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What is Syntha?

Syntha is a multi-agent context framework that solves the coordination problem in AI systems. Instead of manually passing data between agents, Syntha creates a shared knowledge space where agents can intelligently store, discover, and retrieve relevant information.

The Problem

Building AI applications with multiple agents is challenging because:

  • Context Chaos: Agents work in isolation without shared knowledge
  • Manual Coordination: You have to manually pass data between agents
  • Information Loss: Context gets lost during agent handoffs
  • Brittle Workflows: One failed agent breaks the entire system

The Solution

Syntha creates a Context Mesh - a smart, persistent memory layer that:

  • Automatically shares context between agents based on topics and subscriptions
  • Maintains context continuity across sessions and agent handoffs
  • Provides user isolation to keep different users' data completely separate
  • Integrates seamlessly with your existing LLM framework

How It Works

from syntha import ContextMesh, ToolHandler

# Create shared context space
context = ContextMesh(user_id="user123")

# Agents push context as they work
context.push("customer_data", {"name": "John", "tier": "Premium"})
context.push("analysis_result", research_data, topics=["sales", "strategy"])

# Other agents automatically get relevant context when they need it
handler = ToolHandler(context, "SalesAgent")
# Agent now has access to all relevant context through tools

Key Benefits

  • Zero Configuration: Works out of the box with SQLite, scales to PostgreSQL
  • Framework Agnostic: Integrates with OpenAI, Anthropic, LangChain, and more
  • Production Ready: 168+ tests, structured logging, proper error handling
  • User Isolation: Complete separation between different users' contexts
  • Persistent Memory: Context survives between sessions

Who Should Use Syntha?

Developers building multi-agent AI applications who want to focus on agent logic instead of context management.

Teams creating scalable AI systems that need reliable agent coordination.

Companies deploying production AI applications that require robust context handling and user isolation.

Next Steps