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What is TensorBlock?

TensorBlock is an open-source AI infrastructure platform designed to broaden access to large language models by integrating two main components. At its heart lies Forge, a self-hosted, privacy-focused API gateway that unifies connections to multiple LLM providers through a single endpoint compatible with OpenAI’s offerings, which includes advanced encrypted key management, adaptive model routing, usage tracking, and strategies that optimize costs. Complementing Forge is TensorBlock Studio, a user-friendly workspace that enables developers to engage with multiple LLMs effortlessly, featuring a modular plugin system, customizable workflows for prompts, real-time chat history, and built-in natural language APIs that simplify prompt engineering and model assessment. With a strong emphasis on a modular and scalable architecture, TensorBlock is rooted in principles of transparency, adaptability, and equity, allowing organizations to explore, implement, and manage AI agents while retaining full control and reducing infrastructural demands. This cutting-edge platform not only improves accessibility but also nurtures innovation and teamwork within the artificial intelligence domain, making it a valuable resource for developers and organizations alike. As a result, it stands to significantly impact the future landscape of AI applications and their integration into various sectors.

What is Azure Machine Learning?

Optimize the complete machine learning process from inception to execution. Empower developers and data scientists with a variety of efficient tools to quickly build, train, and deploy machine learning models. Accelerate time-to-market and improve team collaboration through superior MLOps that function similarly to DevOps but focus specifically on machine learning. Encourage innovation on a secure platform that emphasizes responsible machine learning principles. Address the needs of all experience levels by providing both code-centric methods and intuitive drag-and-drop interfaces, in addition to automated machine learning solutions. Utilize robust MLOps features that integrate smoothly with existing DevOps practices, ensuring a comprehensive management of the entire ML lifecycle. Promote responsible practices by guaranteeing model interpretability and fairness, protecting data with differential privacy and confidential computing, while also maintaining a structured oversight of the ML lifecycle through audit trails and datasheets. Moreover, extend exceptional support for a wide range of open-source frameworks and programming languages, such as MLflow, Kubeflow, ONNX, PyTorch, TensorFlow, Python, and R, facilitating the adoption of best practices in machine learning initiatives. By harnessing these capabilities, organizations can significantly boost their operational efficiency and foster innovation more effectively. This not only enhances productivity but also ensures that teams can navigate the complexities of machine learning with confidence.

Media

Media

Integrations Supported

Microsoft Azure
Azure Data Science Virtual Machines
Azure Database for MariaDB
Azure Kinect DK
Azure Marketplace
BotCore
Cloudflare
Cranium
DeepSeek
Evvox
Lambda
MLflow
Microsoft 365
Microsoft Intelligent Data Platform
Model Context Protocol (MCP)
NVIDIA Triton Inference Server
New Relic
Omnisient
OpenAI
Slingshot

Integrations Supported

Microsoft Azure
Azure Data Science Virtual Machines
Azure Database for MariaDB
Azure Kinect DK
Azure Marketplace
BotCore
Cloudflare
Cranium
DeepSeek
Evvox
Lambda
MLflow
Microsoft 365
Microsoft Intelligent Data Platform
Model Context Protocol (MCP)
NVIDIA Triton Inference Server
New Relic
Omnisient
OpenAI
Slingshot

API Availability

Has API

API Availability

Has API

Pricing Information

Free
Free Trial Offered?
Free Version

Pricing Information

Pricing not provided.
Free Trial Offered?
Free Version

Supported Platforms

SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux

Supported Platforms

SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Company Facts

Organization Name

TensorBlock

Company Location

United States

Company Website

tensorblock.co

Company Facts

Organization Name

Microsoft

Date Founded

1975

Company Location

United States

Company Website

azure.microsoft.com/en-us/services/machine-learning/

Categories and Features

Categories and Features

Data Labeling

Human-in-the-loop
Labeling Automation
Labeling Quality
Performance Tracking
Polygon, Rectangle, Line, Point
SDK
Supports Audio Files
Task Management
Team Collaboration
Training Data Management

Machine Learning

Deep Learning
ML Algorithm Library
Model Training
Natural Language Processing (NLP)
Predictive Modeling
Statistical / Mathematical Tools
Templates
Visualization

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