India’s Union Textile Minister launched the country’s first fashion forecasting initiative, named “VisioNxt.”
- Along with it, the India-specific Fashion Trend Book ‘Paridhi 24×25’ was introduced.
About VisioNxt:
- VisioNxt is a bilingual web portal established by the National Institute of Fashion Technology (NIFT) in collaboration with the Ministry of Textiles, Government of India.
- Launched in 2018, it is operational at NIFT Delhi and Chennai with the support of the Textiles Ministry.
- The initiative integrates Artificial Intelligence (AI) and Emotional Intelligence (EI) to analyze and predict geo-specific fashion trends that resonate with India’s plurality and cultural richness.
- The portal aims to provide India-specific fashion trend insights to help designers, manufacturers, and retailers, reducing reliance on international forecasting agencies.
Key Features of VisioNxt:
- It offers localized fashion trend insights tailored to Indian designers, manufacturers, and weavers.
- The forecasts reflect India’s socio-economic nuances and cultural diversity.
- It supports the Indian fashion industry by providing consumer-focused data to strengthen homegrown fashion talent.
AI Model and Accessibility:
- Uses the AI-based model called “DeepVision”, which decodes Indian fashion attributes such as style, color, and regional influences.
- Accessible through a bilingual web portal in Hindi and English, making it inclusive for a wider audience within India’s fashion industry.
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Frequently Asked Question:
What is VisioNxt?
VisioNxt is a bilingual fashion trend forecasting portal created by NIFT and the Ministry of Textiles in India.
When was VisioNxt launched?
VisioNxt was launched in 2018, with operations based in NIFT Delhi and Chennai.
Why is localized trend forecasting important in fashion?
Localized forecasting helps designers cater to the cultural and socio-economic preferences of a specific market, making designs more relevant.
How does emotional intelligence influence fashion design?
Emotional intelligence in fashion helps designers understand and respond to consumer emotions, leading to more appealing and personalized fashion.