HindArch builds AI-powered software tools that assist semiconductor engineers across prediction, RTL generation, and verification, compressing design cycles without traditional tool-flow bottlenecks
Predicts PPA metrics directly from RTL, or custom datasets without needing a full synthesis, for early and efficient design space exploration.
Generates multiple RTL variants from natural- language specifications or existing designs with intelligent EDA feedback loop.
Verifies RTL by auto-generating test cases and stimulus by integrating coverage metrics feedback for early sign-off.
HindArch builds AI-powered software tools for semiconductor chip design engineers. Our platform covers three critical phases of the design lifecycle, prediction, RTL generation, and verification. Traditional chip design is heavily dependent on expensive, time-consuming EDA tool flows. HindArch reduces these bottlenecks by cutting the number of design cycles and engineering hours needed at every stage, without locking teams into legacy tool dependencies.
HindPred enables early prediction of chip PPA metrics directly from RTL giving design teams early insight without running full synthesis flows. HindGen converts natural language specifications into RTL code and automates module scaffolding, accelerating hardware design from idea to implementation. HindVer auto-generates UVM testbenches from natural language, reducing the manual effort that makes verification one of the most time-consuming parts of chip design.
HindPred is built for flexibility. Engineers can bring their own dataset or start from a preloaded one, choose from multiple ML architectures depending on what suits their data, train and compare models side by side, and run interactive inference to test different design scenarios. The entire ML workflow from dataset analysis to prediction is guided and interactive, giving teams full control over how they generate power insights.
HindGen runs in a closed loop with EDA tools, so the RTL it produces is already checked for syntax, simulation, and synthesis feedback before it reaches the engineer. It also supports multi-file editing, pair programming, smart autocomplete, and an offline/privacy mode for sensitive designs, and connects directly with HindPred and HindVer for a continuous, end-to-end workflow.
Both. Each product delivers value on its own, but they're designed to work together. Outputs from one product line feed naturally into another, creating feedback loops that tighten the overall design cycle rather than treating each stage as an isolated, one-way step. This gives teams the flexibility to adopt one tool or the full suite.
All three products are currently under active development and will be launching soon. HindPred has validated RTL and PPA prediction on an in-house custom dataset. HindGen has validated natural-language-to-RTL conversion and automated module scaffolding using open-source EDA tools.
No. HindArch works alongside existing EDA tools. Our goal is to reduce the number of cycles and engineering hours it takes to reach a sign-off-ready design, not to replace the tools that verify it.
Engineers new to RTL design, startups building chip design capability, and teams looking to cut down engineering hours across their design pipeline.
We welcome chip design teams interested in early access, research labs looking to collaborate, and engineering leaders who want to evaluate HindArch for their design pipeline. Reach out through our Contact form with your name, company, and role — we'll get back to you directly. HindArch is built by engineers, for engineers, and every conversation helps us build better tools.
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