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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.
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Rootlenses'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, PostgresML seems to be more popular. It has been mentiond 7 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.
The web service supports generating embeddings from OpenAI and Ollama AI models. It also provides a fallback for users without access to AI models running on a remote server through PostgresML. - Source: dev.to / over 1 year ago
That's outside of the database, though. This is more like what I had in mind -- I just found it: https://postgresml.org/. - Source: Hacker News / about 2 years ago
Some excellent tools were created to represent these tasks "naturally" in SQL and even let most of the computation happen inside the database. PostgresML is a great example. It's built above PostgreSQL and provides a set of functions that allow you to train and use machine learning models with SQL. Here's how you can train a classification model for the classic handwritten digit recognition problem:. - Source: dev.to / over 2 years ago
PostgresML | You know Postgres. Now you know machine learning โ PostgresML. - Source: dev.to / over 2 years ago
You can swap in almost any open-source model on Huggingface. HuggingFaceH4/zephyr-7b-beta, Gryphe/MythoMax-L2-13b, teknium/OpenHermes-2.5-Mistral-7B and more.If you haven't seen us here before, we're PostgresML, an open-source MLOps platform built on Postgres. We bring ML to the database rather than the other way around. Source: over 2 years ago
BlazeSQL - ChatGPT for your SQL Database
Talk To Your Data App - Tak to your data in natural language, no technical skills required. PostgreSQL, MySQL, HubSpot, Mailchimp & many more SaaS platforms. Get instant answers, visualizations & insights.
Julius - Turn your Mac into a Bluetooth speaker
Pinecone - Search through billions of items for similar matches to any object, in milliseconds. Itโs the next generation of search, an API call away.
Kipps AI - Make AI Assistant for your business
ChatWithCloud AI - Chat with your AWS Cloud from Terminal. Talk to your Cloud, literally.