Brewit (YC W23)的封面图片
Brewit (YC W23)

Brewit (YC W23)

软件开发

Ask Data, Get Answers: Brewit Simplifies Data Insights for Everyone.

关于我们

Brewit enables business users to generate database queries and create dashboards through natural language, assisting them in making better data-driven decisions.

网站
https://brewit.ai/
所属行业
软件开发
规模
2-10 人
类型
私人持股
创立
2023

动态

  • 查看Brewit (YC W23)的组织主页

    1,007 位关注者

    ?? See how Taron is using Brewit to chat with his Shopify data

    查看Taron Khachatryan的档案

    Chief XR Scientist & CEO at Knoxlabs | Discover the latest in XR devices & solutions

    I made a quick app that enables me to talk to my #Shopify database like a human. We face this problem on the daily with our store, the platform is great but the reports and orders and products sections are so static, you have to generate a report each time you want to understand something and if you really want to go deep you have to download it as a csv and analyze it with excel. I am turning this into a #shopifyapp for other stores, if anyone is on Shopify and wants to use this, please ping me or + Thanks to Brewit (YC W23), I was able to put this together fairly quickly. Update: have 3 stores ready to use it, will get to 10 this week. Looking for more stores

  • 查看Brewit (YC W23)的组织主页

    1,007 位关注者

    ?? New feature: users can now see what sources are used by LLM to generate responses such as tables, metrics, verified queries, and more. Changelog: https://lnkd.in/gXVngeXz

    查看Mark (Kailing) Ding的档案

    Building OmniAI

    ?? Trusting LLM output is the #1 concern raised by our users, especially in the data world. Essentially, "How can we trust the output generated by AI"? Today, we launched an exciting new feature at Brewit (YC W23) that allows users to see what sources are used by LLM to generate responses such as tables, metrics, verified queries, and more. Users can now quickly access and review the exact data sources behind every answer directly within the chat. ??? Happy building! #data #dataanalytics #BI #ai #aianalyst

  • Brewit (YC W23)转发了

    查看Leo Lu的档案

    Partner @ Foundation Capital

    Here is how we "ate our own dog food." ?? I used Brewit (YC W23) to pull out a list of prospects who've used our app (sending 5+ messages) in the past 21 days and haven't yet subscribed to a plan. Literally took me 30 seconds to write the prompt in English and I get the exact table result I wanted :) Then the next fun part is writing personalized email to reach out to each of them, which AI app should I use? ??

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  • Brewit (YC W23)转发了

    ?? 1st feature released in May: Evaluate text-to-SQL on your DB. The most frequently asked question by new users when onboarding to Brewit (YC W23) is "How can I confidently assess Brewit's performance on our databases?". Today, we're excited to announce the launch of the Evaluation feature in Brewit! With this feature, users can: - Run custom tests on your databases: easily set up a series of questions that test the accuracy and performance of Brewit's text-to-SQL agent. - Optimize answer accuracy: add correct queries into Query Library to ensure answer accuracy in the future. - Build confidence in the model output: empower your team and data consumers to trust the model's outputs through transparent and detailed testing results. Changelog: https://lnkd.in/gk7Cfttj Try it out here: brewit.ai

  • 查看Brewit (YC W23)的组织主页

    1,007 位关注者

    ?? We're officially launched today!!!

    查看Y Combinator的组织主页

    1,237,965 位关注者

    Brewit (YC W23) allows you to use plain English to write SQL, create charts, and generate dashboards/reports based on your database. Today, if you're looking to perform analysis and make data-driven decisions, you either have to learn SQL & visualization tools or submit a ticket request to your busy data team. With Brewit, anyone can use plain English to get their data questions answered. Brewit ensures answer accuracy with a built-in data catalog, self-improving capabilities based on user feedback, and monitoring tools for the data teams. Co-founders Leo Lu and Mark (Kailing) Ding met on the first day of college and became best friends. Before Brewit, Leo and Mark both worked on data science projects at JP Morgan and Tesla respectively. Sam (Kaishan) Ding is Mark's identical twin brother who used to work at Apple as a software engineer. Together, they're building Brewit to provide conversational data analytics for every team. Learn more at https://lnkd.in/gxaGYMAn. Congrats Leo, Mark, and Sam on the launch!

  • Brewit (YC W23)转发了

    查看Leo Lu的档案

    Partner @ Foundation Capital

    ?? Our new "Drill Down" feature is now live – you can now perform comprehensive analyses with just a few mouse clicks; our AI will guide you through the process! We've realized our users love using Brewit to explore their data and get inspiration on directions for further analysis; so if you're also looking to dive one step further into your data, this feature is perfect for you! If you're interested in implementing Brewit, book a call with us, and we'll help you onboard on the same day :)

  • Brewit (YC W23)转发了

    查看Leo Lu的档案

    Partner @ Foundation Capital

    ? Introducing Recommendation Questions for All Data Sources You can now get AI-generated recommendation questions based on your data source (CSV, databases, or others) to kick-start your analytics process. This is a great way to explore your dataset and gain inspiration. Try it out today! Link in comments??

  • Brewit (YC W23)转发了

    查看Leo Lu的档案

    Partner @ Foundation Capital

    ?? If you're a startup founder who's looking for your fist BI tool, check out how I used Brewit (YC W23) to build a metric dashboard in 5 minutes. ?? Follow these 4 simple steps to get started 1. Create an account for free at https://app.brewit.ai/ 2. Connect your database and add descriptions to your commonly used tables and columns (2 minutes) 3. Start an analysis conversation with the agent and generate charts (2 min) 4. Add the charts into a dashboard (1min) We've used our app to build a dashboard that we look at EVERY DAY (user metrics, error trackings, KPIs, etc.), so I'm sure you can find some value through it as well! ??

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融资

Brewit (YC W23) 共 1 轮

上一轮

种子前

US$500,000.00

投资者

Y Combinator
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