Data + AI Summit 2026: Day 2: The 9 Keynote Announcements That Complete the Agentic Platform

Data + AI Summit 2026: Day 2: The 9 Keynote Announcements That Complete the Agentic Platform

DAIS 2026 · 18 JUN · SAN FRANCISCO
KEYNOTE DAY 2 · 9 ANNOUNCEMENTS

Day 2 of DAIS 2026 answered the question Day 1 left open: how do we govern all of this together?

If Day 1 expanded the platform into new categories, Day 2 showed how to connect, secure, and democratize them. Omnigent as the agentic meta-harness, LakeWatch as the native SIEM, Genie Code for developers, redesigned AI/BI Dashboards, an expanded Free Edition, and more. Here’s the full recap.

While Day 1 of the Data + AI Summit 2026 laid the foundations (Lakehouse//RT, Agent Bricks, CustomerLake, Open Sharing) Day 2 focused on showing how those pillars connect into a coherent, governed, and accessible stack for every role in the organization.

Nine announcements. From security to user experience, from developer tooling to the free tier of the platform.

The 9 Day 2 Announcements: Quick View

Keynote Day 2 · Databricks Data + AI Summit 2026

Omnigent

OSS meta-harness that governs, shares, and scales agents across any framework

Agentic CDP Explained

Why traditional CDPs are broken and what a truly agentic CDP means

AI Platform Updates

Mosaic AI, ML Engineering, Deep Learning and new agentic capabilities

Unity AI Gateway Ecosystem

Building an open ecosystem for enterprise AI governance

Security & Compliance

New platform-level security and compliance capabilities

Genie Code

AI code assistant for data engineers and scientists inside Databricks

AI/BI Dashboards

Beautiful, expressive dashboards powered by generative AI

Free Edition, What’s Next

Free tier expansion with new capabilities and higher limits

LakeWatch, Agentic SIEM

The modernized SOC: native SIEM on the security lakehouse with AI

1. Omnigent: The Meta-Harness to Govern, Share and Scale Agents

OSS · GAOPEN SOURCE

The question that has gone unanswered in the agentic space for two years: how do you govern, share, and scale agents you’ve already built in Claude Code, Codex, Cursor or any other framework, without rewriting everything from scratch?

Omnigent is Databricks’ answer. It’s the open source meta-harness that sits on top of any existing agent framework and adds three cross-cutting capabilities without requiring changes to the underlying agent:

Govern

Unity Catalog governance over all agents: identities, permissions, lineage and auditing applied automatically

Share

Agent discovery and distribution across teams with a built-in catalog and version control

Scale

Agent execution at Databricks platform scale, with centralized observability and management

The number that puts the problem in context: only 11% of agents in pilot reach production today. Omnigent targets the causes of that 89% that gets stuck, not the model, but the infrastructure around it.

Works across any framework

Claude Code, Codex, Cursor, LangChain, LlamaIndex, Omnigent is a harness that wraps on top without requiring changes to the base agent.

Automatic governance from Unity Catalog

Every agent registered in Omnigent inherits Unity Catalog policies, permissions, ACLs, lineage, and auditing with no extra configuration.

Read full Omnigent blog post →

Official Blog: Introducing Omnigent

2. CustomerLake: Why CustomerLake Is Different

DEEP DIVE

Day 1 introduced CustomerLake as a product. Day 2 was the moment for the deeper explanation: what does it actually mean for a CDP to be agentic? And why are traditional CDPs not enough?

Traditional CDP

  • Data copied into proprietary systems
  • Static, batch-based segmentation
  • Manual activation with rigid pipelines
  • Duplicated governance out of sync

CustomerLake (Agentic CDP)

  • Data stays in the lakehouse, zero duplication
  • Dynamic real-time segments
  • Agents that autonomously trigger next-best-action
  • Unified Unity Catalog governance

An agentic CDP doesn’t just store customer data, it uses it actively to trigger agent actions: real-time recommendations, churn prevention before it happens, individual-level personalization without nightly batches.

