A PE-owned e-commerce company was entirely dependent on a third-party BPO to perform a core back-office operation: matching inbound shopping lists, arriving as images, PDFs, spreadsheets, and other unstructured formats, to its internal standard product taxonomy.
The offshore team had accumulated all the institutional knowledge for this process, creating deep vendor lock-in and fragility. Turnaround time exceeded 24 hours per batch, degrading the customer experience. Without change, the business would remain hostage to an expensive, slow, and opaque external dependency with no path to operational ownership or cost reduction.
Fractional AI designed and deployed a custom generative AI pipeline for a PE-owned e-commerce company, combining OpenAI for taxonomy classification, Google Gemini for text extraction, and Claude for intermediate processing, orchestrated on AWS with a confidence-scoring layer and feedback loop that allows the system to improve automatically over time.
The AI system replaced the BPO as the primary processing engine, with roughly two-thirds of remaining cost attributed to an optional QA layer the client chose to maintain. That layer is expected to be phased out in year two, pushing savings toward near-100%.
What previously required routing batches to an offshore team for 24-plus hour turnaround now completes in approximately 30 seconds per list, enabling real-time operational use cases that were previously impossible.
By deploying evaluation infrastructure early and running blind side-by-side comparisons, Fractional AI demonstrated the new system outperformed the legacy manual process on accuracy, giving leadership the confidence to decommission the BPO.
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