The Alternative AI Architecture That Creates Certainty and Trust - No More Guesses.
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BOSTON, May 6, 2025 ~ In today's world, the adoption of artificial intelligence (AI) has become increasingly prevalent. However, one of the biggest challenges in this adoption is the potential for inaccurate or unreliable results. This risk is especially concerning in regulated industries such as healthcare, pharmaceuticals, finance, legal, publishing, and higher education where errors can have severe consequences. To address this issue, Gyan has developed a solution that enterprises can trust.

Steve Hill, Senior Vice President of Engineering at Macmillan Learning, recognizes the importance of trust and transparency in AI. He states, "At a time when trust and transparency in AI are more important than ever, we're excited to partner with Gyan to explore a more explainable and dependable approach to language models." Gyan's solution gives businesses full control over their data while keeping it private and secure. This makes Gyan a trusted partner for enterprises where reliability and accuracy are mandatory.

Unlike other language models on the market, Gyan's model does not have the potential to make things up. It is built on a neuro-symbolic architecture rather than being transformer-based. This ground-up design ensures that there are no hallucinations or privacy risks associated with using Gyan's model. Joy Dasgupta, CEO of Gyan explains, "If the cost of a mistake is high, you certainly don't want your AI causing it." He further adds that Gyan was specifically built for companies and processes with zero tolerance for hallucination and privacy risks while also being more energy-efficient than current language models.

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Gyan's language model has already proven its efficacy in two key life sciences benchmarks - PubMedQA and MMLU. The company provides full details on its State of the Art performance on its website. Additionally, every inference made by Gyan's model is traceable with full reasoning to exact ideas and arguments in the result. This makes them easily verifiable - something that cannot be said for other models on the Leaderboard.

Gyan's language model is currently being deployed in various mission-critical use cases across industries. This is because trust and provenance are critical in all knowledge work. Raj Echambadi, Ph.D., President of Illinois Institute of Technology in Chicago, recognizes the transformative potential of AI in education. However, he also acknowledges the limitations that current AI advancements face, including hallucinatory tendencies, non-transparency, and unreliable provenance. To address these issues, the institute is collaborating with Gyan to leverage its innovative language model that is explainable, transparent, and energy-efficient while also integrating learning science principles.

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Gyan's precise and accurate analysis has already been put to the test by Accelera. Elena Giannotti, Head of Preclinical Development at Accelera, shares her experience working with Gyan on their AI-powered medical writing product. She says, "We had the opportunity to collaborate with Gyan for the generation of nonclinical study documents using their AI-powered medical writing product." Giannotti further adds that Gyan was able to quickly adapt their solution to Accelera's templates and structures while delivering clear and timely reports.

In a world where trust and accuracy are crucial factors in decision-making processes, Gyan's language model provides a reliable solution for enterprises across various industries. With its proven efficacy and focus on transparency and explainability, Gyan is paving the way for a more trustworthy future for AI adoption.
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