hiloop
Infrastructure for recursive self-improvement
About hiloop
hiloop helps teams train agents for tasks where general models are not good enough. Give us a task, your current agent or model, and an evaluation. hiloop runs an autoresearch campaign across data, SFT and other post-training methods, continual learning, prompts, tools, harnesses, and systems, then returns the best verified improvement. It runs hosted or in your cloud. We provide the research system around models: persistent memory, full experiment lineage, compute orchestration, and statistical verification. We’re starting with agent and model training, continual learning, and optimization. Reach out to us for early access at founders@hiloop.ai.
Public traction evidence
Each signal links to the public source used for attribution.
- GitHub
GitHub signal from hiloopai/hiloop-interceptor
hiloopai/hiloop-interceptor: hiloop interceptor wrapper for agent harnesses - captures LLM calls, network traffic, telemetry, and stdio. (Rust).
- GitHub
GitHub signal from hiloopai/skills
hiloopai/skills: Open-source Agent Skills for operating hiloop — forkable agent sandboxes with tree-native observability. CLI-first, cross-harness. (Python).