AI Assistant for Data Scientists
GAIA helps data scientists manage experiment tracking, automate stakeholder reporting, organize documentation, and reduce operational overhead in data workflows.
Data scientists spend an estimated 45% of their time on data preparation and operational tasks according to Anaconda's State of Data Science report, leaving insufficient time for modeling and analysis. Between managing stakeholder expectations, documenting experiments, coordinating with engineering teams, and presenting findings, the operational burden is substantial. GAIA automates the non-analytical aspects of data science work so you can focus on extracting insights.
Challenges Data Scientists Face Every Day
Stakeholder reporting requires translating technical results into business language repeatedly
Experiment documentation falls behind as the pace of iteration increases
Coordination with engineering teams on deployment and data pipeline issues creates bottlenecks
Research paper tracking and literature reviews are time-intensive but essential
How GAIA Helps Data Scientists
Automated Stakeholder Reports
GAIA compiles experiment results from your documentation in Notion, translates technical findings into business-friendly summaries, and delivers them to stakeholders via Slack or Gmail on your schedule.
Research Organization
GAIA uses Perplexity and DeepWiki to track relevant papers and industry developments. It organizes findings in Notion and alerts you to new research in your focus areas.
Cross-Team Coordination
GAIA monitors Slack and Linear for data pipeline issues, engineering requests, and deployment updates. It ensures you stay connected with engineering teams without constant channel monitoring.
Integrations for Data Scientists
GAIA connects with the tools data scientists already use, creating an intelligent automation layer across your entire workflow.
