved real-time decision-makingCustomer experience & trustFaster access to business knowledgeSpeed & agilityAutomated planning workflowsNew product / capabilityEnabled conversational supply chain insights
Why do we believe this deployment?Customer identity, provider attribution, maturity, and source checks
Customer
o9 Solutions
Provider
Microsoft
Maturity
Production
Linked source
o9solutions.com

This allows planners to use conversational queries to access real-time operational insights, automate workflows, and streamline decision-making within logistics and supply chain operations

Customer identity supportedSource describes one deploymentMaturity supported

Primary read

Use case focus

Showing 3 of 5

  • 1Intelligent supply chain planner
  • 2Logistics workflow automation
  • 3Digital assistant for operational decision-making
  • Fragmented supply chain data scattered across multiple systems and documents
  • Difficulty in capturing and leveraging 'tribal knowledge' within organizations
  • Slow and inefficient decision-making due to lack of real-time actionable insights
  • Information silos reducing the effectiveness of supply chain planners
  • High complexity of integrating structured and unstructured data for operational planning
  • Integrated Azure OpenAI Service into o9 Digital Brain for large language model (LLM) capabilities
  • Enabled semantic search and natural language querying across enterprise knowledge sources
  • Implemented digital assistant workflows using agent frameworks powered by Azure OpenAI
  • Utilized Retrieval-Augmented Generation (RAG) for precise information retrieval
  • Automated responses and workflows to inform planners and drive real-time actionable decisions
  • Improved real-time decision-making for supply chain planners
  • Faster access to actionable business knowledge by breaking down data silos
  • Enhanced automation and efficiency in planning workflows
  • Smarter, more relevant responses to planning queries
  • Streamlined supply chain and logistics outcomes for companies in Japan
Architecture

The o9 Digital Brain platform integrates Microsoft Azure OpenAI Service for advanced natural language understanding. LLMs are used to translate user queries into proprietary integrated business planning language (IBPL), leveraging o9’s domain-specific models and Enterprise Knowledge Graph (EKG). Semantically indexed knowledge is accessed via embeddings, and RAG models supplement data-driven query responses. An agent framework utilizing Azure OpenAI’s chat-completion and code-generation features enables digital assistant workflows for hyper-automation in supply chain planning.

Sources & evidence1
Evidence: Medium65/100Evidence strength
  • Customer explicitly identified
  • Deployment status explicitly supported
  • Independent source available
  • Technical implementation details available
  • Recent evidence check available
  • Last evidence check: Jul 22, 2026.
Live sourceStill referenced

The case's original source is still reachable.

  • Cited source last checked Jun 12, 2026 — ok (0/1 broken).

Measures whether this deployment's public evidence persists — not whether the system is still in production.

Type: News ArticlePublished: Apr 16, 2024Publisher: o9solutions.comEvidence: SecondaryConfidence: Low

AI-generated summary. Verify important details with the linked sources before relying on this case.

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