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RapidAI Vision

Providing Cognitive Surveillance as a Service...

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Providing Intelligent Surveillance and Security Solution

Solving the problem of analysis of tons of data in form of texts, images and videos.

At RapidAI Vision, a leading player of Text and Video Analytics, we are committed to solve the biggest problem in intelligent Surveillance - analysis of tons of data in form of texts and videos. Most of the enterprises and Govt. agencies use IP cameras for surveillance to track their business operations, this requires manual monitoring which is inaccurate and time consuming.

RapidAI Vision helps such enterprises to make sense of this data by implementing the different methodology of Artificial Intelligence which makes the system capable of doing automatic surveillance on behalf of the human eye. Our deep learning algorithms can detect any deviations in standard operating procedures and automatically list them and make them track able for all relevant stakeholders in the organisation.

Our Corner Stones

Strivers for perfection, That is what we are. The venture, right from the ideation, continually strives to integrate modern technologies and trying to transform them into reliable, affordable, and intelligent video analytic solutions. With a focus on perfection, we have defined and laid our corner stones, which are:

Domain Skills
Research & Development
Engineering and Technology Expertise
Customer oriented

Technology

Harnessing the capabilities of Artificial Intelligence

Detect any change in standard operating procedures using Computer Vision, NLP, and Machine/Deep Learning algorithms.

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Text Analytics

Text analytics is the process of using computers to extract information from written text to derive insights and patterns.

Text analytics transforms unstructured text into structured data that can be used for analysis. It can identify patterns, relationships, sentiments, and other actionable knowledge.
We extract the insights from textual data by using the classical ML techniques like natural language processing (NLP) as well as large language models (LLMs) .
Some use cases of text analytics include Sentiment analysis, text classification, part-of-speech (POS) tagging, named entity recognition (NER), chatbot, and conversational AI.