From Data to Decision

Stop relying on intuition for important decisions because AI recommendations are difficult to trust, and the expertise required for rigorous analysis is scarce and too expensive.

Fujitsu Causal AI delivers causally grounded recommendations in minutes—identifying the actions that truly drive your KPIs.

3B

Decisions are made annually by managers and executives collectively(*1)

38%

Of C-suite executives would trust AI to make business decisions on their behalf(*2)

$250M

Is spent annually by a typical Fortune 500 company on decision making(*3)

Fujitsu was recognized as a Sample Vendor in the Causal AI category in Gartner^® “Hype Cycle^TM for Artificial Intelligence, 2026" (Haritha Khandabattu et al., 28 August 2026). (*4)

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Would you defend an AI recommendation in the boardroom?

People readily accept AI recommendations for personal decisions.

As decisions become more consequential and affect others, trust quickly erodes unless the reasoning can be explained and defended.

Fujitsu Causal AI brings

data-science-level rigor to every decision.

e.g., commercial activities, pricing, inventory, staffing, process settings, etc.

Here’s how:

Democratizing

Making Fujitsu Causal AI accessible for both business and technical users

Ask questions in natural language
No data science expertise required
From free trial to enterprise deployment

Rigorous

Understand not just what is happening, but why

Identify true business drivers
Quantify cause-and-effect relationships
Explain recommendations with evidence

Actionable

Turn causal understanding into business decisions

Recommend actions, not just insights
Evaluate scenarios under constraints
Move from analysis to action in minutes

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How you want to work

Developer

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SDK

Business user

▼

Agent Mode

Data scientist

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Expert Mode

Agent

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A2A (coming soon)

Get Started In Minutes

From free trial to real deployment

For first time users, join our Causal Bootcamp, including expert review & validation of customer data

Free trial

20 days, 20 decisions

Paid credits

Repeat weekly team decisions

Team subscription

Embed into operating rhythm

Enterprise

Cross-BU governance, private deployment, expert support

Highlighted Causal AI Case Studies

Brew The Ideal Beer
　

Swivel & Knot Co., Ltd.

CHALLENGE

Beer quality has traditionally relied on brewers’ hard-to-replicate tacit expertise of ingredients and brewing conditions.

APPROACH

Linked brewing parameters (aging, fermentation, malting) to sensory quality, yield & cost via a causal graph.

RESULT

Delivered a production-ready brewing specification that Swivel & Knot adopted directly for commercial brewing.
Modeled recipes, processes & sensory data, enabling quantitative trade-offs across quality, yield and cost.

New insights into
genetics-lifestyle relationships

Genequest Inc.

CHALLENGE

Understanding how genes and lifestyle habits jointly shape health outcomes is difficult because they rely on complex interactions that defy simple correlation

APPROACH

Analyzed genetic traits, diet, and lifestyle survey data from ~4,000 people to separate true drivers from mere correlation

RESULT

Found that metabolic genetic traits shape beverage preference and physique genes correlate with eating habits and BMI.
The research will expand to include questionnaire data, health checkup records, and medical information

Press release: October 9, 2025

Advance Health & Productivity
　

Fujitsu Corporate-Wide Project

CHALLENGE

Despite treating employee well-being as a strategic priority, Fujitsu had no reliable way to measure how specific initiatives moved business performance.

APPROACH

Applied causal AI to ~100 integrated health, HR & financial data points across roughly 30,000 employees.

RESULT

Pinpointed job and life satisfaction as leading causal drivers of employee sick leave, ahead of other tested factors.
Launched the commercial “Fujitsu Decision-Making Support Service” built directly on this proof-of-concept.

More Case Studies: Proven Across Industries

From ESG to healthcare, Fujitsu Causal AI helps organizations uncover hidden drivers, make evidence-based decisions, and accelerate innovation.

Collaborator	Domain	Source	Hidden Driver Discovered	Decision Enabled	Key Details
Deloitte Tohmatsu	ESG Management	Press Release, May 29, 2026	Disclosure gaps and competitive differentiation factors	Better ESG strategy	Analyzed ESG disclosure data from 1,000+ listed companies to identify strengths, gaps, and peer differentiation
Kyoto University & Hirosaki University	Population Health	Press Release, March 6, 2025	True causes of sleep disorders	Better health interventions	Combined limited study data with a causal knowledge base built from 20 years of health data and ~3,000 variables
Atmonia	Materials Science	Press Release, April 13, 2022	Catalyst characteristics driving performance	Faster materials discovery	Accelerated catalyst exploration using HPC, simulations, and AI to reduce discovery time
Tokyo Medical and Dental University	Drug Discovery	Press Release, March 7, 2022	Causal mechanisms behind drug resistance	Accelerated drug development	Identified previously unknown mechanisms of cancer drug resistance through large-scale causal analysis