Delphina Raises $7.5 Million to Develop Generative AI Co-Pilot for Enterprises
In Brief
AI startup Delphina raised $7.5 million to develop its LLM-powered co-pilot, to assist companies in constructing AI models.
Artificial intelligence (AI) startup Delphina raised $7.5 million in funding from investors including Radical Ventures, Costanoa Ventures, and Stanford professor Fei-Fei Li to develop its LLM-powered co-pilot designed to assist companies in constructing AI models across various sectors, from finance to retailing.
Delphina aims to accelerate the construction and deployment of predictive AI models through its co-pilot. The company’s aims to aid enterprises lacking dedicated AI teams in deploying models for applications such as forecasting, personalization, price prediction and fraud detection by identifying and preparing the appropriate data and facilitating model training.
Founded by two former Uber data and engineering managers, known for their work “on time-of-arrival” predictions, the Silicon Valley startup intends to direct the raised capital to hire talent in the San Francisco Bay Area and accelerate product development.
“Companies sit on vast quantities of data but often find it a challenge to leverage it for AI. Large language models such as GPT-4 are now making it possible to close that gap, and Delphina accelerates the speed taken from months to days or hours.”
said Jeremy Hermann, co-founder and chief executive officer at Delphina.
The company’s ultimate goal is to enable more businesses to harness the potential of AI in their operations.
Currently engaged with five early customers, including an insurance provider, a logistics company, and an e-commerce marketplace, Delphina anticipates making its product widely available in the latter part of 2024.
LLM’s Growing Potential For Enterprises
Large Language Models (LLMs) find diverse applications across industries, efficiently recognizing, summarizing, translating, predicting and generating text and other content, based on insights derived from massive datasets.
Large enterprises equipped with substantial resources, capitalize on LLMs across various departments. They derive benefits from the flexibility to customize and integrate LLMs into existing frameworks.
In contrast, smaller enterprises, lacking the capacity to engage data scientists and machine learning engineers, strategically deploy LLMs. This may involve utilizing LLMs for customer engagement on websites, automating routine communication tasks, or extracting insights from customer feedback.
In a recent development, another AI startup Essential raised $56.5 million in funding to develop “Enterprise Brain” technology tailored for corporate functions. The company’s LLMs aim to aid users in addressing increasingly complex tasks, unlocking essential skills and amplifying organizational impact on society.
With the new investment, Delphina is set to empower more businesses to harness the full potential of AI
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About The Author
Alisa, a dedicated journalist at the MPost, specializes in crypto, AI, investments, and the expansive realm of Web3. With a keen eye for emerging trends and technologies, she delivers comprehensive coverage to inform and engage readers in the ever-evolving landscape of digital finance.
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Alisa, a dedicated journalist at the MPost, specializes in crypto, AI, investments, and the expansive realm of Web3. With a keen eye for emerging trends and technologies, she delivers comprehensive coverage to inform and engage readers in the ever-evolving landscape of digital finance.
