Hey HN!<p>We built Inferable to tackle some common challenges when putting AI systems into production. It's an open-source platform with a managed control plane to help simplify the development of reliable AI applications.<p>After working on several LLM-based projects, we kept running into the same issues:<p>- Workflows crashing and losing state
- No good way to pause execution for human approvals
- Need to build the same boilerplate for human approvals
- Difficulty managing the lifecycle of long-running processes
- Can't get structured output out reliably from every LLM
- Repeated effort building infrastructure for structured outputs<p>We built Inferable to address these with:<p>- Persistent workflow state that survives crashes and restarts
- Built-in human-in-the-loop functionality for approvals
- A distributed architecture that separates orchestration from execution
- Standardized methods for extracting structured data from LLMs<p>Your code runs in your infrastructure while our control plane handles the orchestration. If you're familiar with temporal, think of it as temporal with higher-level LLM-native primitives.<p>Everything is open-source (MIT license), and self-hosting options are available if you prefer to run it all yourself.<p>Would appreciate feedback from anyone building AI applications with similar challenges!