Veritas expands its anti-counterfeit chip to jewelry, trophies, and fragrance bottles; plus, Elorian’s first AI model wants to reason with images

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1:13That's Framer.com slash tcstartups rules and restrictions may apply. Counterfeits of luxury goods are a major problem for fashion houses. Counterfeiters are getting better at replicating brands' marks and passing off dupes known as superfakes as genuine items. A startup called Veritas wants to tackle the problem with its own chip that verifies goods. Veritas was founded by Lucy Holland, a former Tesla technical product manager who also has a background in design and art. Its chip is built to be easily inserted into products without damaging them. Brands can use it to verify whether a product is the real deal, and customers can show a certificate of ownership through the company's app.

2:02Holland said other approaches are easier to defeat because a digital record can be reproduced through a copied QR code or static NFC link. Holland said, Our approach combines secure, authenticated chip responses with integration into the product itself. Our chip generates a secure response with each tap and includes a tamper detection wire. We make the connection between the object and its digital identity part of the proof. The Veritas founder told TechCrunch over email that the company has just introduced the second version of its chip, which works on metal surfaces and can be scanned through glass.

2:43She said, The next-generation chip is ready for production and supports a broader range of applications. including jewelry, trophies, hard surface products, and glass objects such as fragrance bottles. Alongside our garment integrations, this gives brands more ways to incorporate authentication directly into their products. Just last week, the startup announced a partnership with Athlos, a women's track and field competition founded by Reddit co-founder Alexis Ohanian, who is also an investor in Veritas. As part of the partnership, all 18 championship crowns will include Veritas' chips so they can be verified.

3:25The company also embedded a chip into a pair of LeBron James' first Nike shoes, reimagined by artist Adam Port. Tapping a phone to the shoe brings up its history and story. The company has so far raised$1.75 million in pre-seed funding, led by Ohanian's venture firm, 776, with participation from DoorDash co-founder, Stanley Tang, Gloria Zhu, co-founder of skincare brand, Ray's, and former TechCrunch editor, Josh Constine. Since its February fundraise, the company has shipped an iOS app for consumers and a brand portal that lets companies manage product records and build owner experiences. Through the app and the portal, brands can offer experiences such as clubs, event check-ins, and segmented early access to product drops.

4:21Well, TechCrunch exclusively learned that Elorian, the Palo Alto AI startup that raised a$55 million seed round at a$300 million valuation before it launched a product, released its first model on Friday. The model, Glimpse, is launching as a research preview with API access and a chat interface. The thesis? Today's AI models, for all their skill with language and code, still cannot really see. Most multimodal models look at an image once, convert it to tokens, and then reason about it in text, like describing a photo from memory. Glimpse keeps going back to the source. Mid-reasoning, it can crop into a region, pull specific frames from a video, or run code to measure or compare what it's looking at, a mechanism Elorian calls a visual scratch space.

5:19Think of it as someone pinching to zoom on a phone photo to double-check what they thought they saw. For former Google DeepMind researcher and Elorian CEO Andrew Dye, one of the clearest signs that AI still could not really see came on game night. Last year, he photographed a board game he'd just finished with friends and asked a frontier model who was winning. It couldn't say. Board games each have their own visual language. Each have their own iconography, symbols, he told TechCrunch. To an adult, it's quite easy to understand what's going on with minimal text, but these models are not able to intuit what the symbols mean.

6:01Humans can look at IKEA diagrams with no text and assemble IKEA furniture, right? Why can't AI models? The approach is not completely new. OpenAI added crop and zoom during reasoning to its O-series models in 2025. But Elorian's pitch is that it built the whole model around it, cheaply. The company says a small team trained glimpse on a few hundred GPUs and that the model is substantially smaller than the frontier systems it's benchmarked against. Glimpse costs$0.60 per million tokens in and$3 per million tokens out, cheaper than mid-level models like Sonnet and Sol, but more expensive than lightweight models like Haiku and Luna.

6:47But according to Elorian's evaluations, Glimpse outperforms even GPT-6 Astra on scientific chart reasoning and short-form video captioning, with competitive results on other visual reasoning tasks. Elorian came out of stealth six months ago, with a round co-led by Striker Venture Partners, Menlo Ventures, and Altimeter Capital, with participation from NVIDIA and Google chief scientist Jeff Dean. The initial targets are companies sitting on lots of video, robotics firms, scientific labs, media, and creative companies. Longer term, Elorion wants to move from seeing to doing. That means building a model of a scene using that to choose an action, including directly controlling robots.

7:31Next year, I said, the company aims to build the world's best visual reasoning model, one that leads on every visual reasoning test. That's all for now. For the latest on startup tech news, go to TechCrunch.com.

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