Runta
Runta provides a secure execution layer for AI agents in production, governing file access, network calls, and credential use at the operating system boundary. The platform reduces token consumption through prompt compression, suspends idle agents automatically, and enforces task-specific egress policies without requiring teams to rewrite their agent frameworks. It offers usage-based pricing with no subscription, charging only for vCPU, memory, and disk while agents run.
- Developer Tools
- Artificial Intelligence
- AI Agents
- Cybersecurity
- Software Only
Funding
Funding not disclosed
Founders
Founder details are not available yet.
Product
Problem
AI agents in production face uncontrolled token spend, idle compute waste, exposure of raw credentials, and unrestricted network access. These issues drive up costs and create security risks that prevent teams from giving agents real, meaningful work.
Solution
Runta provides a secure execution layer that governs what agents can do as they run, without requiring teams to rewrite their agents or swap frameworks. The platform sits at the operating system and network boundary, enforcing predefined policy on every file access, network call, and credential use. It compresses prompts and logs to reduce token consumption, suspends idle agents automatically, and issues credentials just-in-time against task-specific policies. Runta records actual system calls and network activity for audit and debugging, and starts execution environments in milliseconds with auto-scaling memory.
Target Audience
Primary customers are engineering teams at companies deploying AI agents in production who need to control costs, secure credentials, and enforce network access policies without rewriting their agent frameworks.
Features
- Prompt pipeline that compresses JSON, logs, search results, and git diffs into token-efficient formats while preserving signal
- OS-level process monitoring that suspends idle agents and wakes them when work resumes
- Egress governance that restricts network destinations to task-declared endpoints, blocking all other connections
- Just-in-time credential issuance and revocation tied to task policy, preventing raw credential exposure
- Checkpoint and restore functionality for pausing and resuming agent state
- Memory auto-scaling that sizes resources to actual agent workload
- SDKs for Python and TypeScript, plus CLI tooling for runtime management
- Team access controls and role-based permissions for organizational governance