Official Blog: What Is an Agentic CDP?

3. AI Platform Updates: Agents, ML Engineering and Deep Learning

MULTIPLE CAPABILITIES

The Databricks AI Platform (Mosaic AI) receives a broad set of improvements in Day 2 covering the full enterprise AI lifecycle: from model training to agent deployment, including fine-tuning and evaluation.

Enhanced agents

New Mosaic AI Agent Framework capabilities: multi-agent orchestration, improved tool execution, automatic behavior evaluation.

ML Engineering

MLflow updated with native support for agent traces, new model registry functions, and simplified deployment to Model Serving.

Deep Learning Platform

Improvements to distributed training, fine-tuning of proprietary LLMs, and access to optimized GPU infrastructure directly from the platform.

Official Blog: What’s New in the AI Platform — DAIS 2026

4. Unity AI Gateway: Building the Open AI Governance Ecosystem

OPEN ECOSYSTEM

Day 1 introduced Unity AI Gateway as a product. Day 2 expanded the vision: Unity AI Gateway isn’t just a centralized control point, it’s the core of an open AI governance ecosystem that connects Databricks with third parties, partners, and market frameworks.

Integration with external providers

OpenAI, Anthropic, AWS Bedrock, Azure OpenAI and all major model providers integrate directly, with the same governance policies applied regardless of provider.

MCP as a first-class citizen

Model Context Protocol servers are governed by the same policies as models, authentication, rate limits, PII redaction, and observability applied to all agentic integration points.

End-to-end observability

Complete traces from user request to model response, with breakdown of latencies, tokens, costs, and routing decisions visible in a centralized dashboard.

Official Blog: Building an Open Ecosystem for AI Governance with Unity AI Gateway

5. Security & Compliance: Platform Protection for the Agentic Era

PLATFORM UPDATES

Autonomous agents create attack surfaces that didn’t exist in the traditional pipeline world. Day 2 dedicated a full block to showing how Databricks has extended its security and compliance capabilities to cover the agentic world.

Non-human identities

Service principals and autonomous agents with their own identities, granular permissions, and managed lifecycle, treated as first-class actors in the security model.

New compliance certifications

Expanded SOC 2, ISO 27001, HIPAA, and financial industry certifications, with extended coverage for AI agent and model workloads.

Agent action auditing

Immutable log of every action taken by autonomous agents: what tool they invoked, what data they accessed, with what result, with configurable retention.

Network isolation for agents

Network isolation policies applicable at the individual agent level, precise control over which external systems each agent can reach.

Official Blog: What’s New in Databricks Security & Compliance — DAIS 2026

6. Genie Code: The Native AI Code Assistant for Databricks

AVAILABLE

Genie isn’t just for business analysts. Genie Code brings conversational AI capabilities to the workflow of data engineers, data scientists, and ML developers, directly inside Databricks notebooks and the IDE.

Context-aware code generation

Suggests and generates PySpark, SQL, and Python code with understanding of table schemas, existing pipelines, and the current notebook context.

AI-assisted debugging

Identifies root causes of errors in pipelines and notebooks, proposes fixes, and explains the problem in plain language.

Automatic documentation

Generates inline documentation of functions, transformations, and pipelines, keeping the codebase readable without manual effort.

Genie Code isn’t an external plugin or third-party integration, it’s a native Databricks capability that understands your full stack: Unity Catalog, Lakeflow pipelines, MLflow experiments, and the full context of your workspace.

Official Blog: What’s New in Genie Code — DAIS 2026

7. AI/BI Dashboards: Beautiful Visualizations Generated with AI

REDESIGNED

Databricks dashboards already existed. AI/BI Dashboards are something different: AI-generated visualizations that understand the meaning of data, not just its format. In Day 2, the team presented the new generation of AI/BI with AI-assisted design capabilities that produce expressive dashboards from natural language.

