Answering a single question meant manually searching dozens of PDFs. Now, finance teams use an AI assistant to instantly compare clauses.
One of the world's largest mining companies, operating across 19 countries with over 60,000 employees, manages complex financial, tax, and insurance processes that rely heavily on dense, unstructured PDFs.
Answering a single question required searching through dozens of files, manually comparing clauses, and coordinating across multiple teams. Early...
“Databricks is at the center of our AI strategy. With Agent Bricks, we went from experimentation with limited production results to a working initial version of an agent in just days — giving our finance teams entirely new ways to analyze data and make decisions.”
Global mining company and producer of iron ore, pellets, and nickel.
Databricks is a Big Data company that offers a unified analytics platform for data science, engineering, and analytics teams.
Vale's Financial document analysis is part of this use case:
Related implementations across industries and use cases
Engineers lost 30% of their day hunting in isolated data vaults. A unified AI assistant now surfaces technical answers in minutes.
Manual research slowed audit planning. A custom AI assistant now automates data analysis, cutting planning time by 65%.
Models took three years to deploy. Specialized agents now automate claims from PDFs and X-rays, shipping solutions in weeks.
Manual research slowed audit planning. A custom AI assistant now automates data analysis, cutting planning time by 65%.
ATeams manually parsed 8,000-word policy docs. GenAI now structures summaries for validation, cutting contract review time by 80%.
Managers once manually reviewed up to 84 recordings to find information. Now, AI instantly generates summaries and automated scorecards.
Hours of system-hopping to find answers left nothing for analysis. Employees now ask in natural language—instant, structured results.
Manual spot-checks missed duplicates. AI now audits 100% of spend, catching $20k in errors and reclaiming 160 hours for analysis.
Reconciling siloed systems delayed revenue forecasts. Now, teams query AI agents in plain language to pull project data in seconds.
Answering a single question meant manually searching dozens of PDFs. Now, finance teams use an AI assistant to instantly compare clauses.
One of the world's largest mining companies, operating across 19 countries with over 60,000 employees, manages complex financial, tax, and insurance processes that rely heavily on dense, unstructured PDFs.
Answering a single question required searching through dozens of files, manually comparing clauses, and coordinating across multiple teams. Early...
“Databricks is at the center of our AI strategy. With Agent Bricks, we went from experimentation with limited production results to a working initial version of an agent in just days — giving our finance teams entirely new ways to analyze data and make decisions.”
Global mining company and producer of iron ore, pellets, and nickel.
Databricks is a Big Data company that offers a unified analytics platform for data science, engineering, and analytics teams.
Vale's Financial document analysis is part of this use case:
Related implementations across industries and use cases
Engineers lost 30% of their day hunting in isolated data vaults. A unified AI assistant now surfaces technical answers in minutes.
Manual research slowed audit planning. A custom AI assistant now automates data analysis, cutting planning time by 65%.
Models took three years to deploy. Specialized agents now automate claims from PDFs and X-rays, shipping solutions in weeks.
Manual research slowed audit planning. A custom AI assistant now automates data analysis, cutting planning time by 65%.
ATeams manually parsed 8,000-word policy docs. GenAI now structures summaries for validation, cutting contract review time by 80%.
Managers once manually reviewed up to 84 recordings to find information. Now, AI instantly generates summaries and automated scorecards.
Hours of system-hopping to find answers left nothing for analysis. Employees now ask in natural language—instant, structured results.
Manual spot-checks missed duplicates. AI now audits 100% of spend, catching $20k in errors and reclaiming 160 hours for analysis.
Reconciling siloed systems delayed revenue forecasts. Now, teams query AI agents in plain language to pull project data in seconds.