Machine Learning • 2025

e-Commerce Strategy via Agents

e-Commerce Strategy via Agents

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e-Commerce Strategy via Agents

Delivering a strategic AI agent roadmap, streamlining e-commerce and ensuring scalable, long-term automation

Problem

A biotech company needed options for an intelligent agent to streamline its e-commerce experience. Their customers required guidance on complex products, automated access to advisory documentation, and seamless cart management. However, the company also saw this as an opportunity to invest in a scalable, multi-agent AI framework rather than a one-off solution, ensuring long-term strategic benefits across business functions

Solution

We provided a strategic consultation on AI agents, clarifying their capabilities, limitations, and their broader role across their client’s lifecycle, from first contact, thru partnering to support.

Our approach combined a bottom-up strategy—encouraging user-driven experimentation—with a top-down investment focus to identify high-value use cases. As a long-term vision, we introduced Recursion’s LOWE (LLM-Orchestrated Workflow Engine) as a model for AI-driven process automation in pharmaceuticals.

Finally, we outlined an AI maturity roadmap, emphasizing how AI agent investments are cumulative, ensuring progressive automation without conflicting or wasted investments.

Recipe

Worked closely with the CMO to understand immediate requirements and ensure they are addressed first.

For longer term agentic AI uses cases, recommended bottom-up & top-down discovery. This is a mechanism for staff experimentation via tools such as OpenAI Assistants, which informs formal investments in agentic solutions and frameworks. An approach used by other pharmaceutical companies.

Low code Botpress platform recommended as chatbot framework with strong agentic credentials via API integration and model fine tuning potential, supporting both customer facing ecommerce tasks and internal usage.

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