Prompt-driven design

Describe the dashboard you need in natural language: “show me last quarter’s sales by region with a YoY comparison” and the system generates the layout, charts, and queries.

Beautiful by default

New rendering engine that prioritizes readability and visual expressiveness, AI-generated dashboards have presentation-quality design from the very first attempt.

Automatic contextualization

The system uses the Genie Ontology to understand business metrics, it doesn’t generate raw data charts, it generates insights with business context embedded.

Interactivity with Genie

Dashboards have Genie built in, viewers can ask questions directly about the data being shown without leaving the visualization.

Official Blog: Design Beautiful Dashboards with AI/BI

8. Databricks Free Edition: What’s Coming Next

EXPANSION

The Databricks Free Edition exists so any team can get started with the platform without cost friction. Day 2 presented the roadmap of what’s coming: more capabilities, higher limits, and access to the new agentic features without needing a paid account.

Genie access

Genie available in the Free Edition for natural language data queries, democratizing access to conversational analytics.

Basic Agent Bricks

Agent prototyping with the core Agent Bricks capabilities included in the free tier, so any developer can experiment.

Higher limits

More compute, more storage, and more runs included for experimentation projects, lowering the barrier to entry for small teams.

The Free Edition is the on-ramp for the next generation of data professionals. The most important announcements from DAIS 2026 also reaching the free tier is a clear signal of Databricks’ bet on the ecosystem, not just enterprise customers.

Official Blog: What’s Coming Next for Databricks Free Edition

9. LakeWatch: The Native Agentic SIEM from Databricks

ANNOUNCEDPRIVATE PREVIEW

Traditional SIEMs have three structural problems the market has been tolerating for years: data locked in proprietary formats, prohibitive ingestion costs, and limited historical retention. LakeWatch solves all three at once.

It’s Databricks’ agentic SIEM, built on the Security Lakehouse, the same infrastructure that already governs business data, now extended to security telemetry, IT logs, and threat signals.

Medallion architecture for security

Bronze: raw logs with full-text search, 365+ day retention at object storage cost. Silver: enriched and normalized data. Gold: OCSF-aligned, ready for analytics and detections.

OCSF, the open standard

All logs normalize to the Open Cybersecurity Schema Framework: a common taxonomy that eliminates manual parsing work and enables immediate cross-source correlation.

Genie for threat hunting

SOC analysts ask in natural language: “is there unusual activity from European IPs in the last 72 hours?”, without needing to write SPL or KQL queries.

Unified governance with business data

Security data flows through Unity Catalog, same permissions, same lineage, same cost control as the rest of the platform. The SOC works with the same infrastructure as data teams.

Read full LakeWatch blog post →

Official Blog: Databricks Announces LakeWatch

DAIS 2026 in Perspective: Two Days, One Platform

After two full days of keynotes, Databricks’ message is consistent from beginning to end: the fragmentation of the data and AI stack has a cost that organizations no longer have to pay.

Day 1 built the pillars of performance and product expansion. Day 2 connected them: cross-cutting governance with Unity Catalog and Unity AI Gateway, native security for agents, tools for every profile (analysts, developers, the SOC), and democratization through an expanded Free Edition.

Perspective for Talentbricks Communities

The Day 2 announcements reinforce a clear trend: security teams (LakeWatch), developers (Genie Code), analysts (AI/BI Dashboards), and data scientists (AI Platform) are all converging on the same platform. Knowing Databricks is no longer a niche skill, it’s the core skill of the 2026 data professional.

All Day 2 Official References

  • #Databricks
  • #DAIS 2026
  • #Data + AI Summit
  • #Omnigent
  • #LakeWatch
  • #Genie Code
  • #AI BI Dashboards
  • #Unity AI Gateway
  • #Free Edition
  • #AI Platform
  • #CustomerLake
  • #Security
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