Deploy And Apply

We are architects of change.


We drive the development of end-to-end AI and Machine Learning pipelines that deliver impactful results.

01

Machine Learning

ML applications are not only used to analyze vast amounts of numerical data, but also reports and articles to identify patterns and activities. Various industries like finance, engineering and healthcare are applying ML to conduct classification and detective models, which are now becoming a time-saving and cost-effiective methodology.

02

Behavior Analysis

Visualize customers' historical sales, preferences, and sentiments to recommend products they're likely to be interested in. Sales and marketing professionals have been longing for this kind of system. With dynamic-growth datasets and ML-powered algorithms, business leaders are now able to identify targeted customers and their interests.

03

Natural Language Processing

Chatbots can provide 24/7 customer support, answer questions, and offer personalized advice. AI-powered management tools can analyze a customer's goals, risk tolerance, and help with processing account reconciliation. It frees up human employees to focus on complex tasks to improve operational efficiency.
App

  • Real-world Application:

    Retrieval-Augmented Generation (RAG)

  • What is RAG?

    RAG is like having a supercharged researcher and writer partner. RAG can be used to create informative internal knowledge bases or FAQs, allowing employees to find answers to their questions quickly and efficiently. This can save them time and improve overall productivity.

  • Similar to ChatGPT

    In the world of AI, RAG does something similar. This part acts like your diligent journalist. It searches through a vast corpus of text to find relevant documents that answer a specific question. ChatGPT relies solely on its internal knowledge base to respond.

  • Different from ChatGPT

    RAG is not only a skilled writer, it takes your own relevant documents, along with the original question, and generates a detailed and up-to-date answer. RAG can access and leverage external sources of information during the generation process. This makes RAG more flexible and potentially more accurate, especially for factual queries.

  • Your Digital Assistant

    RAG combines retrieval relevant information and generation a response to provide accurate and timely answers. RAG offers more control over the data sources it uses. This can be useful for specific domains or privacy concerns. It’s like having an AI-powered research assistant at your fingertips!

Inquiry

Implementation

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