Rootlenses
BlazeSQL
Julius
Kipps AI
Metabase
Narrative BI
Awsy-ai
MirrorFly AI Voice Agent
NumPy
Pandas
Scikit-learn
OpenCV
Dataiku
Exploratory
htm.java
Figure Eight
Rootlenses Insight helps companies access and analyze their data instantly using AI. It connects to existing databases and transforms information into actionable insights, allowing users to retrieve answers simply by asking questions through a natural language chat interface.
Rootlenses Voice enables organizations across any industry to automate inbound and outbound customer interactions. Teams can create custom call workflows, schedule campaigns, validate phone numbers, and receive automated post-call reports with conversation insights and performance metrics.
Rootlenses MCP provides a secure governance layer for enterprise AI. It enables AI assistants and agents to connect safely with business systems, databases, APIs, and internal tools through the Model Context Protocol (MCP), ensuring controlled access, centralized management, and compliance while accelerating AI adoption across the organization.
RootlensesRootlenses's answer
Unlike platforms that focus on either analytics or automation, Rootlenses combines data intelligence (Insight) and voice automation (Voice) in a single ecosystemโgiving companies an integrated way to understand their data and act on it immediately.
Rootlenses's answer
Most competitors specialize in either analytics or automation. Rootlenses offers bothโInsight for data intelligence and Voice for automated callingโworking together to help companies understand their data and act on it instantly.
Based on our record, NumPy seems to be more popular. It has been mentiond 122 times since March 2021. 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.
Unmatched integration with ML/AI ecosystems through NumPy, TensorFlow, and PyTorch. - Source: dev.to / 9 months ago
The book introduces the core libraries essential for working with data in Python: particularly IPython, NumPy, Pandas, Matplotlib, Scikit-Learn, and related packages Familiarity with Python as a language is assumed; if you need a quick introduction to the language itself, see the free companion project, Aโฆ. - Source: dev.to / 10 months ago
AI starts with math and coding. You donโt need a PhDโjust high school math like algebra and some geometry. Linear algebra (think matrices) and calculus (like slopes) help understand how AI models work. Python is the main language for AI, thanks to tools like TensorFlow and NumPy. If you know JavaScript from Vue.js, Pythonโs syntax is straightforward. - Source: dev.to / 12 months ago
The AI Service will be built using aiohttp (asynchronous Python web server) and integrates PyTorch, Hugging Face Transformers, numpy, pandas, and scikit-learn for financial data analysis. - Source: dev.to / over 1 year ago
This library provides functions for working in domain of linear algebra, fourier transform, matrices and arrays. - Source: dev.to / almost 2 years ago
BlazeSQL - ChatGPT for your SQL Database
Pandas - Pandas is an open source library providing high-performance, easy-to-use data structures and data analysis tools for the Python.
Julius - Turn your Mac into a Bluetooth speaker
Scikit-learn - scikit-learn (formerly scikits.learn) is an open source machine learning library for the Python programming language.
Kipps AI - Make AI Assistant for your business
OpenCV - OpenCV is the world's biggest computer vision library