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Singapore's Vinci Raises $36M to Cut Chip Simulation Time by 90%

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  Published in Business and Finance on Tuesday, December 2nd 2025 at 9:01 GMT by Channel NewsAsia Singapore

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Vinci: Singapore‑based Hardware‑Simulation Pioneer Secures $36 Million to Accelerate Chip Design

In a move that signals a growing appetite for “AI‑accelerated” design tools, Singapore’s own software firm Vinci announced a $36 million Series B funding round on Thursday. The capital injection—led by Singaporean venture group GV (formerly Google Ventures) and Singapore’s sovereign‑wealth fund Temasek**—will help the company scale its platform that promises to slash the time it takes to run hardware simulations by up to 90 percent.

The Core Problem: Time‑Consuming Simulations

Modern silicon design is a complex choreography of logic, timing, and power analysis. Engineers rely on electronic design automation (EDA) tools to simulate every possible signal path in a chip—an exercise that can take days or even weeks. The longer the simulation, the slower the feedback loop for designers, and the higher the cost of a single iteration. Even a small mis‑timing bug can propagate into a costly production defect, especially for high‑volume applications such as AI accelerators, 5G modems, and automotive safety chips.

Vinci tackles this bottleneck by applying machine‑learning models that approximate the results of a full simulation without having to run it in its entirety. By training on a vast corpus of pre‑existing simulation data, the platform predicts the most critical paths and timing margins, allowing designers to focus their resources where it matters most.

“Our goal is to make chip design less of an art and more of a repeatable engineering process,” CEO Daniel Chew told reporters. “With the right level of confidence, our predictive engine can reduce simulation cycles from weeks to hours.”

Product Highlights

• Hybrid AI‑Simulation Engine – The core engine combines deterministic simulation with neural‑net‑based predictions, offering a trade‑off between speed and precision that can be tuned per project.
• Integrated Tool‑chain Compatibility – Vinci’s API works seamlessly with popular EDA suites such as Cadence, Synopsys, and Mentor Graphics, enabling companies to plug it into their existing workflows without a full re‑tooling effort.
• Cloud‑Ready Architecture – By offloading heavy computations to the cloud, the platform eliminates the need for on‑premise HPC clusters, which are both expensive and difficult to maintain.
• Real‑Time Debugging – Designers receive instant feedback on potential timing violations, allowing iterative refinement in the same session rather than after a full simulation run.

The company’s beta customer list includes names such as Samsung Electronics, Qualcomm, and Sony Semiconductor Solutions, all of whom have reported a 70 % reduction in their simulation cycle time during pilot deployments.

Funding Landscape and Investor Appetite

The Series B round was closed with participation from:

• GV – The venture arm of Alphabet, which previously invested in SiFive and Graphcore.
• Temasek – Singapore’s leading sovereign‑wealth fund that has shown strong interest in EDA and semiconductor startups.
• GV Spark – An accelerator program that focuses on early‑stage AI startups in Singapore.
• Private investors – Several prominent Singaporean angels, including former NXP executives, joined the round.

Total funding raised to date now sits at $75 million across two Series A and Series B rounds, positioning Vinci as one of the most heavily backed hardware‑automation startups in Southeast Asia.

“The interest we’re seeing from global silicon players validates the scalability of our approach,” said Mohan Radhakrishnan, a Temasek representative. “We’re excited to see how Vinci’s AI can lower the barriers to entry for smaller fabs.”

Leadership and Team

Vinci was founded in 2019 by Daniel Chew (former software architect at Synopsys) and Anita Tan (previously a senior engineer at ARM). The founding team’s combined experience in ASIC design and AI research fuels the company’s dual focus on hardware performance and machine‑learning rigor.

The engineering squad currently comprises 48 full‑time staff, including 18 data scientists, 14 hardware engineers, and 6 cloud architects. The company is also investing heavily in talent acquisition, hiring from top universities like NUS and MIT, to keep pace with its ambitious roadmap.

Competitive Landscape

While giants like Cadence and Synopsys dominate the traditional EDA market, they have historically been slow to adopt AI‑based optimization. Vinci’s approach is uniquely positioned as it targets the simulation bottleneck—an area that even the largest EDA players treat as a “nice‑to‑have” rather than a core differentiator.

Other emerging players, such as Simul8 and Arianna (a U.S. AI‑EDA startup), are also pursuing similar AI‑enhanced simulation promises. However, Vinci’s early integration with the most widely used EDA suites and its cloud‑native design give it a practical advantage for companies that cannot afford to overhaul their existing toolchains.

What’s Next for Vinci?

The newly secured $36 million will be allocated across three main initiatives:

1. Product Expansion – Adding support for analog and mixed‑signal simulation, a critical frontier for IoT and automotive chips.
2. Internationalization – Setting up a dedicated sales and support team in the U.S. and China to tap into the largest silicon markets.
3. Research & Development – Building a partnership with Singapore’s Agency for Science, Technology and Research (A*STAR) to explore next‑generation neural‑net architectures for hardware prediction.

Chew highlighted that the company also plans to open an AI‑powered simulation lab at the Nanyang Technological University (NTU) to foster academic collaboration and accelerate the development of new algorithms.

Bottom Line

Vinci’s success illustrates a broader shift in the semiconductor industry: an increasing reliance on AI to streamline traditionally labor‑intensive processes. By turning what used to be a multi‑week simulation into a matter of hours, the company is not only cutting costs for its customers but also accelerating time‑to‑market for innovative silicon products.

With the latest round of funding, Vinci is poised to scale its technology, expand its customer base, and potentially disrupt the long‑standing dominance of traditional EDA giants. For chip designers and semiconductor firms alike, Vinci’s promise of rapid, accurate simulation may soon become a standard part of the design toolkit rather than a niche niche.

This article is based on coverage from Channel News Asia, featuring an interview with CEO Daniel Chew and press releases from Vinci.