Chip design takes years, large teams, and iterations. A new approach uses AI to handle decisions, reduce effort, and speed up development across the system.
Tattvam AI is being built to fundamentally reduce the complexity of chip design, enable faster development cycles, and make it possible to design the growing range of silicon the world demands.
Chip design is enormously complex. A single chip requires hundreds of engineers and thousands of iterations over years before reaching tapeout. Countless engineering hours are spent on tasks that are manual and repetitive. A late-stage change does not just delay progress, it cascades across the entire system.
Designing a chip requires millions of interdependent trade-offs across power, performance, and area. These decisions cannot be solved algorithmically using existing tools alone. They require a holistic understanding of architecture, design intent, and physical constraints.
Today, these decisions are distributed across hundreds of engineers working in specialised teams. Important decisions get split across flows, and coordination adds overhead. Only the most consequential decisions should require expert engineer intervention.
Tattvam AI is built for chip design architects, RTL and physical design engineers, verification teams, and semiconductor startups building new silicon. It can also be used by system companies developing custom chips and research teams exploring new architectures.
Using Tattvam AI, teams can explore design trade-offs across power, performance, and area with a unified view. The system can automate repetitive design decisions, suggest design changes based on intent, and adapt to late-stage modifications without cascading delays. Engineers can use it to evaluate multiple design paths, reduce iteration cycles, and keep consistency across teams and stages of design.
At the core, the system reasons from first principles. It understands the design structure and intent, and aims to make the majority of these decisions autonomously while keeping engineers in control of critical choices.
This is a small team working on a hard problem. They are looking for chip design architects, AI researchers, and engineers who think from first principles and want to push what AI can do in semiconductor design.
