p/einblick-analytics Data notebooks that solve any problem with just one sentence

Einblick Prompt AI - Data notebooks that solve any problem with just one sentence

Einblick AI

Tell your data notebook what to do. Meet Einblick, the AI-native notebook that writes and fixes code, plots beautiful charts, builds models, and much more. Provide a prompt and Einblick’s AI agent builds workflows using Python, SQL, and interactive components.

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Emanuel Zgraggen

Einblick AI

Maker

📌

🥳 Hello Product Hunt Community! I’m Emanuel, CEO and co-founder of Einblick. Einblick is an AI-native data notebook on an interactive canvas. When we started this company at MIT and Brown, my collaborators and I had one goal: reimagine the data notebook to make working with data easier for data scientists, data analysts, and anyone who wants to extract insights out of data. Today I’m excited to share our latest AI innovation with the PH community. Einblick Prompt is an AI agent that reasons about your data problems, and figures out the best way to solve your natural language requests. Einblick Prompt is fully integrated into the Einblick canvas–so you can build any workflow without ever switching tabs to Google, ChatGPT, or Stack Overflow. 🤝 Why integrate generative AI into a data notebook? Our team has always been dedicated to making the best workspace for data teams. Over the past year, our team has been working to bring all of the convenience of generative AI into our platform: - An AI Assistant who can “understand” natural language requests, manage syntax, and debug errors - Generate code with just natural language prompts–and run, debug, or edit immediately - Fix code with a click, without tab-switching to Google or Stack Overflow - Create beautiful complex graphs quickly I believe that Einblick Prompt will push our goals and the industry further, going beyond simple code completion, or text to code. Prompt reasons with you. Einblick Prompt has the ability to assess the tools at its disposal, from Python to SQL to Charts, and select the right tool for the right task, based on your requests. Einblick Prompt will supercharge your workflow in many ways, you just have to ask. 🙏 Ask Prompt to: 🧹 Speed up tedious data cleaning tasks. - “Join table1 and table2 on col1 = col2.” - “Filter data for condition1 in col1 and condition2 in col2.” - “Create a new column for new_var based on var1 and var2.” 📊 Create complex graphs to present to stakeholders. - “Create a 2 x 3 grid of histograms showing the distribution of col1 by col2 and col3.” - “Create a scatterplot of var1 and var2, color the points by var3.” - “Recreate the above plot in seaborn using a pastel color palette.” 🔎 Explore your data. - “Show me the top correlations with my_var in a barchart.” - “Print descriptive statistics about my data.” - “Create a heatmap of my dataset.” 🏗️ Build ML models and NLP tasks - “Use the vader package to do sentiment analysis of col1.” - “Predict var1 using logistic regression.” - “Build a linear regression model predicting var1.” 🤔 Why a 2-D canvas rather than a linear notebook? During our research years, we saw the need for industry data scientists to have a more flexible workspace that was innately collaborative. When testing out early versions of Einblick’s data canvas, their productivity benefitted from the freedom of a 2-D canvas. It was faster for them to chase down different lines of thinking as they worked, and so much easier to bring in their teammates who had valuable domain expertise and business insights which could drive further analysis. Now with Einblick Prompt, the canvas layout gives users the flexibility to try different variations of the same natural language prompt and compare the results side-by-side. 🎉 What else can you do in Einblick? - Multimodal workflows: switch between Python, SQL, and interactive components like Charts and Tables easily - Live collaboration: no need to hop on Zoom, you can video call directly in the platform - Data connectors: wherever your data is, you can access it from Einblick with just a few clicks - Run SQL on any table: whether it’s a CSV, a pandas dataframe, or a database table, you can use SQL to write your joins and filters