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Skyvern

Skyvern

Open Source AI Agent to automate browser workflows via an API

Skyvern helps companies automate browser based workflows using LLMs and Computer Vision, fully automating manual workflows and replacing brittle or unreliable scripts. Examples include: 1. Automating materials procurement from commerce websites 2. Completing complex multi-step workflows (ie getting an insurance quote from Geico.com) 3. Automatically logging into portals and downloading invoices 4. Navigating legacy content systems to do data extraction or data entry

Skyvern
Founded:2023
Team Size:3
Location:San Francisco
Group Partner:Nicolas Dessaigne

Active Founders

Suchintan Singh

I'm the founder of Skyvern. We help companies automate complex workflows using AI agents and computer vision. In the past, I've built the ML Platforms at both Faire and Gopuff, which generated over $100M of GMV across their two businesses, I also love bad jokes and puns, so if you have any or are in the need of any feel free to hit me up!

Suchintan Singh
Suchintan Singh
Skyvern

Shuchang Zheng

I am the CTO and cofounder of Skyvern. For the past 5 years, I've been building developer and platform tools. At Lyft, I built testing tools (simulation platform, load test framework, and end to end test framework) used by 1000+ engineers to boost dev productivity, ensure Lyft doesn't go down during peak events, and reduce infra cost. At Patreon, I helped scale the payment and db infra to process 20M+ transactions per month and free 100+ engineers from the 3-day monthly code freeze

Shuchang Zheng
Shuchang Zheng
Skyvern

Company Launches

TL;DR

Skyvern helps companies automate browser-based workflows using LLMs and computer vision. We provide a simple API endpoint to fully automate manual workflows, replacing brittle or unreliable scripts.

🤔 What are browser workflows?

Most companies we’ve talked to have manual or semi-automated workflows that support their core product. Many of these workflows started manually as companies were getting off the ground, doing things that don’t scale, and evolved to occupy a larger amount of human capital or automated with unreliable scripts.

Example 1 — Automating materials procurement from commerce websites

Let’s say you’re a B2B marketplace for car parts, and your users submit orders from multiple vendors with you. A subset of vendors you work with don’t support ordering via an API, so you have a human in the loop to transact orders for those vendors. Here’s an example of Skyvern navigating to finditparts.com and ordering an airbag — all via an API call!

Example 2 — Completing complex multi-step workflows

Let’s say you’re trying to automate complex workflows such as generating insurance quotes. Skyvern can navigate each step until its specified goal is achieved — even if the steps change depending on the user’s situation. Here’s an example of Skyvern navigating to Geico.com and generating an auto insurance quote with your personalized information.

🤩 How does it work??

Our focus is bringing stability to browser-based workflows. We leverage LLMs to create an AI Agent capable of interacting with websites like you or I would — all via a simple API call.

Traditional approaches required writing custom scripts for websites, often relying on DOM parsing and XPath-based interactions which would break whenever the website layouts changed.

Skyvern operates like a human — increasing reliability by not relying on fragile scripts, instead relying on computer vision to parse items in the viewport and interact with them the way a human would.

This approach gives us a few advantages:

  1. Skyvern can operate on websites it’s never seen before, as it’s able to map visual elements to actions necessary to complete a workflow, without any customized code
  2. Skyvern is resistant to website layout changes, as there are no pre-determined XPaths or other selectors our system is looking for while trying to navigate
  3. We’re able to circumvent or navigate through many bot detection methods as many of them rely on allowing people to access the websites
  4. We rely on LLMs to reason through interactions to ensure we can cover complex situations. Examples include:
    • If you wanted to get an auto insurance quote from Geico, the answer to a common question “Were you eligible to drive at 18?” could be inferred from the driver receiving their license at age 16
    • If you were doing competitor analysis, it’s understanding that an Arnold Palmer 22 oz can at 7/11 is almost definitely the same product as a 23 oz can at Gopuff (even though the sizes are slightly different, which could be a rounding error!)

Our Ask

Do you have any complex workflows that you’d love to automate? Were you doing things that don’t scale that you now need to scale? We’d love to chat! Shoot me an email at suchintan@skyvern.com or grab some time via my calendar.

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