AI and Machine Learning


AWS AI and ML services

We specialize in designing, developing, and supporting various AI and machine learning services from AWS. Some of these services include: Amazon Sagemaker, BedRock, CodeGuru, Comprehend, Forecast, Fraud, Kendra, Lex, Personalize, Polly, Rekognition, Textract, Transcribe, Translate and MlOps. If you have a specific use case in mind, feel free to share it with us. We’ll guide you in selecting the best service to meet your needs. Let’s simplify the process for you!

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AI and Machine Learning

Azure AI and ML Services

Here are some of the Azure AI and ML services we implement and support,  Azure AI Search,  Azure OpenAI,  Bot Service,  Content Safety,  Custom Vision,  Document Intelligence,  Face,  Immersive Reader,  Language,  Speech,  Translator,  Video Indexer,  Vision, Azure ML services and MLops. Additionally, we specialize in Azure ML services and MLOps, ensuring efficient model development, deployment, and management. Feel free to reach out for more details or if you have a specific use case in mind. Let’s explore the best options for your needs!

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Azure AI and ML Services

Google cloud AI and ML Services

Here are the Google AI and ML services we implement and support AutoML, Contact Center AI, Dialogflow, Document AI, Gemini Code Assist, Generative AI Document Summarization, Natural Language AI, Speech-to-Text, Text-to-Speech, Translation AI, Vertex AI Agent Builder, Vertex AI Notebooks, Vertex AI Platform, Vertex AI Studio, Video AI, Vision AI. Feel free to reach out for more details or if you have a specific use case in mind. Let’s explore the best options for your needs!

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Google cloud AI and ML Services

Private LLM and RAG

Our 100% private Large Language Model (LLM) service is built on open-source models like Mistral and LLma. Unlike other services, this LLM remains entirely within your network, with zero external connections. Here’s how it benefits you: Complete Privacy: Your data never leaves your network. You can confidently provide private data for tasks like Retrieval Augmented Generation (RAG) and fine-tuning the model. Internal Use Cases: Internal Wikis: Create a knowledgeable internal wiki that stays within your company. Private Code Generation: Use the LLM for code snippets, documentation, and more. Chatbots: Develop well-behaved, company-specific chatbots that don’t venture beyond your network. Google Search Alternative: Treat it as your private Google search tool, tailored to your organization’s needs.

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Private LLM fine turning and RAG