Founder & CEO
Profile summary: Berkeley SkyDeck • Founder · MBA at Quantic School of Business and Technology
Chipchop
Chipchop provides an AI‑driven platform that automatically analyzes FPGA projects—combining RTL code, simulation results, synthesis reports, and timing data—to locate root causes of design failures such as FSM gaps, reset issues, and clock‑domain crossing errors. Engineers query the system in natural language and receive contextual explanations and fix recommendations, while the tool integrates with existing Vivado workflows and supports a human‑in‑the‑loop approval process, accelerating debug cycles by up to tenfold.
- Artificial Intelligence
- Developer Tools
Updated yesterday
Funding
Funding not disclosed
Funding rounds are not available yet.
Founders
Product
Problem
FPGA development cycles are slowed by manual, trial‑and‑error debugging, where engineers must repeatedly run simulations and manually inspect waveforms to locate issues. This process is time‑consuming, error‑prone, and often depends on a few senior experts, leading to costly delays in product delivery.
Solution
Chipchop offers an AI‑driven reasoning platform that ingests the complete context of an FPGA project—including RTL code, constraints, simulation results, synthesis reports, and timing data—to automatically pinpoint the root cause of design failures. The system traces failing signals backward through hierarchy and state machines, classifies common bugs such as FSM gaps, reset problems, and clock‑domain crossing errors, and flags non‑synthesizable constructs before place‑and‑route. Engineers interact via natural‑language queries and receive contextual explanations and recommended fixes while retaining control through a human‑in‑the‑loop approval workflow. Chipchop integrates with existing toolchains (currently Vivado, with planned support for Quartus and Lattice) and accelerates debug and iteration by 5–10× without requiring changes to the underlying design environment.
Target Audience
Primary customers are FPGA design engineers and verification teams in semiconductor companies, as well as system integrators who need rapid, reliable debugging of complex RTL projects.
Features
- Cross‑domain AI reasoning that correlates RTL, simulation, synthesis, and timing data in a single analysis step
- Waveform‑to‑RTL root‑cause tracing that follows failing signals through hierarchy, conditions, and states
- Automated classification of bugs such as FSM gaps, reset issues, CDC errors, and width truncation
- Synthesizability analysis that flags risky or non‑synthesizable constructs before synthesis
- Natural‑language interface for querying designs and receiving grounded, contextual answers
- Design exploration tools for understanding third‑party IP and unknown designs
- Tool‑agnostic integration layer that works with Vivado today and extends to Quartus and Lattice