SixSense, a Singapore-based startup that applies artificial intelligence (AI) to semiconductor manufacturing, has closed a US$8.5 million investment round led by Peak XV’s Surge.
Alpha Intelligence Capital, Febe Ventures, and other unnamed investors also participated.
Founded by engineers Akanksha Jagwani and Avni Agarwal, SixSense directly addresses one of the semiconductor industry’s most formidable challenges: transforming vast quantities of raw production data–ranging from intricate defect images to precise equipment signals–into actionable, real-time intelligence.
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This intelligence is critical for factories to pre-empt quality issues, enhance throughput, and ultimately produce a greater number of high-quality chips from existing production lines.
The demand for advanced chips is escalating rapidly, driven by emerging technologies such as AI, 5G, the Internet of Things (IoT), and electric vehicles. Chipmakers are under immense pressure to design and manufacture smaller, more intricate chips, leaving significantly less margin for error.
“Making a single chip is one of the most demanding feats in modern manufacturing; it happens in cleanrooms thousands of times cleaner than hospital operating rooms and relies on precise coordination across hundreds of machines and thousands of ultra-sensitive steps,” said Akanksha Jagwani, co-founder and CEO. “Imagine trying to build a skyscraper out of microscopic Lego blocks, where a tiny shift in one brick–invisible to the eye–can collapse the whole structure. That’s what chip factories face every day.”
Identifying early indicators of potential failure before they escalate into costly defects or delays remains a significant hurdle, making AI an indispensable tool for the industry.
The SixSense AI platform empowers engineers with the crucial early warnings to address problems proactively. It achieves this by analysing massive volumes of production data to detect, classify, and predict failure patterns, thereby enabling factories to transition from reactive inspection processes to proactive control mechanisms.
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With the SixSense platform, manufacturers gain the ability to:
- Catch rare, minute, and critical defects that often elude human detection.
- Avoid over-rejecting perfectly good chips, consequently boosting usable output, commonly known as yield.
- Predict process drifts before they precipitate larger, more significant failures.
Avni Agarwal, Co-founder and CTO, added: “Unlike traditional AI tools, SixSense is hardware-agnostic, explainable, and built for engineers, not data scientists.” This design philosophy ensures that process engineers can fine-tune models using their proprietary fab data, deploy them in under two days, and trust the results – all without the need to write a single line of code. “That’s what makes the platform both powerful and practical.”
The platform has already established a presence globally, powering inspection lines at leading semiconductor manufacturers, including GlobalFoundries and JCET. According to SixSense, its customers have processed 100 million chips through the system, consistently achieving “substantial benefits”.
These typically include:
- 30 per cent faster production cycles.
- 1-2 per cent higher yield through the recovery of chips that would otherwise have been incorrectly rejected.
- Up to 20 per cent fewer errors and more than 90 per cent less manual effort.
Furthermore, the SixSense platform is well-integrated with major inspection equipment vendors, collectively covering over 60 per cent of the market.
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The new funding round is set to fuel SixSense’s ambitious expansion plans.
The company intends to:
- Expand its footprint into key chipmaking hubs across Malaysia, Taiwan, and the United States.
- Forge deeper partnerships with more AI-first inspection equipment makers to deliver enhanced on-the-ground AI integration.
- Invest significantly in next-generation research and development (R&D), transitioning from isolated inspection tools towards comprehensive line-level intelligence. This future development aims for multiple machines to communicate with each other through AI, optimising factory-wide decisions in real time.
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