The Web Search Your Agent Inherited Isn't Good Enough
Summary
Omnigent lets you define an agent once—model, tools, policies, limits—and deploy it across Claude Code, Codex, or the raw API instead of rebuilding it per harness, with model calls routed through Databricks Foundation Model APIs for unified cost tracking and governance. Swapping in Nimble for web search lifted benchmark accuracy from 46% to 71% while cutting search costs in half.
Summary generated by brickster.ai. For the full article, follow the source link above.
More from Databricks Blog
Database for AI Agents: 5 Evaluation Criteria
Lakebase meets all five criteria a production-ready AI agent database needs—branch-per-agent isolation, scale-to-zero compute, hybrid search in a single query, ACID guarantees under concurrency, and a unified platform without ETL lag. Superhuman and easyJet's real-world deployments validate the approach against the continuous, concurrent read/write patterns agent memory demands.
What is AIOps?
AIOps applies AI and machine learning to operational data to detect anomalies, correlate events, pinpoint root causes, and automate incident response. For IT and platform engineering teams, it complements existing observability and DevOps practices, cutting alert fatigue and MTTR while keeping humans in the loop for higher-risk actions.
Modernizing the Trade Lifecycle With Governed Data and AI
Databricks capital markets GTM lead Andrea DeSosa argues that modernizing the trade lifecycle now hinges on governed data and AI rather than more isolated pilots, connecting research, trading, risk, operations, and compliance on a shared foundation. The post recommends starting with high-value decisions—execution quality, exposure analysis, and settlement exceptions—as the entry point for scaling measurable AI workflows.
"Regex for Rows": Simplifying Pattern Detection in SQL with MATCH_RECOGNIZE
MATCH_RECOGNIZE brings regex-style pattern matching to SQL, now in Public Preview, letting you detect sequences and patterns directly in event data. It's built for use cases like fraud detection in financial services, threat detection in cybersecurity, funnel analysis in e-commerce, and anomaly detection in manufacturing and IoT.
How energy teams turn theft detection into governed action with Genie and AI business processes
A Databricks App orchestrates the full lifecycle of energy theft detection—turning ML-flagged suspicious accounts into prioritized investigations, dispatch-ready reports, and tracked recovery workflows, with Lakebase keeping live case state and recovery totals. Genie One, Unity Catalog, Unity Gateway, and Agent Bricks tie this together on one platform, delivering trusted metrics, governed AI usage, and automated executive reporting.
How Databricks’ marketers use data 3x more with Genie, an AI analytics assistant
Databricks built Marge, an AI analytics assistant powered by Genie Agents on a governed Marketing Lakehouse, letting marketers get trusted answers to natural-language questions instead of filing repetitive analytics requests. The result: marketers now use data 3x more in decision-making, adoption tops 85% of the marketing org, and access to insights scaled without adding analytics headcount.