Guild.ai is the control plane for AI agents, giving engineering teams a single place to manage every agent running in production. It handles governance, access control, cost tracking, and observability so agents don't operate as unsupervised black boxes. Guild is framework-agnostic and model-agnostic, working with LangChain, CrewAI, OpenAI, Anthropic, and more. You can build agents with its TypeScript SDK, deploy ready-made Starter Kit agents, or bring your own and run them through the same governed infrastructure. Free to start, with paid plans based on usage.

• Agent Control Plane: Define what agents can do, manage system access, and monitor all agent activity from one centralized dashboard. Every execution is traceable and auditable.
• Zero-Trust Security Model: Tokens are dynamically resolved at the exact moment of execution and never exposed to agent code. Identity is enforced and access is controlled at the infrastructure level.
• Human-in-the-Loop Approvals: Set approval gates for sensitive actions. Agents pause and wait for human review before proceeding, configurable per agent and per action.
• Real-Time Cost Visibility: Track token consumption per agent, user, and model with live dashboards. Spot runaway loops and inefficient prompting before they drain your budget.
• Framework & Model Agnostic: Works with LangChain, CrewAI, OpenAI SDK, Microsoft Bot Framework, Anthropic, Google, and custom code. No vendor lock-in, no rewrites required.
• Starter Kit Agents: Ship faster with production-ready agents for Ticket Triage, Code Review, Incident Response, and Slack Bot. Fork and customize them to fit your workflows.
• Agent Hub & Sharing: Discover, fork, and remix agents across your organization. Build on what others have already created instead of starting from scratch.
• Versioning & Rollback: Agents are treated like source code with full version control, change validation, and the ability to roll back to previous versions.

• Minimal Integration Effort: Works with existing agent runtimes using the Guild SDK, allowing teams to add governance and observability without rebuilding their agents from scratch.
• Strong Governance Out of the Box: Scoped access, audit trails, and approval workflows are built into the runtime, not bolted on as an afterthought.
• Vendor-Neutral Architecture: Supports multiple LLM providers and agent frameworks. You can switch models or providers without changing your agents.
• Fast Time to Value: Starter Kit agents and the TypeScript SDK let teams go from zero to a governed, production-ready agent in under an hour.

• Enterprise-Focused Scope: The platform targets engineering teams managing agents at scale. Solo developers or small teams with only a few agents may not need this level of infrastructure.
• Competitive Market: Cloud providers like Google, Microsoft, and Amazon are building agent governance features into their own ecosystems, which could reduce the appeal of a standalone control plane.
• TypeScript-First SDK: The primary SDK is TypeScript-based, which may not suit teams working primarily in Python or other languages, though a Python SDK is also available.

• Engineering Team Agent Governance: Your team has deployed a dozen agents across different frameworks, and nobody knows what they can access or what they cost. Guild.ai gives you a single dashboard to manage permissions, track spend, and audit every action across all your agents.
• Automated Code Review: Use the Starter Kit Code Review agent to flag security vulnerabilities, breaking changes, and performance regressions in every pull request. Fork and customize the agent to match your team's review standards.
• Support Ticket Triage: Deploy an agent that automatically classifies incoming tickets by urgency, routes them to the right team, and enriches them with relevant context from your codebase, reducing manual sorting time.
• Incident Response Automation: When an alert fires, the Incident Response agent traces through logs, recent deploys, and code changes to surface the probable root cause, cutting mean time to resolution.
• Cost Control for AI Operations: Track token consumption across every agent in your organization. Set spend thresholds and circuit breakers to prevent runaway loops from burning through your inference budget overnight.
• Codebase Onboarding: Build an agent that lets new engineers have a conversation with the codebase, ask questions about features, and get system diagrams instead of spending days reading documentation.