Normalized claim
Revenue: 67% increase
Boosted sales productivity by 67%.
Last evidence check: Jun 1, 2026
Fujitsu boosts sales productivity by automating proposal generation
Use case typeAutomotive operations automationUpdated Jun 13, 2026
Fujitsu faced time-consuming and manual sales proposal creation processes, hampering staff productivity and slowing the onboarding of new salespeople. To address these challenges, Fujitsu developed an orchestrated multi-agent AI system using Microsoft Azure AI Agent Service, Azure AI Foundry, and Semantic Kernel, allowing them to automate data gathering and proposal drafting. The new system integrates with Fujitsu's existing workflows and leverages multiple specialized AI agents to dynamically retrieve, synthesize, and tailor sales proposals from dispersed enterprise data sources. As a result, Fujitsu boosted sales team productivity by 67%, enabling staff to focus on customer engagement, faster onboarding for new hires, and delivery of more accurate, data-driven, and current proposals.
- Organization
- Fujitsu
- Industry
- Tech & Comms
- Location
- Japan
- Published
- June 2025
Reported outcomes
+67%
revenueRevenue & growth
Strategic outcomes
New product / capabilityAutomated proposal drafting and data gatheringSpeed & agilityAccelerated proposal turnaroundEmployee experienceFreed sales teams for high-value workCustomer experience & trustDelivered more accurate client proposals
Catalog median for revenue & growth deployments: +40% across 68 reported metrics. Compare benchmarks →
Why do we believe this?Outcome claims, sources, and evidence checks
Why do we believe this deployment?Customer identity, provider attribution, maturity, and source checks
- Customer
- Fujitsu
- Provider
- Microsoft
- Maturity
- Unknown
- Linked source
- Microsoft Customer Stories
No explicit deployment-stage evidence found.
Customer identity supportedSource describes one deploymentMaturity evidence evaluated
Primary read
Use case focus
Showing 2 of 2
- 1Automated Sales Proposal Generation with Multi-Agent AI
- 2AI Orchestration for Real-time Data Synthesis in Sales
- Manually intensive process of generating tailored sales proposals for clients.
- Sales staff spent excessive time identifying, accessing, and consolidating dispersed data sources.
- New employees struggled to learn the product portfolio and locate relevant information quickly.
- Delayed proposal turnaround time hindered sales effectiveness.
- Developed an orchestrated multi-agent system using Azure AI Agent Service and Semantic Kernel.
- Automated proposal drafting and data gathering by dynamically retrieving and synthesizing internal knowledge.
- Seamlessly integrated the AI-driven approach with existing Fujitsu workflows for sales teams.
- Boosted sales productivity by 67%.
- Freed up sales teams to focus on customer engagement and high-value activities.
- Accelerated onboarding and proposal turnaround for new staff.
- Provided more accurate and timely client proposals.
Architecture
At the solution's core, Fujitsu Kozuchi Composite AI uses Semantic Kernel to orchestrate multiple specialized AI agents. Azure AI Agent Service provides foundation PaaS capabilities, allowing the orchestrator AI to coordinate agents that retrieve, synthesize, and assemble proposals from dispersed internal data. Seamless integration is achieved via Azure services into existing workflow systems.
Sources & evidence4
Evidence: Medium70/100Evidence strength
- Customer explicitly identified
- Primary source available
- Quantified outcome available
- Technical implementation details available
- Multiple corroborating sources available
- Recent evidence check available
- Last evidence check: Jun 1, 2026.
Live sourceStill referenced
The case's original source is still reachable.
- Cited source last checked Jun 1, 2026 — ok (0/4 broken).
Measures whether this deployment's public evidence persists — not whether the system is still in production.
Type: Customer StoryPublished: Jun 3, 2025Publisher: Microsoft Customer StoriesEvidence: PrimaryConfidence: High
AI-generated summary. Verify important details with the linked sources before relying on this case.
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