
cognee
Mem0
Claiv Memory
ChainMemory
Memori
Agentmemory
Supermemory
Graphiti
Plotly
D3.js
RAWGraphs
Tableau
Google Charts
Highcharts
Bokeh
Chart.js
Build dynamic memory for Agents and replace RAG using scalable, modular ECL (Extract, Cognify, Load) pipelines.
cognee
PlotlyPlotly is recommended for data scientists, analysts, and developers who need to create interactive and visually appealing data visualizations. It's particularly useful for those who work with Python or R and want the ability to embed their visualizations in web applications or dashboards.
Based on our record, Plotly seems to be a lot more popular than cognee. While we know about 34 links to Plotly, we've tracked only 2 mentions of cognee. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.
Research tools forget across sessions, and they never notice when two sources disagree. Crosscheck is a small copilot on top of cogneethat does both: persistent memory of everything you feed it, and a hero feature that flags when sources contradict each other โ e.g. "FooDB sustained 50,000 req/s" (2021) vs "only 10,000 req/s" (2024). - Source: dev.to / about 2 months ago
Cognee structures this raw text into a Knowledge Graph. Instead of just saving "Pricing is popular", it creates nodes:. - Source: dev.to / 7 months ago
Let's dive into some practical examples. First, you'll need to set up your environment with the right tools. I recommend using pandas for data manipulation and plotly for visualization. - Source: dev.to / 6 months ago
Plotly is perfect for interactive visualizations. You can create interactive charts and graphs that allow users to hover, click, and zoom in. Plotly is also great for web-based visuals, making it easy to share your findings online. - Source: dev.to / over 1 year ago
Front End: A React application that leverages React-Chatbotify library to easily integrate a chatbot GUI. It also uses the Plotly library to display the charts/visualizations. The generative AI implementation and details are entirely abstracted from the front end. The front-end application depends on a single REST endpoint of the backend application. - Source: dev.to / over 1 year ago
In this tutorial, Mariya Sha will guide you through building a stock value dashboard using Taipy, Plotly, and a dataset from Kaggle. - Source: dev.to / over 1 year ago
How to Accomplish: Utilize visualization libraries like Matplotlib, Seaborn, or Plotly in Python to create histograms, scatter plots, and bar charts. For image data, use tools that visualize images alongside their labels to check for labeling accuracy. For structured data, correlation matrices and pair plots can be highly informative. - Source: dev.to / about 2 years ago
Mem0 - Your private, local memory layer for all AI tools
D3.js - D3.js is a JavaScript library for manipulating documents based on data. D3 helps you bring data to life using HTML, SVG, and CSS.
Claiv Memory - The missing memory layer for AI products.
RAWGraphs - RAWGraphs is an open source app built with the goal of making the visualization of complex data...
ChainMemory - Portable, verifiable memory for AI agents โ works across ChatGPT, Claude, Gemini and any MCP client
Tableau - Tableau can help anyone see and understand their data. Connect to almost any database, drag and drop to create visualizations, and share with a click.