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AI Recommendation Engine Success Story

AI-driven engine transformed Mobisoft from a passive ordering tool into a proactive business advisor.

Let's Talk

The Client

Mobisoft is a leading provider of B2B commerce solutions, enabling wholesalers and distributors to manage expansive product catalogs and complex procurement cycles. Serving as the digital backbone for high-volume trade, Mobisoft’s platform supports thousands of businesses in streamlining their operations and maintaining reliable supply chains.

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Location
HQ in Israel; global service coverage.
Industry
B2B eCommerce & Supply Chain Technology.
Main Technologies
Date of Project
Problem

The Challenge

In the traditional B2B landscape, product discovery is largely reactive. Mobisoft identified that their clients were relying heavily on manual searches or static order lists, which led to significant revenue leaks:

  • Inventory Gaps: Businesses often failed to stock high-demand items that their industry peers were successfully selling.
  • Missed Seasonality: Without data-driven insights, procurement teams often missed the window for high-volume seasonal products.
  • Stock-outs: A lack of automated tracking for replenishment cycles resulted in delayed reorders, lost revenue, and weakened customer loyalty.

To maintain its market leadership, Mobisoft needed to transform the procurement workflow from a manual process into a proactive, AI-driven growth engine.

What we’ve done

The Solution

As a strategic partner with deep expertise in AI and scalable infrastructure, Opsfleet collaborated with Mobisoft to develop an internal B2B Intelligence & Recommendation Engine. The system was designed to leverage segment-level peer learning and historical transaction data to guide buyers toward the right products at the right time.

The system focuses on three core pillars:

  1. Peer-Based Opportunity Detection: The engine cross-references a customer’s catalog with the purchasing patterns of industry peers to identify "inventory gaps."
  2. Seasonal Intelligence: Using historical correlation data, the system automatically surfaces products with high transaction volumes during specific holiday windows.
  3. Predictive Replenishment: The AI monitors individual purchasing cycles to trigger proactive alerts when a product is nearing its expected depletion date.
Results

The Outcome

The implementation of the AI-driven engine transformed Mobisoft from a passive ordering tool into a proactive business advisor. The rollout yielded immediate results:

  • 10% Increase in Sales: Driving higher transaction volumes by surfacing relevant, segment-specific products.

Final Thoughts

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