From question to forecast in a single conversation. Business users ask about trends, the agent builds the model, and delivers predictions ready for decisions—no data science team required.
"By the time we clean the data, build the model, and generate the report—the quarter is over and leadership has moved on."
Ask business questions. Get forecasts, trends, and recommendations—without waiting for the data team.
No SQL. No Python. Ask "What will churn look like next quarter?" and get an answer. The agent handles the technical complexity.
Revenue projections, demand forecasts, trend analysis—built and delivered in minutes, not weeks. Run scenarios on the fly.
Not raw data. Not technical reports. Clear visualizations and actionable recommendations your leadership team can use immediately.
Natural language—no SQL required. "What are sales trends for Q3?"
Database sub-agent writes & executes optimized queries across your warehouses.
DS agent analyzes patterns. BQML agent builds predictive models if needed.
Results returned as charts, graphs, and plain-English summaries.
Predict future revenue, customer demand, and resource needs with confidence intervals your finance team can trust.
"What if we raise prices 10%?" Get instant modeling of business scenarios without waiting for analyst bandwidth.
Surface emerging patterns in sales, operations, or customer behavior before they become obvious—or problematic.
Identify at-risk customers, suppliers, or deals before you lose them. Prioritize intervention where it matters most.
Every answer comes with charts, graphs, and visual summaries—ready for your next leadership presentation.
Combine data from your warehouse, CRM, and ERP in a single query. No manual data stitching required.
Multi-database support with MCP Toolkit and ADK Built-in Tools.
Predict quarterly revenue using historical transaction data. Ask "What's our Q4 forecast based on current trends?" and get a BQML-powered prediction with confidence intervals.
Forecast demand spikes and identify inventory imbalances before they become stockouts. Cross-reference ERP data with external signals.
Analyze admission patterns, predict capacity constraints, and optimize resource allocation—all through natural language queries.
The Data Science Agent is production-ready on Google Cloud. See the multi-agent architecture running on your data stack.