Enterprise PubSub for AI Agents

Solving the Agentic AI Scaling Challenge

Secure, scalable message brokering service designed specifically for coordinating AI agents in enterprise environments.

The Challenge

As organizations deploy multiple AI agents, coordination becomes exponentially complex. Traditional messaging systems weren't built for the unique requirements of AI agents.

Reliability Issues

AI agents need guaranteed message delivery and ordering to maintain consistency across complex workflows.

Performance Bottlenecks

Traditional systems struggle with the high-frequency, low-latency communication patterns of AI agents.

Security Concerns

Enterprise environments require end-to-end encryption and fine-grained access control for agent communications.

Our Solution

Purpose-Built for AI Agents

  • Agent-Aware Protocol: Optimized for the unique communication patterns of AI agents, including context preservation and state management.
  • Semantic Routing: Intelligent message routing based on agent capabilities and current workload.
  • Built-in Observability: Deep insights into agent interactions, performance metrics, and system health.

Enterprise-Grade Features

  • End-to-End Encryption: Military-grade encryption for all agent communications with key rotation.
  • Horizontal Scaling: Seamlessly scale to thousands of agents with automatic load balancing.
  • 99.99% Uptime SLA: Built on proven infrastructure with redundancy and failover capabilities.

Technical Architecture

Message Broker Core

  • • High-performance event streaming
  • • Guaranteed message ordering
  • • At-least-once delivery
  • • Message persistence & replay

Agent SDK

  • • Python, Node.js, Java SDKs
  • • Auto-reconnection & retry
  • • Built-in circuit breakers
  • • Prometheus metrics export

Control Plane

  • • Web-based management UI
  • • Real-time monitoring
  • • Access control & policies
  • • API for automation

Use Cases

Multi-Agent Workflows

Coordinate complex workflows across specialized agents - from data ingestion and processing to analysis and action execution.

Example: Financial analysis pipeline with data collection, risk assessment, and trading execution agents.

Agent Swarm Management

Manage large swarms of agents working on distributed tasks with dynamic task allocation and load balancing.

Example: Content moderation system with hundreds of specialized agents for different content types.

Event-Driven Architectures

Build reactive systems where agents respond to events in real-time, enabling dynamic and adaptive behaviors.

Example: IoT monitoring system with agents responding to sensor data and triggering appropriate actions.

Human-in-the-Loop Systems

Enable seamless collaboration between AI agents and human operators with approval workflows and escalation mechanisms.

Example: Customer service system where agents handle routine queries and escalate complex issues to humans.

Ready to Scale Your AI Agents?

Join the enterprises already using our PubSub solution to power their agent ecosystems.