Media Summary: Recap Blog: Confluent CEO and Co-Founder Jay Kreps took the stage at Current New Orleans to explain ... Streaming Agents enable you to build, deploy, and orchestrate ... Agents can generate code. The hard part is generating code that's right for your system, team conventions, and past decisions.

Real Time Context Engine Power - Detailed Analysis & Overview

Recap Blog: Confluent CEO and Co-Founder Jay Kreps took the stage at Current New Orleans to explain ... Streaming Agents enable you to build, deploy, and orchestrate ... Agents can generate code. The hard part is generating code that's right for your system, team conventions, and past decisions. Join Jay Kreps, Confluent leadership, our customers, and industry thought leaders to learn how you can build intelligent systems ... MCP has a blind spot. The standard request-response model means your AI agents only find out about anomalies, spikes, and ... ... Amazon Bedrock AgentCore Explained [09:20]

From smart glasses to enterprise agents, all agentic AI systems need trusted data, models, and logic to operate. That's where the ...

Photo Gallery

Real-Time Context Engine: Power AI Agents With Instant Intelligence | Current ‘25 Keynote Highlights
Demo: Streaming Agents for price matching, with RAG, observability, and Real-Time Context Engine
Demo: Confluent Intelligence - Real-Time Context Engine
Mergeable by default: Building the context engine to save time and tokens — Peter Werry, Unblocked
Keynote: Building Intelligent Systems on Real-time Data
Danti for Global Context on Demand - AI-Powered Knowledge Engine
DeltaStream: The Real-Time Context for GenAI Agents
MCP Beyond Request-Response: Streaming Real-Time Context to AI Agents
Power Your AI Agents with Context
Building the Agentic Enterprise: How AWS and Confluent Power Real-Time AI | Life Is But A Stream
Power AI Agents with SAS AI and Real-Time Analytics via Model Context Protocol (MCP)
View Detailed Profile
Real-Time Context Engine: Power AI Agents With Instant Intelligence | Current ‘25 Keynote Highlights

Real-Time Context Engine: Power AI Agents With Instant Intelligence | Current ‘25 Keynote Highlights

Recap Blog: https://cnfl.io/4p8sDKo | Confluent CEO and Co-Founder Jay Kreps took the stage at Current New Orleans to explain ...

Demo: Streaming Agents for price matching, with RAG, observability, and Real-Time Context Engine

Demo: Streaming Agents for price matching, with RAG, observability, and Real-Time Context Engine

http://github.com/confluentinc/quickstart-streaming-agents/ Streaming Agents enable you to build, deploy, and orchestrate ...

Demo: Confluent Intelligence - Real-Time Context Engine

Demo: Confluent Intelligence - Real-Time Context Engine

Confluent's

Mergeable by default: Building the context engine to save time and tokens — Peter Werry, Unblocked

Mergeable by default: Building the context engine to save time and tokens — Peter Werry, Unblocked

Agents can generate code. The hard part is generating code that's right for your system, team conventions, and past decisions.

Keynote: Building Intelligent Systems on Real-time Data

Keynote: Building Intelligent Systems on Real-time Data

Join Jay Kreps, Confluent leadership, our customers, and industry thought leaders to learn how you can build intelligent systems ...

Danti for Global Context on Demand - AI-Powered Knowledge Engine

Danti for Global Context on Demand - AI-Powered Knowledge Engine

Danti, the company behind an AI-

DeltaStream: The Real-Time Context for GenAI Agents

DeltaStream: The Real-Time Context for GenAI Agents

Discover how Model

MCP Beyond Request-Response: Streaming Real-Time Context to AI Agents

MCP Beyond Request-Response: Streaming Real-Time Context to AI Agents

MCP has a blind spot. The standard request-response model means your AI agents only find out about anomalies, spikes, and ...

Power Your AI Agents with Context

Power Your AI Agents with Context

Airbyte's Agent

Building the Agentic Enterprise: How AWS and Confluent Power Real-Time AI | Life Is But A Stream

Building the Agentic Enterprise: How AWS and Confluent Power Real-Time AI | Life Is But A Stream

... Amazon Bedrock AgentCore Explained [09:20]

Power AI Agents with SAS AI and Real-Time Analytics via Model Context Protocol (MCP)

Power AI Agents with SAS AI and Real-Time Analytics via Model Context Protocol (MCP)

From smart glasses to enterprise agents, all agentic AI systems need trusted data, models, and logic to operate. That's where the ...