HindArch builds AI-powered software tools that assist semiconductor engineers across prediction, RTL generation, and verification, compressing design cycles without traditional tool-flow bottlenecks
Built for the next generation of intelligent hardware
From defence electronics to edge AI, every application demands efficient, reliable hardware. HindArch simplifies the journey from design requirements to verified RTL through AI-driven generation, early PPA prediction, and automated verification, helping engineering teams explore more possibilities with less manual effort.
Early PPA prediction, straight from RTL
AI-driven RTL generation from specifications
Automated, coverage-driven verification
Onboard processors and payload electronics run on tight power and area budgets, and once a satellite is launched there is no chance to fix the silicon.
Estimate power and area early, so designs fit strict satellite power and mass budgets.
Generate RTL variants for payload data-handling, telemetry and communication blocks.
Push coverage towards closure before tape-out, where a post-launch fix is not an option.
ASIC and SoC teams weigh many architecture options against tight schedules, and every RTL iteration through synthesis costs time.
Compare PPA across architecture options straight from RTL, before a full synthesis run.
Turn specifications into multiple RTL variants and scaffold new modules faster.
Auto-generate test cases and stimulus, with coverage feedback for earlier sign-off.
Radar, secure communications and electronic-warfare systems demand reliable hardware, long lifecycles and tight control over sensitive design data.
Evaluate PPA trade-offs for signal-processing and control logic early in the design.
Generate RTL with privacy controls, including an offline mode for sensitive programmes.
Explore corner cases and track functional coverage for mission-critical designs.
Basebands, packet processing and high-speed interfaces have to deliver more throughput every generation while staying inside power and thermal limits.
Predict PPA for DSP and datapath-heavy blocks before committing to an architecture.
Explore several micro-architecture variants of the same specification side by side.
Describe protocol scenarios in natural language and track coverage as interfaces evolve.
On-device inference accelerators must deliver performance within milliwatt power budgets and tight cost targets.
Explore accelerator design spaces quickly by ranking variants on predicted PPA.
Generate and iterate on compute and dataflow RTL from natural-language specifications.
Verify datapaths and control logic with coverage-driven test refinement.
Avionics and flight-control electronics must meet strict reliability and size, weight and power targets, with every design decision open to review.
Assess PPA trade-offs early to meet size, weight and power targets.
Move from written requirements to RTL variants faster, with the specification as the starting point.
Build thorough, coverage-tracked verification that supports design assurance.
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.
Building something in chip design? Let's talk.
