Real-World Case Studies and Customer Success Stories with H2O Driverless AI

H2O Driverless AI helped G5, Inc. boost lead scoring accuracy to over 95%. G5 used machine learning on AWS to improve real estate marketing. The solution saved $500,000 each year and cut model tuning... time by 80%. Leasing agents now get high-quality leads faster. G5's marketing optimization platform now delivers better insights and higher revenue.
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H2O Driverless AI helped AIMIA cut machine learning model development time in half. AIMIA saw a 700% increase in campaign cost savings and an 11% boost in ROI for customer retention campaigns. The pl...atform improved transparency and trust in AI for AIMIA's SmartJourney methodology. AIMIA can now predict customer churn and deliver new loyalty solutions faster. The solution made predictive marketing more agile and accurate for AIMIA.
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H2O.ai helped Epsilon improve its Abacus data Coop platform with machine learning. Epsilon used H2O.ai to build custom models for over 3,000 brands, boosting direct mail response rates by 3-5%. This ...led to an average of 15,000 more highly relevant customers per campaign. Epsilon's clients saw over $9 million in incremental revenue. The solution allowed Epsilon to better tie advertising costs to revenue and deliver stronger marketing ROI.
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Epsilon used H2O.ai to improve its Abacus data Coop for marketing campaigns. The company helps over 3,000 brands reach the right consumers. By moving to machine learning with H2O.ai, Epsilon saw a 3-...5% increase in direct mail response rates. This led to an average of 15,000 more relevant customers per campaign. Epsilon's clients gained more revenue and better marketing ROI.
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H2O LLM Studio helped AT&T fine-tune a small language model for text-to-SQL tasks. The CDO Office team wanted a tool for non-technical users to get database insights using plain English. They needed ...high accuracy and lower costs. Fine-tuning with H2O LLM Studio cut costs, improved query speed, and matched the performance of larger models. The new solution is nearly free to use, replacing a system that cost two cents per call. AT&T achieved higher customization, accuracy, and faster decision making.
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H2O LLM Studio helped AT&T cut call center costs by 90%. The CDO Office used the platform to fine-tune a small language model for text-to-SQL tasks. This let non-technical users query databases in pl...ain English. The new solution matched large language model performance but at a much lower cost. AT&T now gets faster, more accurate insights for campaign targeting and market growth.
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H2O Driverless AI helped Airvantage improve real-time risk scoring for airtime advances. Before, Airvantage used static business rules that often declined good customers. With H2O Driverless AI, they... trained a new model using real customer data. The solution reduced false negatives and integrated well with their existing systems. Airvantage chose H2O Driverless AI after evaluating over 30 data science platforms.
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AT&T used H2O.ai's Generative AI to improve its call center operations. The company manages 15 million customer calls each year. With H2O.ai, AT&T achieved 90% cost savings and 75% better latency. Su...mmarization became 10 times faster. The solution also scaled 5 times better, helping AT&T serve customers more efficiently.
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H2O Driverless AI helped Visión Banco cut model build time from 6 months to less than a week. The bank used the platform to improve credit risk modeling and customer targeting. As a result, Visión Ba...nco doubled its customer propensity to buy rate. The solution increased accuracy and saved time for the data science team. The bank now plans to expand use of H2O Driverless AI for more predictive analytics projects.
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H2O.ai helped Commonwealth Bank of Australia scale machine learning across the organization. The bank reduced time to prototype new models from weeks to 2 days. H2O.ai's AI Cloud enabled personalized... customer experiences and better cash flow forecasting. The partnership supports real-time offers and energy-saving solutions for customers. CBA gains access to H2O.ai experts and exclusive AI innovation in banking.
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H2O.ai helped Commonwealth Bank of Australia use real-time Generative AI to fight fraud. CBA built a customer engagement engine with thousands of models running over billions of data points. The solu...tion improved service experience and decision-making. CBA saw a 30% reduction in fraud and a 70% reduction in scam losses. Over 900 H2O.ai analysts were trained, supporting more than 16 million customers.
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Driverless AI helped センコーグループホールディングス株式会社 improve warehouse shipment forecasting. The company achieved 87% prediction accuracy, up from 60%. Forecasting periods extended from one week to one month wi...thout losing accuracy. Staff workload dropped by 5%. The solution made workforce planning easier and reduced manual forecasting tasks.
