H2LooP Raises $2m For Embedded-System AI Coding Tools

BySendTech Times AI & Enterprise DeskNewsroom-edited, source-reviewed coverage|Source: YourStory

Newsroom brief

YourStory reported that Bengaluru startup H2LooP raised $2 million to build hardware-aware AI coding tools for firmware and embedded systems, with early deployments in semiconductor and automotive teams.

Verified against source materialEdited by SendTech Times AI & Enterprise Desk

H2LooP Raises $2m For Embedded-System AI Coding Tools

Image source: YourStory

YourStory lists a $2 million seed round behind H2LooP's push into firmware and device drivers, with the Bengaluru startup pairing small language models with a hardware knowledge graph covering processor constraints, safety standards and customer-owned code.

The H2LooP embedded-system AI coding tool targets software that general AI coding assistants often miss: low-level code for semiconductors, automotive systems, aerospace, telecom, defence, data centres and robotics.

The startup is already deployed with semiconductor and automotive teams across India and Europe, while its funding plan points to more enterprise deployments.

H2LooP Raised $2m From Speciale Invest And 3one4 Capital

YourStory lists H2LooP's seed round at $2 million, about Rs 18.6 crore, co-led by Speciale Invest and 3one4 Capital in early 2026.

The funding is meant to strengthen the platform, scale enterprise deployments and push into higher-complexity areas including data centres, drones and robotics.

The company was founded in May 2025 by chief executive Sairanjan Mishra and chief technology officer Pulkit Agrawal.

Mishra's background spans complex-systems software work at Philips, Toshiba, Cisco and Bosch, while Agrawal's résumé includes low-level software work at Google.

The report said the problem is a hardware-software bottleneck, not a normal application-development task.

Firmware and driver work can require manual reviews, hand-written compliance documents and months of senior engineering time when a product moves to a new chip.

Small Models Are Paired With A Hardware Knowledge Graph

H2LooP's product combines small language models trained on embedded-systems code with a proprietary knowledge graph.

That graph maps hardware specifications, safety standards, design patterns and a customer's own codebase so the models can reason over the constraints that ordinary web-code assistants do not understand.

A verification layer checks generated code before it reaches production.

The system can also run on-premises or fully air-gapped, keeping customer code inside the buyer's environment for sectors such as defence and semiconductors.

The architecture is aimed at mission-critical industries including semiconductors, automotive, aerospace, telecom and defence.

Data centres and robotics are also listed as newer target areas for the startup.

German Semiconductor Deployment Carries The Performance Claim

At one German semiconductor company handling AUTOSAR compliance and legacy-code conversion, H2LooP claims its tools reduced the time needed for design updates and audits.

The report said H2LooP claims its generated test cases reached 90 to 95 percent accuracy in that deployment, and the company points to roughly a doubling of engineering velocity across deployments.

The AUTOSAR example anchors the product in compliance work and legacy-code conversion beyond generic code completion.

Those performance figures come from the company without an independent benchmark published with the story.

Infineon selected H2LooP for its Global Startup Program, and the India Electronics and Semiconductor Association has also recognised the startup.

YourStory did not name the German semiconductor company behind the AUTOSAR deployment.

#H2LooP #embedded systems #AI coding tools #Bengaluru startups

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