Microsoft Azure GenAI Offerings

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GenAI Products Models and API


Azure offers a comprehensive suite of generative AI products and services, primarily through its Azure OpenAI Service, which integrates OpenAI’s advanced models with Azure's robust infrastructure and security features.

Azure OpenAI Service

The Azure OpenAI Service provides access to several powerful models developed by OpenAI, including:

  • GPT-4 and GPT-4 Turbo with Vision: These models offer advanced natural language processing capabilities, with GPT-4 Turbo incorporating enhanced code generation and other specific improvements.
  • GPT-3.5 Turbo: An improved version of GPT-3.5, offering better performance and cost-efficiency.
  • DALLE-3: For generating high-quality images from textual descriptions.
  • Codex: Designed to assist in coding by generating code snippets based on natural language prompts.
  • Whisper: An automatic speech recognition (ASR) system that converts spoken language into text.

Features and Capabilities

  1. Text Generation and Completions: The core capability of Azure OpenAI is generating text based on input prompts, useful for a wide range of applications from chatbots to content creation.
  2. Image Generation: DALLE-3 enables the creation of high-quality images from textual descriptions, supporting creative industries and marketing efforts.
  3. Code Assistance: Codex helps developers by generating code snippets, completing code, and even translating between programming languages.
  4. Speech Recognition: Whisper transcribes spoken language into text, useful for creating transcripts, enabling voice commands, and more.
  5. Function Calling: Allows the models to intelligently decide when to invoke external functions and incorporate their responses, enhancing the interactivity and utility of AI applications.

Customization and Fine-Tuning

Azure OpenAI supports fine-tuning of models to better fit specific use cases:

  • Custom Model Training: Users can fine-tune models like GPT-3.5 Turbo to create custom models tailored to their specific needs, including support for function calling and continuous fine-tuning to incrementally improve the model without losing previous training.
  • Assistants API: Enables developers to build stateful AI-powered assistants, useful for a range of applications like customer service bots, personal assistants, and more.

Security and Compliance

Microsoft emphasizes responsible AI use, incorporating principles and content filters to guard against misuse and unintended harm. Azure OpenAI integrates these models with Azure's security features, including private networking and regional availability, ensuring data privacy and compliance.

Business Applications

Businesses are leveraging Azure OpenAI in various innovative ways:

  • Content Creation: Generative AI is used to create high-quality content quickly, including images, videos, and text for marketing and branding purposes.
  • Automation: AI models automate routine tasks in IT and HR, improving efficiency and reducing operational costs.
  • Personalized Marketing: Businesses use generative AI to create personalized marketing campaigns, enhancing customer engagement and conversion rates.
  • Customer Service: AI-powered chatbots and virtual assistants provide instant, accurate customer support, improving customer satisfaction and loyalty.

Overall, Azure's generative AI services offer powerful tools for businesses to innovate, automate, and enhance their operations, supported by the robust infrastructure and security of Microsoft Azure.






Dataknobs Blog

10 Use Cases Built

10 Use Cases Built By Dataknobs

Dataknobs has developed a wide range of products and solutions powered by Generative AI (GenAI), Agent AI, and traditional AI to address diverse industry needs. These solutions span finance, healthcare, real estate, e-commerce, and more. Click on to see in-depth look at these use cases - Stocks Earning Call Analysis, Ecommerce Analysis with GenAI, Financial Planner AI Assistant, Kreatebots, Kreate Websites, Kreate CMS, Travel Agent Website, Real Estate Agent etc.

AI Agent for Business Analysis

Analyze reports, dashboard and determine To-do

DataKnobs has built an AI Agent for structured data analysis that extracts meaningful insights from diverse datasets such as e-commerce metrics, sales/revenue reports, and sports scorecards. The agent ingests structured data from sources like CSV files, SQL databases, and APIs, automatically detecting schemas and relationships while standardizing formats. Using statistical analysis, anomaly detection, and AI-driven forecasting, it identifies trends, correlations, and outliers, providing insights such as sales fluctuations, revenue leaks, and performance metrics.

AI Agent Tutorial

Agent AI Tutorial

Here are slides and AI Agent Tutorial. Agentic AI refers to AI systems that can autonomously perceive, reason, and take actions to achieve specific goals without constant human intervention. These AI agents use techniques like reinforcement learning, planning, and memory to adapt and make decisions in dynamic environments. They are commonly used in automation, robotics, virtual assistants, and decision-making systems.

Build Dataproducts

How Dataknobs help in building data products

Building data products using Generative AI (GenAI) and Agentic AI enhances automation, intelligence, and adaptability in data-driven applications. GenAI can generate structured and unstructured data, automate content creation, enrich datasets, and synthesize insights from large volumes of information. This helps in scenarios such as automated report generation, anomaly detection, and predictive modeling.

KreateHub

Create New knowledge with Prompt library

At its core, KreateHub is designed to enable creation of new data and the generation of insights from existing datasets. It acts as a bridge between raw data and meaningful outcomes, providing the tools necessary for organizations to experiment, analyze, and optimize their data processes.

Build Budget Plan for GenAI

CIO Guide to create GenAI Budget for 2025

CIOs and CTOs can apply GenAI in IT Systems. The guide here describe scenarios and solutions for IT system, tech stack, GenAI cost and how to allocate budget. Once CIO and CTO can apply this to IT system, it can be extended for business use cases across company.

RAG For Unstructred and Structred Data

RAG Use Cases and Implementation

Here are several value propositions for Retrieval-Augmented Generation (RAG) across different contexts: Unstructred Data, Structred Data, Guardrails.

Why knobs matter

Knobs are levers using which you manage output

See Drivetrain appproach for building data product, AI product. It has 4 steps and levers are key to success. Knobs are abstract mechanism on input that you can control.

Our Products

KreateBots

  • Pre built front end that you can configure
  • Pre built Admin App to manage chatbot
  • Prompt management UI
  • Personalization app
  • Built in chat history
  • Feedback Loop
  • Available on - GCP,Azure,AWS.
  • Add RAG with using few lines of Code.
  • Add FAQ generation to chatbot
  • KreateWebsites

  • AI powered websites to domainte search
  • Premium Hosting - Azure, GCP,AWS
  • AI web designer
  • Agent to generate website
  • SEO powered by LLM
  • Content management system for GenAI
  • Buy as Saas Application or managed services
  • Available on Azure Marketplace too.
  • Kreate CMS

  • CMS for GenAI
  • Lineage for GenAI and Human created content
  • Track GenAI and Human Edited content
  • Trace pages that use content
  • Ability to delete GenAI content
  • Generate Slides

  • Give prompt to generate slides
  • Convert slides into webpages
  • Add SEO to slides webpages
  • Content Compass

  • Generate articles
  • Generate images
  • Generate related articles and images
  • Get suggestion what to write next