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About Us

Our Core

Research | Find | Buy

ReFiBuy, is an homage to how people shop both online and offline.  They Research, Find, Buy.  Our goal is to leverage agentic technology to solve some of e-commerce’s hardest problems.  These problems all live within the Research, Find, Buy cycle.

Research

Step 1

Discover the right product for your needs. Compare features, read reviews, and explore options whether it's the latest gadget or the perfect gift for your 12-year-old niece.

Find

Step 2

Narrow down your choices and compare availability, prices, shipping times, and payment options. Get the details that matter before making your decision.

Buy

Step 3


You've found the perfect product now complete your purchase with confidence. Choose the best deal, finalize delivery options, and enjoy a seamless checkout experience.

Business Statistics

Grow with ReFiBuy

At ReFiBuy, our solutions are built for brands and retailers, but they ultimately empower consumers to Research, Find, and Buy with ease. We’re driven to accelerate e-commerce growth beyond its current 7-8% rate and push it back toward 20%+ expansion.

7-8%

Current Growth Rate

20%+

Expected Growth Rate

The Evolution of the Research, Find, Buy Journey

How consumers make purchasing decisions has evolved over more than a century, shaped by psychology, technology, and commerce. From early advertising models to today’s digital-first shopping experience, the Research, Find, Buy cycle remains a core framework in understanding how people discover and purchase products. Here’s a look at its history:

  • 1898 – The Birth of Consumer Decision Theory

    E. St. Elmo Lewis, an early advertising pioneer, introduced the AIDA framework (Attention, Interest, Desire, Action) to formalize how consumers move from awareness to purchase.

    While some debate his authorship, with a name like E. St. Elmo Lewis, we’ll go with innocent until proven otherwise! AIDA was first applied to life insurance sales.

  • 1910 – John Dewey’s Five-Stage Buying Process

    Philosopher John Dewey outlined five key stages in consumer decision-making in his book How We Think:

    1. Problem/Need Recognition
    2. Information Search
    3. Evaluation of Alternatives
    4. Purchase Decision
    5. Post-Purchase Evaluation

  • 1999 – Research, Find, Buy Takes Shape

    Our co-founder and CEO, Scot Wingo, first encountered the Research, Find, Buy concept while meeting Pierre Omidyar at eBay during his time at AuctionRover.

    This simple yet powerful framework for understanding e-commerce behavior stuck with him for decades.

  • 2005 – Microsoft’s Vision of a ‘Seamless Marketplace’

    In a memo, Microsoft CTO Ray Ozzie described a future where consumers could Research, Find, and Buy anything they wanted seamlessly.

    While we suspect an ex-eBay team member influenced this thinking, the exact origins remain a mystery.

  • 2009 – McKinsey’s Consumer Decision Journey

    McKinsey challenged the traditional funnel model, introducing the idea of consecutive loops instead where initial consideration, active evaluation, and post-purchase engagement play an ongoing role in the buying cycle.

  • 2025 & Beyond – The Future of Research, Find, Buy

    Today, research shows that while most consumers start their journey online, 82% of transactions still happen in-store.

    We believe this will invert, with online purchasing becoming dominant. At ReFiBuy, we’re building solutions to reignite e-commerce growth delighting consumers at every step of their Research, Find, Buy journey.

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What Does Agentic Mean?

There are three core technologies that we are building on at ReFiBuy.

Large Language Models

Large Language Models (LLMs), or GPTs such as OpenAI’s ChatGPT family of offerings, Google Gemini, Anthropic’s Sonnet models and so on.

Someone typing in ChatGPT

Retrieval Augmented Generation

Retrieval Augmented Generation (RAG), introduced by Facebook researchers in 2020, enhances LLMs by giving them access to real-time, industry-specific data sources like databases.

While LLMs are trained on vast datasets, they often generate 'hallucinations' or incorrect or fabricated information. RAG mitigates this by grounding responses in reliable, domain-specific data, effectively acting as a filter that reduces inaccuracies and improves contextual relevance.

An artist’s illustration of artificial intelligence (AI). This illustration depicts language models which generate text.

Agentic frameworks

In 2022 and 2023, both the open-source community (LangChain) and commercial players (Microsoft’s Semantic Kernel) introduced frameworks that simplified the development and orchestration of AI agents.

It’s worth noting that ‘agent’ is a broad term. At ReFiBuy, our agents are ‘headless’ as they operate without a user interface, executing tasks like booking flights, modifying databases, and transforming data. These agents function under the direction of an LLM-powered ‘electronic brain,’ often integrated with an industry-specific RAG database to enhance accuracy and relevance.

An artist’s illustration of artificial intelligence (AI). This image represents how machine learning is inspired by neuroscience and the human brain.

Isn't Everything AI?

When we say AI at ReFiBuy, we start the clock at the release of ChatGPT on November 30th, 2022. While GPTs had been around for a long time before, ChatGPT was the starting gun for the large language model (LLM) AI race.

We’re excited about this new wave of technology and the innovative ways it’s transforming problem-solving. At ReFiBuy, we’re bringing these advancements to retail and demonstrating their impact firsthand. If you’re interested in diving deeper, here are some foundational materials we highly recommend:

Professionals

Teamwork begins by building trust

We founded ReFiBuy to apply Agentic AI technology and drive new innovation in e-commerce and retail. At the same time, we see this as an opportunity to build something entirely new—an AI-native company designed to leverage next-gen intelligence, automation, and adaptability.

Our team thrives on curiosity, execution, and a shared belief that technology should make commerce smarter, faster, and better for everyone.

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CEO, Co-founder

Scot Wingo

Scot is a serial entrepreneur with deep eCommerce experience, founding four startups—including ChannelAdvisor (IPO 2013) and AuctionRover.com—while successfully exiting three.

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CTO, Co-founder

Cameron Bowe

Cameron is an NCSU alumni and veteran technologist with 18 years of eCommerce experience at ChannelAdvisor and Rithum.

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CAIO, Co-founder

James Frawley

James is an expert in eCommerce analytics and intelligence, bringing 11 years of experience from ChannelAdvisor and MikMak.

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COO, Co-founder

Derek Conlin

Derek is an eCommerce expert with 18 years of experience at ChannelAdvisor, Walmart, and Rithum leading global sales, partnerships, and strategy. 

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Creative Director

Rebecca Ross

Rebecca is a graphic communicator and industrial designer with expertise in ideation, manufacturing, and design strategy.

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Whether you want to learn more, ask questions, or get involved, we’d love to hear from you.