From "What Happened?" to "What Will Happen?"
Summary
Conversational BI now delivers predictive answers in seconds, not days, by fusing Genie for dynamic feature engineering with TabPFN for zero-training prediction, orchestrated by Agent Bricks. This self-assembling pipeline eliminates data science bottlenecks for business users, providing a governed experience backed by Unity Catalog and MLflow.
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More from Databricks Blog
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Evaluating AI Agents Live at the Grounded Reasoning Cup
Stanford's team won the Grounded Reasoning Cup with 63.3% accuracy on OfficeQA Pro V2, a new 120,000-page U.S. Treasury document benchmark, using an end-to-end agent optimization approach combining reusable skills, document-representation fallbacks, and adaptive verification. Across all 11 academic teams, out-of-the-box frontier agents averaged under 30% accuracy, showing that agent performance tuned on one benchmark doesn't reliably generalize to a new corpus.
How Databricks Feature Store serves features with sub-second freshness
Databricks Feature Store now delivers streaming feature updates from Kafka to the online store at 200ms p99 latency, cutting feature staleness from minutes or hours down to milliseconds. The gains come from Spark Real-Time Mode's continuous per-event processing and amortized checkpointing paired with Lakebase's compute-storage separation, which together enable low-latency, high-throughput writes for real-time model inference.
The prototyping tax is killing your AI roadmap
Platform-native agents grounded in business semantics—like Databricks Genie plus Unity Catalog—eliminate the "prototyping tax" of fragmented context and siloed domain knowledge, hitting 77% accuracy versus 56–72% for general coding agents at roughly half the cost. Abacus Insights proved the approach even in regulated settings, cutting new-client onboarding time by about 50% and manual data-mapping effort by 40% inside a HIPAA-grade environment.
