A startup called Gradient has stepped out of the shadows, revealing its mission to transform how businesses to build and harness the power of AI. Founded by Chris Chang, Mark Huang, and Forrest Moret, the company has recently secured $10 million in funding, led by Wing VC with participation from Mango Capital, Tokyo Black, The New Normal Fund, Secure Octane and Global Founders Capital, to help make this vision a reality.
The founders of Gradient hail from prominent tech giants like Netflix, Splunk, and Google. Their collective experience led them to realize that large language models (LLMs), such as OpenAI’s GPT-4, could revolutionize how enterprises operate. However, they also recognized that making the most of these LLMs required the integration of private, proprietary data, a challenge that traditional methods couldn’t effectively address.
Gradient’s main goal is to simplify the deployment of specialized and fine-tuned LLMs on a large scale. They’ve developed a cloud-based platform that allows organizations to develop and integrate numerous LLMs into a single system, making it easier for businesses to address specific tasks more effectively.
One of Gradient’s standout features is that customers don’t have to train LLMs from scratch. The platform hosts a variety of open-source LLMs, like Meta’s Llama 2, which users can adjust to meet their unique needs. Gradient also offers LLMs designed for specific purposes and industries, such as finance and law.
Gradient provides the flexibility to host and serve models through an API, similar to other AI infrastructure providers, or it can deploy AI systems within an organization’s public cloud environment, whether it’s Google Cloud Platform, Azure, or AWS. Importantly, customers maintain “full ownership” and control over their data and trained models.
So, what sets Gradient apart from other companies working on LLM integration? While there are other players in this field like Reka, Writer, Contextual AI, Fixie, and LlamaIndex, Gradient emphasizes its ability to “productionize” multiple models simultaneously. Furthermore, it prides itself on being cost-effective, with pricing based on demand, ensuring that users only pay for the infrastructure they use.
Despite the competition, Gradient is poised to benefit from the growing interest in generative AI, especially LLMs. AI has attracted a significant portion of venture capital funding, and the generative AI market is predicted to reach $42.6 billion in 2023.
Gradient has around 20 enterprise customers currently and is working to scale its cloud infrastructure. The company plans to expand its team from 17 to 25 employees by the end of the year.
In summary, Gradient is a startup that simplifies the integration of large language models (LLMs) into enterprise applications. Its cloud-based platform allows businesses to fine-tune LLMs for specific tasks and industries, making it more accessible and cost-effective. While there is competition in this space, Gradient aims to stand out by offering the ability to deploy multiple models simultaneously and focus on affordable pricing. With the growing interest in generative AI, Gradient is well-positioned to help businesses tap into the power of LLMs.