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  • Welcome
  • Getting Started
    • Amigo Overview
      • System Components
      • Overcoming LLM Limitations
      • [Advanced] Future-Ready Architecture
      • [Advanced] The Accelerating AI Landscape
    • The Journey with Amigo
      • Partnership Model
  • Concepts
    • Agent Core
      • Core Persona
      • Global Directives
    • Context Graphs
      • State-Based Architecture
      • [Advanced] Field Implementation Guidance
    • Functional Memory
      • Layered Architecture
      • User Model
      • [Advanced] Recall Mechanisms
      • [Advanced] Analytical Capabilities
    • Dynamic Behaviors
      • Side-Effect Architecture
      • Knowledge
      • [Advanced] Behavior Chaining
    • Evaluations
      • [Advanced] Arena Implementation Guide
    • [Advanced] Reinforcement Learning
    • Safety
  • Glossary
  • Advanced Topics
    • Transition to Neuralese Systems
    • Agent V2 Architecture
  • Agent Building Best Practices
    • Agent Identity & Background Guide
      • Quick Reference Guide
    • Context Graph Guide
      • Quick Reference Guide
    • Dynamic Behaviors Guide
      • Quick Reference Guide
  • Developer Guide
    • Enterprise Integration Guide
      • Authentication
      • User Creation + Management
      • Service Discovery + Management
      • Conversation Creation + Management
      • Data Retrieval + User Model Management
      • Webhook Management
    • API Reference
      • V1/organization
      • V1/service
      • V1/conversation
      • V1/user
      • V1/role
      • V1/admin
      • V1/webhook_destination
      • V1/dynamic_behavior_set
      • V1/metric
      • V1/simulation
      • V1/tool
      • Models
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On this page
  • The Partnership Model
  • The Trust Framework
  • Speed of Execution

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Welcome

At Amigo, our mission is clear: build safe, reliable AI agents that organizations can genuinely depend on. We've developed a proprietary agent architecture and built a robust platform to enable enterprises to safely create, train, and deploy expert agents into high-stakes frontline use cases.

The Partnership Model

Amigo operates on a clear division of responsibilities: you bring your expertise to define agent behavior, success criteria, and simulation scenarios, while our platform and team help you build an efficient, recursively improving AI system that evolves until we exceed your performance benchmarks.

Similar to Waymo's approach to autonomous driving, we prioritize reliability in well-defined domains rather than pursuing a high-risk "do it all" approach. This methodical, safety-first philosophy ensures our systems are thoroughly validated before expanding their scope, providing organizations with AI solutions they can confidently implement.

The Trust Framework

Despite enormous potential, AI adoption faces one critical barrier: trust. We define trust as confidence that an AI system will reliably act in alignment with an organization's goals and values, built on three pillars:

  • Controllability: Human ability to train, adjust, and intervene in agent behavior

  • Continuous Alignment: Adaptation to changing organizational priorities & regulatory environments

  • Real-time Observability: Transparent operations for monitoring and verification

Speed of Execution

Our system delivers three decisive time-based advantages:

  • Time to Trust: Reducing verification timelines from months to hours through transparent, inspectable AI reasoning

  • Time to Value: Deploying agents in weeks rather than traditional six-month cycles

  • Time to Flywheel: Establishing a rapid self-reinforcing improvement cycle where data drives enhancement, leading to wider adoption

To see our product & platform overview, please start with our Overview:

To see our API documentation, please refer to our Developer Guide:

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