Deploy Machine Learning Models with One Command

PoplarML lets you deploy any machine learning model to a fleet of GPUs as a ready-to-use and scalable API endpoint with one command.

Team Size:2
Location:San Francisco
Group Partner:Dalton Caldwell

Active Founders

Danna Liu

Co-Founder of PoplarML, Previously Research @ Snap, SWE @ Stripe, Coinbase, Microsoft, PagerDuty

Evan Chu

Co-Founder @ PoplarML. Previously SWE @ Stripe, Amazon, AWS

Company Launches

πŸ‘‹ Hey Everyone, this is Danna and Evan, and we’re super excited to introduce PoplarML!

πŸ“– TL;DR

Building deployment infrastructure for machine learning models is difficult and time-consuming. With PoplarML, you can replace that process with one simple command. We handle all of the infrastructure to deploy and serve at scale, enabling you to focus on building your product.

❌ The Problem

AI-powered products have grown in popularity but many are deterred by the challenges to bring their models to life. Deploying a machine learning model to production is complex and requires a heavy engineering lift. Building the infrastructure to support ML models takes days, increasing the time to ship your product.

⚑ The Solution

PoplarML helps teams easily deploy custom machine-learning models to production. With one simple CLI command, you can turn your model into an API endpoint that you can integrate with the rest of your product. Our endpoints come with auto-scaling out of the box, ensuring low-latency when there are bursts of requests to your model.

PoplarML can deploy any custom model, regardless of the framework used. Some examples of models that our customers have deployed on PoplarML are:

  • Flan-T5-XXL
  • Whisper
  • Stable-Diffusion-2

πŸ€– How it Works

  1. ✏️ Define a Load and Predict function in a main.py file
  2. πŸ’» Use our CLI tool to pick a GPU instance and deploy your model
  3. πŸš€ Use the returned API endpoint in your product

πŸ’‘ Why PoplarML was Built

We have personally felt the pain of deploying models to production and have previously built ML deployment infrastructure at companies such as Amazon and Snapchat. With PoplarML, we would like to provide a better and more streamlined experience for ML development.

πŸ™Œ Our Asks

  • Reach out via our contact us form or book a time directly on our calendly if you want to try PoplarML
  • Share this with anyone you know building AI-powered products or companies
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