Databricks

Databricks is the Data and AI company, helping organizations build and scale data and AI apps, analytics and agents.

[Databricks @databricks]

Getting a prototype working is one thing. Getting it ready for production is where things get complicated.

This guide gives you practical examples, code snippets, and repeatable patterns to help you move faster.

Inside:
• Turn notebooks and prototypes into real applications
• Serve analytical data and application state through a transactional layer
• Build secure, governed apps without custom infrastructure
• Deploy and operate apps with production-ready patterns

Download the guide 📕: https://t.co/7HQyVVcP59

[Databricks @databricks]

Your data. Your context. Real outcomes.

Attend #DataAIWorldTour 2026 to learn how organizations are grounding AI in enterprise data and business context.

Hear the latest product announcements and customer insights, join technical breakouts, and explore practical ways to build and run AI apps, agents and analytics at scale.

Find a city near you: https://t.co/Xh9fSheUWQ

[Databricks @databricks]

GLM 5.3 is available as a day 0 release on Databricks!

GLM 5.3 is the smartest open-weight model available today and joins GLM 5.3 Flash and 30+ open-source and frontier models available natively on Databricks.

We host GLM 5.3 on secure GPUs owned by Databricks so you can use the most intelligent models with your most secure data.

With Unity Gateway, you can connect GLM 5.3 to your coding agents and get smart routing, centralized cost controls, and observability in a single pane of glass.

https://t.co/QhgYtiReY1

[Databricks @databricks]

More AI tools usually means more questions: who’s using what, what’s it costing, and is it actually working well?

@matei_zaharia and @kuhlenhuth show how Unity Gateway helps teams see and control AI usage across models, agents, harnesses, and workflows.

They also cover how Omnigent lets builders combine and share the coding agents and SDKs they already use, while leaders keep governance, cost, and quality in check.

Watch now: https://t.co/VVk8yxxpw8

[Databricks @databricks]

🔜 We’re heading to #VLDB2026 next week as a Gold Sponsor!

Databricks Co-Founder and Chief Architect @rxin will open the conference with a keynote on the “third golden age” of database engineering, including Lakebase and LTAP.

Our engineering and research teams will also be sharing work on:

- Lakebase and serverless Postgres
- Spark Structured Streaming
- Automatic Lakehouse optimization
- History-based query optimization
- Incremental materialized view maintenance

Stop by the Databricks booth to meet the team, talk through the papers, and see what we’re building for the agentic era.

https://t.co/4SU8NroiOf

[Ivan Zhou @ivanzhouyq]

We are very excited about GLM 5.3 Flash, the latest frontier model in the efficient tier:
- On OfficeQA Pro and Pro V2, GLM 5.3 Flash outperforms DeepSeek V4 Flash 0731 and GPT 5.6 Luna. We are especially impressed to see it push out the quality-cost pareto frontier for both benchmarks.
- We also evaluated its new vision capabilities on an internal enterprise document parsing benchmark. It delivers strong performance approaching Gemini 3.6 Flash, with solid results on the structured documents and tables.

You can try GLM 5.3 Flash on the @databricks serving platform today!

[Databricks @databricks]

.@Zai_org's latest open-weight model, GLM 5.3 Flash, is now available on Databricks!

GLM 5.3 Flash joins 30+ open-source and frontier models on Databricks. On Databricks’ OfficeQA Pro v2 benchmark, it delivers 10% higher quality than GLM-5.2 at just one-tenth the cost, pushing out the quality-cost-pareto frontier. With new multimodal support, it can now read figures and verify web pages at coding.

Run GLM 5.3 Flash where your data already lives — governed, secure, and ready for custom AI apps and agents. Control access, spend, and observability across all your AI with Unity Gateway.

https://t.co/QhgYtiReY1

[Databricks @databricks]

Chart-JSON enrichment will power Genie One to answer questions over PDFs for databricks customers. It will also be available in ai_parse_document soon. Pair it with ai_prep_search to build agentic retrieval systems that actually get the numbers right.

https://t.co/2nuA9qdZ0e

[Databricks @databricks]

We asked a frontier agent to count the local maxima on a chart. It looked at the image, thought for 50 seconds, and got it wrong: 17 instead of 18.

