accord-engine 1.0.1

Multi-Agent Decision Intelligence Engine by Arclane Systems

Accord Engine

Accord Engine is a powerful Multi-Agent Decision Intelligence framework designed by Arclane Systems. It provides a robust, state-of-the-art infrastructure for executing and orchestrating complex negotiations between autonomous AI agents.

Whether you're building automated B2B procurement systems, autonomous trip planners, or dynamic resource allocators, Accord handles the hard parts of agent interaction: policy enforcement, cryptographically verifiable trust trails, long-term memory, and observability.

Features

• Multi-Agent Orchestration: Seamlessly run complex, multi-round negotiations between customized agents (powered by LangGraph).
• LLM-Driven Policies: Agents negotiate intelligently using Groq-powered LLMs, balancing strict priorities and flexibilities.
• Persistent Agent Memory: Deep memory integration via Letta ensures agents remember past outcomes and opponents across sessions.
• Cryptographic Trust: Every offer and counter-offer is signed and verified using asymmetric cryptography for complete auditability.
• Deep Observability: Tracing via Langfuse provides granular visibility into every LLM call and agent reasoning step.
• Rich Reporting: Automatically generate beautiful HTML negotiation transcripts and visual trace reports.

Quick Start

pip install accord-engine

from accord import NegotiationSession, Agent, Preference

# 1. Define your agents and their hidden preferences
buyer = Agent(
    name="ProcurementBot",
    preferences=[
        Preference(name="budget", value=5000, priority=0.9, flexibility=0.2),
        Preference(name="timeline", value=30, priority=0.6, flexibility=0.5),
    ]
)

seller = Agent(
    name="VendorBot",
    preferences=[
        Preference(name="budget", value=7500, priority=0.9, flexibility=0.3),
        Preference(name="timeline", value=45, priority=0.4, flexibility=0.8),
    ]
)

# 2. Spin up a secure negotiation session
session = NegotiationSession(
    agents=[buyer, seller], 
    max_rounds=15
)

# 3. Let them negotiate
result = session.run()

print(f"Outcome: {result.outcome}")
if result.success:
    print(f"Final Agreed Terms: {result.final_terms}")

print(f"Reasoning: {result.reasoning}")

Documentation

Full documentation, architecture references, and advanced usage guides are available at Arclane Systems.

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Built with precision for the next generation of autonomous infrastructure.