What Does the Future Hold for Fashion in AI and SaaS Driven Solutions?

AI-driven SaaS platforms have the ability to transform the fashion industry’s approach to sustainability. It can do that with the help of the supply chain carbon emissions tracking. This helps them to track the emissions for a greener future. The fashion industry can provide consumers with better products without having to cause harm to the environment.

This can be possible with the help of the AI-driven SaaS platforms. These technologies are revolutionizing supply chain transparency and automating the tracking of carbon emissions, paving the way for a more responsible future in fashion. At the captivating intersection of deep technology and compliance infrastructure, and decentralized AI solutions are reshaping the very fabric of the fashion world. 

Their influence spans from design and production to sales and marketing, with a particular emphasis on e-commerce and retail channels that define today’s marketplace. Navigating a complex supply chain filled with multiple stakeholders often results in inefficiencies and a lack of transparency. 

Many fashion brands struggle with tracking their environmental impact and labor conditions. This happens in their entire supply chain, especially when it comes to decentralized and lower-tier suppliers. 

However, with the help of other platforms, fashion companies can automate the tracking and report carbon emissions. This can help them to focus on the greenhouse gas emissions. By using data from suppliers and manufacturers, these platforms offer real-time insights into emissions. 

Besids, they can also streamline the reporting process, which can empower companies to meet regulatory requirements and industry standards with remarkable ease. Yet, as Narendra Makwana, co-founder and CEO of GreenStitch, an innovative sustainability software designed for the fashion and textiles industry, points out, assessing a company’s emissions involves navigating through extensive data. 

Large textile and fashion enterprises manage millions of purchase orders each month, which can lead to data entry errors. A term like ‘cotton’ might inadvertently be recorded as ‘COT’ or ‘CO’, resulting in disorganized data. 

This is precisely where machine learning steps in to provide clarity and structure. In a recent conversation with AIM, Makwana illuminated the transformative benefits of applying machine learning to emission analysis. 

GreenStitch’s AI-powered SaaS platform is meticulously trained over time to handle unstructured data from various companies, making the entire process swifter and more efficient.

The company firmly emphasizes the importance of third-party verification in its modeling processes. Customers supply data, such as bills of materials, which are then validated using cutting-edge Optical Character Recognition (OCR) technology. 

If a discrepancy arises, like a customer reporting 1,000 kilowatt-hours of electricity that doesn’t match their bill of 5,000 kilowatt-hours, the system promptly flags the inconsistency and notifies them.

“While we provide some assurance regarding our modeling, the ultimate responsibility for accurate inputs rests with the customers. We also leverage advanced AI analytics to identify discrepancies. 

Our final assurance focuses on confirming the proper alignment of emission factors, methodologies, and frameworks, all validated through third-party verification of our code,” the CEO stated.

India is a leading exporter of fashion and textile goods. Here companies want to diversify their manufacturing and sourcing operations to reduce dependency and mitigate risks. 

This trend has shown an increase in the local demand for fashion manufacturing. By structuring this data efficiently, they provide invaluable insights, including climate scores. For companies struggling with ineffective data workflows, their platform captures the necessary information with remarkable ease.

GreenStitch offers templated workflows and generates an array of reports, product, buyer, and activity reports, through the power of AI, resulting in visually stunning outputs complete with informative graphs and insightful commentary. 

Companies such as Aditya Birla Fashion and Retail frequently need to comply with numerous frameworks, including the Business Responsibility and Sustainability Reporting (BRSR), Global Reporting Initiative (GRI), Customer Data Integration (CDP), and Geostatistical Software (GS+).

Shashank Sripada, co-founder and COO of Gaia, shared an inspiring perspective with AIM, suggesting that creating a network of agents to monitor various aspects of vehicles, such as emissions, usage, and wear, can unlock remarkable opportunities, akin to those within the clothing industry. 

This allows makers to collect data easily, from vehicles and other emission sources. They can then integrate the emissions map & the policymakers can take worthy decisions. In India, consumers often focus on outdated databases. This is when analysts feel that the government can publish its own data.

This can enhance the accuracy and relevance of the tracking & reporting of the emissions. Sripada asserts that, much like supply chain management, personalized insights into fashion preferences can revolutionize real-time clothing and style advice. “We have seen significant disruption in fashion retail with the advent of D2C and Shopify-led online platforms. He also adds, that he is confident AI will further empower fashion creators to design, market, and distribute their products.

Likewise, he feels that AI gives the edge to individual designers for large fashion houses. Only time will tell.