The UAE-based Fero.ai, a developer of AI-based SaaS products, is all set to become a leader in logistics process automation. As a ‘product provider,’ it aims to raise efficiency and minimise errors, ensuring quick decision-making in the fast-expanding supply chain industry.
Abhinav Chaudhary, CEO & Founder said Fero.AI said the company continues to research and develop on high-customisable tools and environments for transactional ease in micro-diverse logistics processes across domains, industries, and regions.
Given the evolving logistics process issues, he mentioned that chat-based TMS (Transport Management System) and DMS (Distribution Management System) customised setup, along with recommendation engines that include all sub-business functions in logistics organisations are few more services in the pipeline.
Multiple tech-logistics companies in the market have addressed or are increasingly addressing the issues of digitisation, connectivity, multi-stakeholder platform orchestration, and more. Fero’s products and solutions aim to provide a digital user who can act on such software modules, he said.
The company’s USP, according to him, lies in automating decision-making and communication roles in logistics processes across industries such as freight forwarders, manufacturers, and 3PLs.
To a query on the utilisation of AI to improve logistics and freight management, Chaudhary said Fero utilizes machine learning models for learning patterns and generating suggestions, predictions, and recommendations. Such output enhances logistics process management to ensure efficiency at various business levels, reducing errors and enabling better business decisions.
“Our mantra is to harness these technologies and empower logistics and freight companies to streamline operations, cut costs, and provide more reliable and efficient services, ultimately boosting their competitiveness in the market”, he added.
He cited the instance of an India-based customer, among the global top five freight forwarders, implementing the company’s ‘Consolidation Engine’ to provide real-time predictions on road freight consolidation happening across 10 cities in India for their global aviation spares distribution mobilised via ocean and air freight. ML algorithms in action during 2022 provided a reduction of 14 per cent in road freight expenses for the customer compared to 2021 volumes.
On the plans for the Indian market, Chaudhary said, “We are already contributing in our capacity to grow the AI ecosystem in India. The current impact is not large scale, owing to the size of the Indian market. We have tie-ups with AI academic institutes for hiring, arrangements for data processing, and training model development activities. As Fero grows in the logistics hubs globally, we intend to establish logistics hubs-specific AI teams within India for small and mid-size AI companies spread across the country.
When asked about the cost incurred for products, he explained that logistics and forwarding tasks are largely outsourced in the market by distributors and manufacturers. Thus, cost reduction and efficiency depend largely on the actions of transporters, freight forwarders, ports, 3PLs, and similar companies. Fero.Ai solutions address such avoidable costs and amplify efficiencies in these processes.
Within international trade, he said organisations need faster, more efficient, and error-free transactions. Actions and tasks such as rate procurement, quote submissions, planning, scheduling, customs documentation, consolidation, recommendation engines, and many more are addressed via Fero’s suite of solutions.
In India, where logistics and freight transactions happen at a massive scale, there is a substantial opportunity to automate transactions and thus have an impact at the industry level. “Our freight forwarding customers in India have successfully not only automated transactions with their 100+ Indian trucking vendors but also looped in vendors across destination and origin ports for their export and import shipments globally”, he said.
The majority of the responsibilities in WM (warehouse management) and DP (demand prediction) for manufacturers and distributors, since the inception of the trade hundreds of years back, have always been manual. ERPs provided us with digitisation and connectivity among teams. With developments in statistics and algorithms, the company has seen an augmentation in decision-making.
