LLM Fine-Tuning Startup OpenPipe Raises $6.7 Million
Leaders from OpenAI and GitHub back tool that simplifies the deployment of smaller, specialized LLMs
Seattle-based LLM fine-tuning startup OpenPipe announced the closing of a $6.7 million seed round. OpenPipe makes a tool that lets developers create their own application-specific Large Language Models (LLMs). The funding round was led by Costanoa Ventures, with participation from Y Combinator and prominent angel investors, including Logan Kilpatrick, former head of developer relations at OpenAI, Alex Graveley, creator of GitHub Copilot, and Tom Preston-Werner, co-founder of GitHub. The funds will be utilized to scale its team and accelerate product development.
OpenPipe’s key insight is that smaller models can match or exceed the performance of much larger ones when specialized to a specific task. This specialization is done through a process known as “fine-tuning.” Fine-tuning massively improves response quality and correctness, but many developers aren’t able to perform this task because of the complex workflow required. Existing tools are designed for engineers with specialized knowledge and skills in machine learning, which limits teams and organizations without a dedicated specialist. OpenPipe provides an easy-to-use tool that enables everyday developers to train and deploy fine-tuned models faster, more cost-effectively and with greater accuracy.
OpenPipe works by integrating into a customer’s existing codebase to collect their existing prompts, which are then used as training data to fine-tune a much smaller, more specialized model. Developers can then use the fine-tuned model as a drop-in replacement for their existing prompts.
“The biggest challenge we see for developers deploying LLM applications today is going from proof of concept to usage at scale,” said Kyle Corbitt, co-founder and CEO of OpenPipe. “OpenPipe enables teams to easily convert their prompts into production-ready fine-tuned models. These fine-tuned models allow developers to deliver a much snappier user experience at a much lower price point, without sacrificing quality.”
OpenPipe’s active customer base includes startups and enterprises that use fine-tuned models to perform critical business workflows, like translating and extracting information from government regulations, categorizing and filtering YouTube videos based on transcripts or routing inbound customer service requests to the appropriate teams. OpenPipe has saved customers over $3M in inference costs since September 2023.
“OpenPipe is paving the way for greater accessibility and usability of large language models,” said Tony Liu, Partner at Costanoa Ventures. “This investment underscores our belief in the profound impact OpenPipe will have in enhancing the productivity of developer teams and their ability to launch competitive go-to-market applications faster and with more precision.”
Headquartered in Seattle, the company was founded by brothers Kyle Corbitt and David Corbitt, who both honed their skills at top tech companies, including Google, Palantir and Qualtrics. Kyle also led Y Combinator’s Startup School team serving over 100,000 startup founders worldwide. The company is partnered with several industry leaders to provide fine-tuning like Langfuse and Athina AI for data collection, and OctoAI and Fireworks AI to serve the completed models.
OpenPipe is a tool that simplifies Large Language Model (LLM) integration for developers in production applications. Its platform allows developers to fine-tune models for accuracy, reducing latency and costs, enabling full-stack and AI engineers and developers to successfully train and deploy fine-tuned models without relying on data science and machine learning specialists. The company is based in Seattle and was founded by a team of experienced engineers, brothers Kyle Corbitt and David Corbitt.
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