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Built on Microsoft Azure, the cloud computing service created by Microsoft, the platform will accelerate insight driven decision making for retail brands through intelligence and unified view of data from multiple data points.
Albus, with its machine learning capability, will collect data from different retail data points in any format and convert them into actionable intelligence and goal-based algorithms specific to retail problems. It enables getting structured data in any format quickly giving a unified view of data and insights that acts as the foundation of the AI platform.
Moreover, Albus complements Ace Turtle's Omni-channel platform, Rubicon, to execute actionable intelligence, real time for enterprise retailers. The platform leverages Microsoft Azure's best-in-class data services and artificial intelligence that scale and support deep learning and enables faster go to market solution.
"A majority of retailers are now highly adept at collecting relevant information or data but the real challenge that they face is in deriving actionable intelligence and in execution capability. Built on Microsoft Azure, our platform has developed capabilities to bridge the gap between the insights required by retailers and the information that is available to enable better decision making, real-time. Moreover, our omni-channel capabilities ensure that the actionable intelligence for brands are actually executed in order to yield the desired result based on the client's goal," said Ace Turtle CEO, Nitin Chhabra.
Albus is expected to address dynamic order allocation for fulfillment to the most optimal stock point - offline retail stores or warehouses; dynamic safety stock assigned real-time for each product to ensure no excess order occur due to globally shared inventory across sales channels, nor does any loss of opportunity occurs due to locked inventory in safety stock.
The platform also aims to address dynamic inventory allocation to distribute inventory of a product among online channels based on parameters such as demand, cost of sales and discounts to optimise profit, and last-mile allocation to optimise cost and speed, while ensuring reliability and performance.
Another area of importance is catchment and assortment planning to identify the right catchment areas for store locations, and the right product range or merchandise to stock in a store as per demand signals of target customers in the catchment area. This not only optimises store sales but also reduces huge working capital lost in unsold inventory
According to a report by Gartner, 85 percent of customer interactions in retail will be managed by AI in 2020. The embedded machine learning capability of Albus turns retailers online and offline data into actionable intelligence and Azure's elastic cloud infrastructure helps in faster deployment of the platform into the retail channels of the brand.
The partnership between Ace Turtle and Microsoft aims at boosting enterprise readiness and go-to-market strategy of the former, while assisting in achieving scale in national and international markets.
(This story has not been edited by Business Standard staff and is auto-generated from a syndicated feed.)