Whalechip Deploys ChipAgents AI Platform to Accelerate Semiconductor Chip Debugging

ChipAgents, the category leader for Agentic AI platforms in the semiconductor design industry, announced that Whalechip has successfully deployed ChipAgents' AI-powered platform, which immediately paid dividends during a recent critical chip debugging effort. Using ChipAgents, the Whalechip engineering team was able to rapidly identify critical design issues in a new chip and significantly reduce the time required for root cause analysis.

"The semiconductor industry doesn't have a chip shortage problem. It has an engineering productivity problem," said William Wang, Founder and CEO of ChipAgents. "Engineering teams often spend days searching through logs, waveforms and fragmented design data trying to understand why a system failed. Whalechip's deployment demonstrates how domain-specific AI can dramatically reduce the time required to identify and resolve critical design issues."

When Whalechip engineers encountered a complex issue with a new chip design, they faced limited visibility into the source of the problem and were forced to rely on logs and indirect system signals to piece together what was happening inside the design.

Whalechip deployed ChipAgents' autonomous platform, which uses specialised semiconductor AI agents to analyse unstructured engineering data and generate actionable debugging insights. During a 60-hour debug effort, the platform identified three complex structural pitfalls, including gated clock conversion, clock self-brick and removal violations, and uncovered four critical bugs within a customer memory controller, including a hidden three-cycle race condition that would have been difficult and time-consuming to diagnose through traditional methods.

"As chip designs grow more complex, root cause analysis has become a critical bottleneck in development. As a company with hands-on 3DIC and Wafer-on-Wafer mass production experience, ChipAgents enabled us to isolate design bugs significantly faster, a capability that will only grow more important as 3D stacked die interactions introduce ever-greater debugging complexity," said Thomas Tsai, CEO at Whalechip.

The results were significant. By replacing manual waveform analysis and log review with AI-driven root cause analysis, Whalechip reduced per-round RCA cycles from days to as little as 15 to 60 minutes. The platform achieved a 100% hit rate in identifying the underlying issues and helped prevent an estimated one to two weeks of project delays.

Whalechip's deployment highlights a growing challenge facing the semiconductor industry. As chip designs become larger and more sophisticated, verification, debug, and root cause analysis continue to consume a significant portion of engineering resources. While much of the industry's AI conversation has focused on code generation and design automation, many engineering organisations are increasingly looking to AI to help accelerate the identification and resolution of complex design and verification issues.

Unlike general-purpose coding assistants, ChipAgents is purpose-built for semiconductor engineering and designed to work across specifications, simulation logs, waveforms, verification environments and other specialised workflows. The platform transforms specifications and code into production-ready RTL, verification assets and automated root cause analysis, helping engineering teams accelerate development while reducing time spent on repetitive manual tasks.