Agyn

Agyn is the open-source management layer for AI agents that takes them off employee laptops and runs them safely across the entire organization. It is the missing infrastructure layer for companies moving from AI experiments to production-grade agent deployments. Every agent runs in an isolated sandbox with secrets hidden from the model, giving each team its own spend cap, role-based access, and a complete audit trail. Agyn works with any agent framework including Claude Code, Codex, and custom builds, and supports any model provider. It can be deployed self-hosted or via Agyn Cloud.

Built for the moment when AI stops being a side project and starts touching production data, Agyn solves the security, finance, and IT challenges that block enterprise adoption. Non-technical teams get agents they can actually use with pre-configured access to internal systems. Engineering retains full oversight through GitOps-driven policies and Kubernetes-native deployment. Finance sees every dollar spent on tokens with per-agent budget tracking. IT stops worrying about shadow AI because every agent is governed by least-privilege policies, static security rules, and prompt-injection defenses. With a 72.2% issue resolution rate on SWE-bench Verified ranking #1 among GPT-5-based systems, Agyn is already proving its production readiness. If your company is moving from agent experiments to agents in production, Agyn is the layer that makes it possible.

Multi-Environment Private Network Deployment

Deploy agents into your VPC in minutes with full support for private networks, VPNs, and VPCs. Ship agents into any environment or private network so they can reach internal services behind firewalls without exposing sensitive infrastructure to the public internet. Instant rollback capabilities ensure you can recover from any deployment issue quickly.

Least Privilege Security with Policy Gate

Every agent runs under least privilege with static policies and a policy agent that inspects every tool call before execution. Secrets stay hidden from the model, defending against prompt injection attacks and sensitive data leaks. The policy gate reviews every action in real-time, blocking out-of-scope operations and escalating ambiguous or high-risk actions for human approval.

Per-Agent Budget Tracking and Cost Attribution

Track spend across agents, teams, and workflows with granular per-agent budget limits and usage alerts. Set hard caps on token consumption, receive real-time alerts when spending approaches thresholds, and get full cost attribution to understand exactly which teams and workflows are driving AI costs. Finance teams finally get the visibility they need to approve AI agent adoption.

Team Sharing with Role-Based Access Control

Give the right employees access to the right agents with role-based access controls and comprehensive audit logs. Share agents safely across teams, manage permissions at scale, and keep usage fully governed as adoption grows. Every action is logged and auditable, providing the compliance and governance that enterprise security teams demand.

Production Database Analysis for Business Teams

Data analysts and business users can deploy agents that securely connect to production databases from within the corporate network. The agent runs in an isolated sandbox with read-only database access scoped to specific tables and columns. Non-technical users simply request analysis in natural language, while security teams enforce data access policies and audit every query executed against production systems.

Automated Code Review and PR Management

Engineering teams deploy code review agents that read repositories, comment on pull requests, and send email notifications about review status. The policy gate ensures these agents cannot make outbound calls to external services or access sensitive data outside their defined scope. Teams get consistent, automated code review at scale while maintaining strict security boundaries and preventing data leaks.

Customer Support Agent with Escalation Workflows

Support teams deploy agents that read tickets, query internal knowledge bases, and send email replies to customers. The planner/executor split architecture ensures planning agents cannot directly execute actions, preventing accidental data modifications. Human escalation policies pause on ambiguous or high-risk actions, giving support managers final approval before sensitive responses go out.

Internal Research and Web Intelligence Gathering

Research teams deploy agents that browse the web, summarize findings, and write reports while maintaining internal network access for corporate resources. The policy gate blocks agents from following embedded instructions in web content, preventing prompt injection attacks. Budget limits ensure research costs stay under control, and audit trails provide complete visibility into what information was accessed and how it was used.

How does Agyn protect against prompt injection attacks?

Agyn employs multiple layers of defense against prompt injection. Secrets are stored in a vault and never exposed to the model, so even if an attacker injects malicious instructions, they cannot access credentials. The policy agent sanitizes feedback from tools and agents, stripping injected instructions from responses before they reach the model. Additionally, the planner/executor split ensures planning agents cannot directly execute actions, preventing injection-based command execution.

Can I deploy Agyn on my own infrastructure?

Yes, Agyn is fully open-source and supports self-hosted deployment on Kubernetes. You can deploy it into your own VPC, behind your corporate VPN, and integrate with your existing identity providers. The quickstart involves cloning the bootstrap repository and running a single apply command. Agyn Cloud is also available as a managed alternative for teams that prefer not to manage infrastructure.

Does Agyn work with any AI model or agent framework?

Agyn is model-agnostic and works with any agent framework including Claude Code, Codex, GPT-5, Gemini, and custom-built agents. The platform provides a consistent management layer regardless of which model or framework you choose. You can mix and match different agents for different use cases, all governed by the same security policies, budget controls, and audit trails.

How does Agyn handle cost management across teams?

Agyn provides per-agent budget tracking with configurable spend caps and usage alerts. Finance teams can set hard limits on token consumption for each agent, team, or workflow. When spending approaches predefined thresholds, alerts are sent to relevant stakeholders. Full cost attribution shows exactly which teams and use cases are driving AI costs, enabling informed budget planning and chargebacks.