Alkemi– Bridging the Gap Between Data Providers and AI Developers.

Data providers want to sell the data AI developers need. So, why hasn’t a thriving AI data market emerged? At its core, this is a problem of product-market fit.

Since the release of ChatGPT, the AI landscape has evolved rapidly. Pre-trained models and Retrieval-Augmented Generation (RAG) frameworks have democratized access to AI tools, empowering over 30 million developers to build commercial AI applications and in-house AI solutions in pursuit of a $200 billion market.

However, these AI developers have vastly different resources and needs than foundational model providers. Today, 90% of AI projects use off-the-shelf models, which developers augment with proprietary data to generate intelligence tailored to their domain-specific needs.?The widespread adoption of off-the-shelf models and RAG frameworks shifted 95% of AI spending from training to inference, dramatically expanding the market for inference data.

With over 300,000 third-party data providers offering high-leverage insights on consumer behavior, like how many Pampers size fives Target sold last May, to global logistics data measuring the time it takes a Toyota Prius to ship from the Port of Nagoya to Long Beach, and much more—these resources remain underutilized in AI due to difficulties in sourcing, accessing, and integrating them.

The data market has been slow to adapt to AI buyers that primarily need data for augmentation, not training, and access pre-trained AI services on-demand through APIs. Consequently, most data providers still sell and deliver products designed for a training-data market that never materialized. This mismatch creates bottlenecks, preventing developers from accessing the critical data needed to build industry-specific solutions. Alkemi is here to change that, simplifying data access and eliminating these barriers.

While working at Amazon, I witnessed the challenges brands faced in turning high-leverage digital exhaust into actionable insights. This realization drove me to co-found Downstream in late 2017, where we empowered brands with insights and machine learning automation to measure and optimize their growth on ecommerce platforms like Amazon and Walmart.

In 2021, Downstream was acquired by Jungle Scout , creating the industry's largest ecommerce data asset and most comprehensive suite of tools. This merger allowed me to focus on our growing Data-as-a-Service (DaaS) business and how data products could better support businesses in their AI-driven goals.

Abundant data supply and booming demand for domain-specific AI solutions provided the ingredients for a massive AI data market. Yet, the anticipated deluge of AI data buyers never materialized. I became obsessed with understanding the product inefficiencies that prevented AI developers from tapping into the DaaS market.

By a stroke of serendipity, my far more talented brother Maxwell Folley recently sold the company he founded, Caravel . As an early machine learning pioneer, Max encountered similar challenges in developing AI solutions for firms like Samsung, Brex, Verizon, and Yahoo. Our combined experience and expertise laid the perfect foundation for Alkemi .

Alkemi is bridging the gap between data providers and AI developers, making world-class data accessible to every AI builder with a vision to create something extraordinary. We are focused on simplifying external data access, integration, and use for the millions of developers empowered by the modern AI stack to address new verticals. Our platform allows data providers to offer AI-ready data on demand through RAG-compatible APIs, safeguarding intellectual property while enabling developers to easily access and integrate high-quality data.

The result? A more efficient, vibrant AI ecosystem where developers can focus on innovation and data providers can unlock the AI market’s full potential. At Alkemi, we are on a mission to put world-class data into the hands of those who can build amazing things.