AI powered apps // use cases — startups series

sbagency
3 min readDec 3, 2023
https://pdf.ai/
https://photoai.com/
https://formulabot.com/
https://scale.com/
https://www.linkedin.com/posts/elenasamuylova_how-do-companies-actually-use-llms-in-production-activity-7137435035002949632-5hK5

How do companies actually use LLMs in production?

We updated our curated list of ML use cases (300+ case studies from 80 companies 🔥), including a bunch of new use cases on LLMs.

Here are some interesting examples we found:

🔠 Grab uses LLMs for data governance. They automatically classify data entities, such as whether data contains PII or other sensitive information.

🛍 Whatnot improves marketplace spam detection. They use LLMs to identify potentially fraudulent messages as an additional signal for their rule engine.

🏠 Nextdoor personalizes customer communications. They use LLMs to come up with interesting subject lines for emails and notifications

🧠 Instacart built an internal AI assistant called Ava. It helps in many internal processes, from code review and debugging to Slack message summarization.

🍿 Vimeo built a customer support AI assistant. Users can chat with a bot and get personalized responses based on the help center data.

I wish more companies shared pragmatic, real-life examples like this! Did we miss some great use cases? Share the links so we can add them to the next update of our database!

https://www.evidentlyai.com/ml-system-design
https://oreilly.medium.com/generative-ai-in-the-enterprise-c43d57f0f20c
https://www.oreilly.com/radar/generative-ai-in-the-enterprise/

Executive Summary

We’ve never seen a technology adopted as fast as generative AI — it’s hard to believe that ChatGPT is barely a year old. As of November 2023:

Two-thirds (67%) of our survey respondents report that their companies are using generative AI.

AI users say that AI programming (66%) and data analysis (59%) are the most needed skills.

Many AI adopters are still in the early stages. 26% have been working with AI for under a year. But 18% already have applications in production.

Difficulty finding appropriate use cases is the biggest bar to adoption for both users and nonusers.

16% of respondents working with AI are using open source models.

Unexpected outcomes, security, safety, fairness and bias, and privacy are the biggest risks for which adopters are testing.

54% of AI users expect AI’s biggest benefit will be greater productivity. Only 4% pointed to lower head counts.

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sbagency

Tech/biz consulting, analytics, research for founders, startups, corps and govs.