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Driverless AI helped Senko Group Holdings boost shipment volume forecast accuracy from 60% to 87%. The company used AI to plan manpower and reduce logistics staff workload. Staff saw a 5% reduction i...n workload. Accurate forecasts let them allocate workers more efficiently. Driverless AI made predictive modeling easy for non-experts. Senko Group streamlined operations and improved planning with this solution.
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H2O Driverless AI helped Deserve cut model development time from months to weeks. The platform improved explainability, meeting regulatory needs in credit scoring. Deserve used automatic machine lear...ning to deploy new fraud, self-scoring, and underwriting models. The data science team increased productivity and scaled faster with fewer resources. Built-in explainability boosted trust in AI for the regulated credit card industry.
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H2O Driverless AI helped Acordo Certo retire over $10M in consumer debt per month. The platform reduced model development time by 70%. Model accuracy improved to nearly 80%. Acordo Certo expanded par...tnerships with retail and banking firms. The AI solution made debt collection faster and more accurate. The team used machine learning interpretability to build trust with partners.
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H2O Document AI helped UCSF Health automate the processing of 1.4 million annual e-faxes. Before, staff handled each document manually, causing delays and high costs. With H2O Document AI, UCSF saved... over 25,000 hours of access center staff time and 5,000 hours of clinician time. The solution improved workflow automation, reduced manual data entry, and enhanced patient care. UCSF Health now processes documents faster and more efficiently.
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Kaiser Permanente used H2O.ai's machine learning to predict patient deterioration and reduce unplanned ICU transfers. The Advanced Alert Monitoring (AAM) system analyzes electronic records, vital sig...ns, and lab results to warn care teams up to 12 hours before a patient may crash. This early warning helps lower mortality rates and shortens hospital stays. Kaiser processes large volumes of healthcare data with open source tools and real-time analytics. Faster data access and predictive AI improve patient outcomes in intensive care units.
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AES used H2O.ai to transform its energy business. The company wanted to move from fossil fuels to renewable energy and needed digital and AI tools to help. H2O.ai helped AES predict and optimize ener...gy output, predict failures, and optimize load distribution. AES saved $1 million a year by cutting non-essential technician trips. Customers saw 10% fewer power outages.
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Driverless AI helped ArmadaHealth match patients with the right specialists. The platform used natural language processing to analyze patient reviews for sentiment, focusing on treatment outcome, com...munication, and attitude. ArmadaHealth saw increased Net Promoter scores and faster model building. The solution improved patient outcomes and physician satisfaction. ArmadaHealth enhanced customer experience using H2O.ai's automatic machine learning.
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H2O Driverless AI helped Jewelers Mutual improve insurance rates and customer experience. The platform gave them transparency and explainability in machine learning models. Jewelers Mutual used AI to... offer more competitive insurance rates and better protect jewelry stores. During California wildfires, AI insights helped them identify stores needing extra security. The company now plans to use AI for loss prevention and customer journey improvements.
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Driverless AI helped PropertyGuru speed up model development and deployment. The team saved up to 3 months from development to production. They used Driverless AI for image moderation, churn predicti...on, and credit forecasting. The platform enabled faster data exploration, outlier detection, and model iteration. Non-technical teams could also interact with data more easily. PropertyGuru improved agility and innovation in their real estate business.
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H2O's predictive model factory helped Cisco cut model processing time from over a month to just two days. Cisco used H2O's in-memory compute engine and pre-built algorithms to analyze all customer da...ta, not just samples. This improved prediction accuracy for customer buying patterns. The solution enabled Cisco to deploy 60,000 predictive models each quarter, supporting over $3B in revenue. Marketing and sales teams now focus on high-potential opportunities using real-time insights.
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H2O.ai helped AES transform its energy business with AI. AES needed to predict and optimize energy output from renewables, predict failures, and optimize load distribution. The company used H2O.ai to... drive its digital and AI transformation. AES achieved $1 million in annual savings by cutting non-essential technician trips. Customers saw 10% fewer power outages. AES accelerated its move from fossil fuels to renewables with H2O.ai.
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