Then we gave Databricks Genie the same chart, but first extracted its values into structured JSON with ai_parse_document. Genie got the right answer.

[Databricks @databricks]

We tested a fix: parse charts into structured JSON at ingestion, index it with ai_prep_search, and let a lightweight 300M-parameter text embedding model do the retrieval. Across two chart-heavy benchmarks, this approach beat four multimodal embedding models up to 10x its size.

[Databricks @databricks]

Databricks Co-Founder and CEO @alighodsi has been named to the 2026 TIME100 AI list!

TIME highlights Ali in their AI leaders category saying, “as AI agents change how organizations work, Databricks is giving those agents access to secure, governed enterprise data on which to operate."

Congratulations to Ali and all of this year’s #TIME100AI honorees!

View the full list: https://t.co/ijcwk7Mo8g

[Databricks @databricks]

.@SpaceXAI's latest model, Grok 4.6, is now available on Databricks!

Grok 4.6 sets a new state-of-the-art performance standard with Genie harness on Databricks' OfficeQA Pro v2 benchmark, our flagship benchmark for complex data reasoning tasks on enterprise documents.

Run Grok 4.6 where your data already lives - governed, secure, and ready for custom AI apps and agents built with the data in your Lakehouse. Govern every call, monitor performance, and scale securely across your AI apps with Unity Gateway.

https://t.co/yZ2eYYAqfz

[Neon @neondatabase]

The Neon CLI is moving fast. In the last weeks, we added tooling for agents, Postgres debugging, branch-first workflows, and tons more

Check out what's new: https://t.co/1wAYAUZbQQ

[Databricks @databricks]

[DEMO] Give an AI agent the right context, tools, and guardrails, and it can do a lot more than answer questions.

Watch how to build a store operations agent that pulls from enterprise context and MCP servers, traces behavior in MLflow, turns follow-up work into a recurring weekly task, and stays governed through Unity Gateway.

Built with Agent Bricks, Omnigent, and the OpenAI Agents SDK.
https://t.co/VKSQ3rTUuG

[Omnigent @omnigent_ai]

On Tuesday, Sept 1 in SF, we're spending an evening on the layer above the agent. 👇

An agent with a shell, a budget, and write access to your repo is infrastructure. Infrastructure gets policies. Live Omnigent demos.

Three breakout slots, two tracks each. Speakers from @OpenHandsDev, @cursor_ai, @databricks, @OpenAI, @modal, and @ollama.

🗓️ Tues, Sept 1 | 3:30–9:00 PM PT
📍 Terra Gallery, 511 Harrison St, SF
🎟️ https://t.co/G8y3ttKuvY

#AIAgents #AISecurity #Omnigent

[Databricks @databricks]

.@NBCUniversal modernized its data infrastructure to support the speed and scale of a modern media business, where major content launches, awards shows, and live events can drive sudden spikes in analytics demand.

Working with Databricks and EXL, NBCUniversal moved to a unified platform for data engineering, analytics, and ML, with job-specific compute that lets pipelines scale independently instead of competing for pre-reserved capacity.

That move delivered:

- 30% lower overall data infrastructure costs
- 300+ analysts onboarded to Databricks SQL
- Greater flexibility to scale for high-traffic events while reducing the time teams spend managing infrastructure

https://t.co/RVoYb9pi27

[Databricks @databricks]

What if you could connect who owns your infrastructure with what it costs in one query?

With Backstage running on Lakebase, Lakehouse Federation can join live ownership data with system.billing.usage.

That means:
• One SQL query for ownership + cost
• Ephemeral branches show up as their own billing line items
• Engineering teams can see dev costs by branch, developer, and sprint

Explore the one-query FinOps pattern:
https://t.co/com4Vmlf7y

[Neon @neondatabase]

Postgres on S3 is the right design, but even more interesting is making WAL the source of truth. This is how our storage works - we wrote a deep dive, summary on thread: https://t.co/7iHKt2RpNf

[Databricks @databricks]

40,000+ attendees. 20 cities. One global data and AI community.

Starting in September, Data + AI World Tour brings a full day of new ideas, technical learning, and hands-on experiences to a city near you. Hear the latest advancements from Databricks leaders, customers, partners, and technical experts, and explore practical ways to advance your data and AI strategy.

Find your city: https://t.co/Xh9fSheUWQ