DeepTrail offers the DeepSecure library, enabling AI agents to obtain cryptographic identities and short‑lived, rotating credentials instead of hard‑coded API keys. By installing a Python package and configuring a Docker‑based gateway, developers can retrieve secure, auditable secrets with a single client call, simplifying compliance and reducing security risk for LLM‑powered applications.
Funding
Funding not disclosed
Founders
Product
Problem
AI agents often rely on hard‑coded API keys or static credentials, which creates security risks, makes auditing difficult, and hampers compliance when agents need to access multiple services.
Solution
DeepTrail’s DeepSecure library provides AI agents with cryptographic identities and automatically issued short‑lived credentials. By installing the library, configuring a gateway service, and invoking a single client call, developers can give each agent a unique, auditable identity without embedding raw keys in code. The library fetches temporary secrets from a secure backend, enabling agents to access external APIs and internal resources safely. Integration works through a simple three‑step process (install, configure, runtime) and supports both command‑line and SDK usage, streamlining secure deployment for AI‑driven applications.
Target Audience
DeepSecure is aimed at developers and engineering teams building LLM‑powered applications, AI agents, and automation workflows that require secure, programmatic access to external services and internal data.
Features
- Python package (pip install deepsecure) with Docker‑based gateway service for credential issuance
- Automatic generation of cryptographic identities per agent instance
- Short‑lived, rotating credentials fetched on demand, eliminating static key storage
- Single‑line client API to retrieve secrets securely at runtime
- Compatibility with both CLI workflows and SDK integrations for diverse AI platforms
- Auditable access logs tied to agent identities for compliance and monitoring