Revefi extends its AI DBA to autonomously optimize Databricks ecosystem. June 16, 2026 San Francisco, CA, June 16, 2026. Revefi today extended its AI DBA to Databricks, bringing the agentic teammate that autonomously manages, optimizes, and operates cloud data platforms to the Databricks ecosystem. The announcement coincides with Databricks Data + AI Summit 2026 in San Francisco, June 16 to 18, where Revefi will be exhibiting at Booth 113 and demonstrating the AI DBA live. As Databricks deployments scale across jobs, pipelines, all-purpose clusters, and SQL warehouses, the operational burden on data teams scales with them. Engineers and platform owners spend most of their time on repetitive, high-toil work: tuning Spark jobs, chasing runaway DBU consumption, right-sizing and consolidating clusters, fixing out-of-memory failures and skewed joins, and resolving production incidents. Hiring a skilled Databricks administrator is expensive and slow. Existing tools can surface cost dashboards but rarely act on them, while the platform itself keeps getting more complex to operate. The Revefi AI DBA closes that gap by combining detection, investigation, and autonomous action in a single agentic teammate. "The best AI embodies the human, not the other way around," said Sanjay Agrawal, Co-Founder and CEO of Revefi. "The Revefi AI DBA is built to work the way a great Databricks administrator works: task-oriented, transparent, and accountable. It runs controlled experiments before it changes anything, asks for approval when needed, assigns tasks to teammates, and keeps improving the platform around the clock. Customers can hire it the way they would hire a person, and it gives their team back the hours they spend on reactive operational work." What the Revefi AI DBA for Databricks Does The Revefi AI DBA gives a human element to agentic AI: an expert Databricks administrator working autonomously around the clock across the Databricks ecosystem, within enterprise process guidelines. Customers assign it work from Slack, Jira, or directly in the Revefi product. It executes, raises pull requests, opens tickets, tracks attribution, reports progress, and loops the team in when needed. The AI DBA handles: * Performance. Job and Spark optimization through controlled experiments, slow-run investigation, and root-cause analysis of failures, skewed joins, high shuffle volume, and out-of-memory errors. * Cost and FinOps. Continuous DBU and spend monitoring with autonomous savings actions. Cluster right-sizing, autoscaling tuning, idle and over-provisioned cluster reclamation, and tradeoffs across job clusters, all-purpose clusters, and serverless. Cost is attributed by job, cluster, user, and Databricks product category (SQL, jobs, all-purpose clusters, and predictive optimization) for chargebacks and showbacks. * Operations. Cluster and configuration management, job consolidation, removal of redundant jobs, and continuous tuning across workspaces. * Governance. User and role management, access reviews, and table-level usage auditing that attributes compute cost to individual users. * Agentic workflow. Finds and creates work for itself to keep improving the platform. Asks for approval from team members as needed. Assigns work to others. Accepts work from others via Slack, Jira, or in-product chat. * Organizational memory. Remembers every action taken across the customer's organization, what worked and what did not, and personalizes recommendations. The AI DBA is powered by RADEN, Revefi's underlying agent. Unlike platform-native agents, Revefi is aligned with the customer's goal of reducing cloud data spend; it carries persistent organizational memory across actions; and it operates across multiple data platforms, viz., Databricks, Snowflake, Google BigQuery, and more rather than inside a single vendor's walled garden. Availability The Revefi AI DBA for Databricks is generally available today and is included in the Revefi enterprise package at no additional cost. Customers can get started in five minutes with a zero-touch, read-only integration. To request access or a live demo, visit revefi.com/databricks. Databricks Data + AI Summit attendees can meet Revefi at Booth 113, June 16 to 18 at Moscone Center, for live demos of the AI DBA and conversations with the founding team. Trusted by Leading Enterprises Revefi is trusted by F500 and other leading enterprises such as AMD, Verisk, Stanley Black & Decker, Docker, Ingersoll Rand, Help At Home and Cribl. About Revefi Revefi is the creator of RADEN, an AI agent designed to help enterprises optimize cost, data operations, data observability, AI observability, and database administration across cloud data platforms and LLMs. Founded in 2021 by data experts and ThoughtSpot co-founders Sanjay Agrawal and Shashank Gupta, Revefi's AI and ML-powered platform automates complex data and AI use cases, delivering up to 60 percent reduction in data spend, 10x improvement in operational efficiency, and results in as few as five minutes. Revefi is a 2025 Gartner Cool Vendor in Data Management. Revefi is recognized as one of "The Companies That Matter Most in Data" in the DBTA 100 2026 list. Media Contact Adopt the AI Agent for Data Cost Optimization

Revefi has launched FinOps, Observability and Token Economics for AI to govern cost, quality and reliability across data, AI and agents. The announcement was made at FinOps X 2026 in San Diego. The platform provides real-time attribution and control of AI spending across providers including OpenAI, Anthropic, Google Gemini and Vertex AI. Revefi caught one Fortune 500 enterprise user incurring $76,000 in unexpected token spend within minutes. The company reports token economics through four lenses: by outcome, by department, wasted and optimised. Founded in 2021 by ThoughtSpot co-founders Sanjay Agrawal and Shashank Gupta, Revefi already helps customers cut cloud data and Snowflake warehouse costs by 30-60%. The company is a 2025 Gartner Cool Vendor and FinOps Foundation member.

