Connect. Secure.
Audit your AI agents.
Quickly build and scale AI agents without exposing your enterprise data with public models. Track agentic with the performance you expect from Redpanda.
Why AI deployments fail
Large enterprises face unique challenges implementing AI at scale that smaller organizations don't encounter. While startups may focus on rapid deployment and iteration, enterprises must navigate complex regulatory environments, legacy systems, and data governance requirements.
Data risks
Unintended exposure of private sensitive data with public models
Model costs
Uncontrolled costs using public models or runaway GPU cycles
Access policies
No centralized data access policies for model authentication or enforcement
Developer friction
Manual stitching of tools impacts developer efficiency
Data leaves your environment and goes over the public internet to your AI model.
Run secure, performant models locally with Redpanda while reducing costs.
Enterprise-grade agentic AI solution
Redpanda transforms how enterprises implement AI with a complete platform that prioritizes security, auditability, and performance. Our agentic runtime delivers powerful capabilities designed for enterprise requirements.
Autonomous traceable agents
Define multi-agent workflows with built-in access controls and complete auditability without sacrificing performance. Our Python SDK allows you to create agents that dynamically control processes, tools, and internal data systems with code-free prompts while maintaining full visibility of every action.
MCP enabled integration
Transform any internal tool—Redis, Postgres, GitHub, Salesforce—into secure, agent-ready HTTP endpoints within seconds. Our Model Context Protocol enables seamless communication while preserving your security controls, eliminating data exposure risks.
300+ enterprise connectors
Leverage our comprehensive connector library for all your integrations, eliminating custom development work and accelerating implementation. These pre-built connections to your essential data systems reduce developer friction and improve efficiency across your AI initiatives.
Sovereign data with BYOC
Run everything inside your own network. Redpanda's atomic data plane architecture guarantees compliance and uptime while keeping sensitive data within your control. Our Bring Your Own Cloud approach ensures you meet regulatory requirements without sacrificing performance.
Private AI without compromise
Deploy state-of-the-art open models like Llama 3.1, Phi-4, Mistral, Gemma3, and Qwen inside your firewalls. This approach ensures all sensitive data remains within your infrastructure, providing maximum security while still leveraging cutting-edge AI capabilities—your data stays yours, always.
Protection across all layers
Confidently deploy and manage large-scale systems with robust integrity, authentication, authorization, access controls, and audit logs. Seamlessly integrate AI model deployments with standard OCSF audit log tools like Splunk and monitor them using your open telemetry stack.
Integrate seamlessly with your entire stack
Go from humdrum data pipelines to composable data products. Connect anything with 300+ connectors.
Bring Your Own Cloud, leveraging enterprise AI
Deploy on AWS, GCP, or Azure.
Support for 112,500 partitions and 450,000 connections.
Achieve 99.99% SLA with built-in redundancy.
SSO, RBAC, audit logging, and OIDC integration ensure compliance.
Intuitive CLI, Kafka-compatible APIs, and comprehensive dashboards.
Introducing the Redpanda Connect MCP server and rpk agent
Transform your data streams with Redpanda agents
