Resources
Explore H2LooP's latest insights on embedded systems AI, safety-critical software development, AUTOSAR best practices, research papers, industry case studies, and expert tech talks.
Blog
- From Silicon Specs to Optimized Code: H2LooP's Embedded Engineering Superpower
From Datasheet to High-Performance Code — How H2LooP Thinks Like a Lower-Level System Engineer. AI-powered embedded code generation directly from silicon datasheets. - High-Performance Computing Code Generation using LLMs
Writing high-performance computing (HPC) code is notoriously difficult. Discover how H2LooP uses purpose-built LLMs for parallel algorithms, MPI, and complex mathematical computations. - On Convergence Dynamics in Fine-tuning Strategies for Large Language Models
H2LooP research on convergence dynamics in fine-tuning strategies for domain specialization of large language models in systems engineering tasks. - Auto-Transform Your C Code to MISRA Compliance with H2LooP Code-Sanitizr
Benchmarking compact, domain-specialized Small Language Models (SLMs) against frontier models for safety-critical embedded systems MISRA compliance. - SpecMap: Connecting Datasheets to Code
H2LooP's SpecMap provides AI-powered traceability between datasheet specifications and code implementations for embedded systems, IoT devices, and standards-compliant software.
Research
- SpecMap: Hierarchical LLM Agent for Datasheet-to-Code Traceability Link Recovery in Systems Engineering — H2LooP Research Team, Jan 2026. Read on arXiv
Case Studies
- Knowledge Graph — Maximizing GitHub Copilot Value with H2LooP
How a Tier-1 Semiconductor Company deployed H2LooP's on-premise Knowledge Graph MCP Server to inject deep internal context into GitHub Copilot Enterprise — achieving 30–40% productivity improvement. - Sovereign AI Coding Stack for Mission-Critical Defence Software
How a Leading Defence R&D Lab deployed a fully sovereign, air-gapped end-to-end AI coding stack with domain-specific SLMs and distributed low-GPU inference — zero external dependencies.