Revefi launches FinOps, Observability and Token Economics for AI. SAN DIEGO, June 8, 2026 Revefi today announced general availability of FinOps, Observability and Token Economics for AI to govern cost, quality, and reliability across Data, AI, and Agents. The announcement coincides with FinOps X 2026, in San Diego, June 8 to 10, where Revefi will be exhibiting. On the AI layer, a single user in a Fortune 500 enterprise incurred a $76,000 unexpected token spend for a single AI use case. Revefi caught the above spend for this customer within minutes, and they immediately stopped the unplanned dollar burn. "Today as enterprises are pushing everyone to use AI across the board, we see AI Agents burning billions of tokens within minutes, real risk of running out of annual budget within weeks or even days. Your AI just lit both your AI and your data budget on fire," said Sanjay Agrawal, CEO and co-founder of Revefi. "The model was the easy part, knowing what it cost, whether it worked, and if it was even worth it, is the hard part. That's Token Economics: every token, seen, attributed, and under your control. Because you can't adopt AI safely at scale if you can't measure continuously & can't attribute ROI." Revefi's Token Economics gives enterprises a single, unified layer to see, attribute, and control the true cost of AI. As organizations push LLMs and AI agents into production, the spend sprawl across providers, models, agents, and users is increasing at an unprecedented rate with no way to trace what happened, where it went wrong, or what it cost. Revefi closes that gap: full user-to-agent-to-model attribution, real-time observability, prompt optimization, and automated ROI on every AI action, across OpenAI, Anthropic, Google Gemini, and Vertex AI. The result is safe AI adoption built on the three things that matter most - spend, trust, and control with value in as little as five minutes and zero-touch, read-only setup. Revefi reports Token Economics through four lenses that tie spend to value and ROI instead of raw consumption: By Outcome, By Department, Wasted and Optimized. Revefi attributes spend across the full path a request travels. It starts with the user who issues the request, through per-user cost attribution, outlier detection, prompt analysis and tracing, automatically alerts if it goes in the wrong direction, and triggers workflows for model selection, prompt analysis to balance performance and spend. Proven at the data layer, now governing the full chain Revefi customers have already cut cloud data and Snowflake warehouse costs between 30-70%. Today the platform is running tens of millions of automated monitors for data freshness, quality, spend increases, schema changes, and query performance for enterprise customers. This is the data-layer foundation that trusted Token Economics depends on. About Revefi Revefi is the creator of RADEN, an AI agent designed to help enterprises optimize cost, data operations, data observability, AI observability, and database administration across cloud data platforms, LLMs and Agents. Founded in 2021 by data experts and ThoughtSpot co-founders Sanjay Agrawal and Shashank Gupta, Revefi's AI and ML-powered platform automates complex data and AI use cases, delivering up to 60 percent reduction in data spend, 10x improvement in operational efficiency, and results in as few as five minutes. Media contact: Adopt the AI Agent for Data Cost Optimization