Most staff worked around the data warehouse in Excel; new reports queued behind Qlik specialists. Now executives query KPIs from Teams.
A Mexican insurance company with more than 20,000 sales agents relying on an on-premises analytics stack to support pricing, sales, and executive decision-making.
Most employees couldn't access the data warehouse directly and worked around it in Excel, while a small team of Qlik specialists became a bottleneck...
“Databricks has been a fresh start for ANA Seguros, helping us move faster, work more efficiently and become a more data-driven company.”
Auto insurance company specializing in vehicle protection and roadside assistance.
Databricks is a Big Data company that offers a unified analytics platform for data science, engineering, and analytics teams.
ANA Seguros's Self-service analytics is part of this use case:
Related implementations across industries and use cases
Business users queued requests to specialists for simple questions. Now they ask in plain language—business knowledge drives the work.
Analysts couldn't touch the data—every question funneled through engineers, taking hours or weeks. Now they get answers in seconds.
Pulling reports from scattered dashboards took two days. Now, employees query an AI assistant for instant commercial insights.
Business users queued requests to specialists for simple questions. Now they ask in plain language—business knowledge drives the work.
Analysts couldn't touch the data—every question funneled through engineers, taking hours or weeks. Now they get answers in seconds.
Agents spent up to 6 minutes writing inconsistent notes. Now, AI instantly summarizes 55,000 weekly calls directly into the CRM.
Each incident sent engineers hunting for context from scratch, inconsistently across teams. Edwin AI now delivers it upfront.
Energy market research that took weeks now closes same-day. Staff freed from chasing information to make the calls that matter.
With 99% of records missing metadata, teams sifted unlabeled databases. Now, AI generates column descriptions for data experts to verify.
Most staff worked around the data warehouse in Excel; new reports queued behind Qlik specialists. Now executives query KPIs from Teams.
A Mexican insurance company with more than 20,000 sales agents relying on an on-premises analytics stack to support pricing, sales, and executive decision-making.
Most employees couldn't access the data warehouse directly and worked around it in Excel, while a small team of Qlik specialists became a bottleneck...
“Databricks has been a fresh start for ANA Seguros, helping us move faster, work more efficiently and become a more data-driven company.”
Auto insurance company specializing in vehicle protection and roadside assistance.
Databricks is a Big Data company that offers a unified analytics platform for data science, engineering, and analytics teams.
ANA Seguros's Self-service analytics is part of this use case:
Related implementations across industries and use cases
Business users queued requests to specialists for simple questions. Now they ask in plain language—business knowledge drives the work.
Analysts couldn't touch the data—every question funneled through engineers, taking hours or weeks. Now they get answers in seconds.
Pulling reports from scattered dashboards took two days. Now, employees query an AI assistant for instant commercial insights.
Business users queued requests to specialists for simple questions. Now they ask in plain language—business knowledge drives the work.
Analysts couldn't touch the data—every question funneled through engineers, taking hours or weeks. Now they get answers in seconds.
Agents spent up to 6 minutes writing inconsistent notes. Now, AI instantly summarizes 55,000 weekly calls directly into the CRM.
Each incident sent engineers hunting for context from scratch, inconsistently across teams. Edwin AI now delivers it upfront.
Energy market research that took weeks now closes same-day. Staff freed from chasing information to make the calls that matter.
With 99% of records missing metadata, teams sifted unlabeled databases. Now, AI generates column descriptions for data experts to verify.