Healthcare

H2LooP.ai is building Specialized Language Models (SLMs) tailored for system software engineers in regulated industries like healthcare. Our models are fine-tuned specifically on legacy C/C++ codebases found in medical imaging systems, patient monitors, and embedded diagnostic platforms. H2LooP enables deep code comprehension, architectural visualization, and auto-generation of technical documentation accelerating engineering velocity without compromising on compliance or safety. We empower healthcare OEMs and ISVs to gain visibility into their legacy systems and build confidently toward modern, modular software.

healthcare devices

Challenges in Healthcare

Healthcare system software faces major challenges: large undocumented C/C++ codebases, slow onboarding, and strict compliance demands (FDA, IEC 62304, ISO 13485). Lack of architectural visibility increases the risk of regressions and audit failures.
Poorly Documented Legacy Codebases
Vast legacy codebases in C/C++ with little to no documentation.
Traceability is Critical in Medical Software
Medical software must be auditable and maintain traceability from requirements to implementation. Legacy codebases without consistent documentation put companies at risk during regulatory inspections and audits.
Lack of Architectural Visibility Jeopardizes Safety
Without full architectural visibility, refactoring embedded healthcare software can break dependencies, cause regressions, and delay releases, jeopardising compliance and safety.
Long Onboarding Time for New Engineers
New engineers spend 4–6 weeks on average understanding legacy systems before becoming productive. Without access to system-level documentation or architecture diagrams, onboarding is slow and error-prone.
Regulatory Compliance Requires Documentation
Compliance demands (FDA, IEC 62304, ISO 13485) require traceable, up-to-date documentation
High risk of regression during modernization
Modernizing legacy systems without a clear view of their architecture can unintentionally introduce bugs or break critical functionality, increasing the risk of costly regressions.

Why H2Loop ?

01

DICOM Documentation from Legacy Code

Auto-generating DICOM stack documentation and data/control flow diagrams from existing C/C++ source code.

02

System Architecture Visualisation

Visualising complex system architecture, including driver-hardware interactions and modality logic.

03

Audit-Ready Engineering Documentation

Supporting FDA and ISO audits by creating engineering documentation from codebases directly.

04

Faster Onboarding with Code Insights

Reducing onboarding time by providing contextual diagrams and code explanations to new team members.

SLMs Purpose-Built for Healthcare System Software

Unlike general purpose AI coding tools, H2LooP is purpose-built to serve engineering teams working on performance-critical and regulated healthcare systems. Our domain-specific SLMs are trained on real-world C/C++ code enabling them to parse legacy software, reason about protocols like DICOM, and produce meaningful architecture-level insights. H2LooP gives R&D and quality teams a shared, AI-powered lens into their systems, accelerating development while maintaining compliance.