We're excited to share more about Adept Workflow Language (AWL). We've designed AWL to simplify the creation of AI workflows to operate across multiple business applications. Read more in our blog. https://bit.ly/4fYgSlX
About us
At Adept, we are building a future where AI helps every employee focus on meaningful work. We envision a workplace where our time is mainly spent on collaboration, creativity, and strategic decision-making. In today's digital landscape, Adept seamlessly integrates into existing workflows and business processes, executing tasks across the software tools and systems employees use every day. Powered by our best-in-class proprietary model, our tool navigates systems to extract, transform, and populate information into forms, websites, and SaaS applications reliably at scale, all while adhering to a company’s business rules and processes. With Adept completing these manual, repetitive workflows, employees can use the gift of time to focus on more strategic work. Companies can rest easy knowing that processes are being executed exactly the way they want, every time. Adept is the enterprise AI tool that powers your workforce.
- Website
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https://www.adept.ai
External link for Adept
- Industry
- Software Development
- Company size
- 51-200 employees
- Headquarters
- San Francisco, CA
- Type
- Privately Held
- Founded
- 2022
Locations
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Primary
Get directions
San Francisco, CA, US
Employees at Adept
Updates
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Today, we’re announcing some updates to our strategy and some changes to our leadership and team. More details are in our blog: https://lnkd.in/gNVvAr-F
An Update to Adept
adept.ai
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Excited to share that for the second year, Adept has been listed on the Forbes AI 50. Big thanks to our incredible team for all the hard work! Check out our open roles to join us! https://lnkd.in/gTwYQfpw https://lnkd.in/eT2MhX_f
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Introducing Fuyu-Heavy, our newest multimodal model. Fuyu-Heavy is the world’s third-most-capable multimodal model, behind only GPT4-V and Gemini Ultra, which are 10-20 times larger. In particular, it outperforms Gemini Pro at both MMLU and MMMU. Training Fuyu-Heavy wasn’t easy - in addition to the standard hiccups with model scaling, we had to deal with the extra problems associated with training a new architecture on both text and image data. Here’s a blog post if you want all the details: https://lnkd.in/gHeUbqRn We’re working on further scaling up these models and building useful software agents around them - if that sounds exciting to you, please reach out at https://lnkd.in/eT2MhX_f