Hyrex
Hyrex is an open-source task queue and job orchestration platform for Python and TypeScript developers. It enables reliable execution of background jobs, cron tasks, and AI agent workflows, requiring only Postgres as its infrastructure dependency. The platform includes high-available workers that self-heal and monitor each other, with cross-cloud deployment on AWS, GCP, and Azure.
- Developer Tools
- Software Only
- Artificial Intelligence
Funding
Raised to date
$500KRaised to date based on public sources. This may differ from the amount the company actually raised and is based only on what is publicly available on the internet.
Founders
Founder details are not available yet.
Product
Problem
Developers building background jobs, scheduled tasks, and AI agent workflows often rely on complex infrastructure systems that require multiple services to manage reliably. These systems introduce operational overhead, vendor lock-in concerns, and significant configuration complexity, making it difficult for teams to focus on core application logic rather than plumbing.
Solution
Hyrex provides an open-source task queue and job orchestration platform with SDKs for Python and TypeScript developers. The platform enables reliable execution of background jobs, cron tasks, and AI agent workflows, including real-time data index building, LLM context preparation, and multi-step processes like ecommerce checkouts and user onboarding. Hyrex requires only Postgres as its infrastructure dependency, making deployment simple across any cloud provider. The platform includes high-available workers that monitor each other and self-heal, ensuring maximum uptime, and offers full source code access with no vendor lock-in.
Target Audience
Primary users are Python and TypeScript developers building background job systems, AI agent workflows, and event-driven applications who need reliable task orchestration without complex infrastructure requirements.
Features
- Python and TypeScript SDKs for rapid integration with existing codebases
- AI-ready dataset building with real-time data indexes for up-to-date AI agent context
- Parallel processing pipelines for document parsing, transformation, and analysis
- Built-in workflow orchestration for ecommerce checkouts, user onboarding, and other multi-step processes
- High-available worker architecture with self-healing and safe fail-overs
- Minimum viable architecture requiring only Postgres, with cross-cloud deployment on AWS, GCP, and Azure