Be My Eyes needed a richer form of visual assistance for blind and low-vision users because basic image recognition could label objects but could not hold a conversation or reason about what information mattered in complex real-world situations.
Reported impact
Be My Eyes created a more capable accessibility assistant, improved user independence for both physical and online tasks, and opened a broader commercial path for visual accessibility support.
Be My Eyes used GPT-4's visual input capabilities to build Virtual Volunteer, a conversational assistant inside its accessibility app. Instead of stopping at basic object labels, the system lets users share images or webpages and ask follow-up questions so the model can describe, interpret, and reason about what matters in context, whether that means identifying ingredients in a fridge, navigating a station, or summarizing cluttered shopping pages. Inputs from a camera, uploaded image, or web page enter the Be My Eyes app, GPT-4 processes both the visual content and the ongoing dialogue, and the resulting explanation is returned as immediately usable guidance for the user. The company beta-tested the GPT-backed assistant internally before broad release and highlighted that the same architecture can work across the physical and digital worlds. That gives Be My Eyes a more scalable accessibility layer than volunteer-only or line-by-line screen-reader experiences alone.
Images, screenshots, webpages, and user questions are sent into the Be My Eyes app, GPT-4 interprets the visual scene and conversational context together, and the app returns spoken or textual guidance the user can act on immediately.
Be My Eyes began developing a GPT-4 powered Virtual Volunteer within the Be My Eyes app
GPT-4 is able to summarize the search results the way the sighted naturally scan them
GPT-4 technology not only recognizes and names what's in there, but extrapolates and analyzes what you can make with those ingredients
In early February, the company started beta-testing the GPT-backed assistant with a small group of employees
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Scoring methodology
Customer Reference Value measures usefulness as a customer reference. Evidence Confidence measures the quality and traceability of available evidence, not independent verification.
Traceability
Field coverage shows which facts each source supports. Dates are shown only when documented by the source.
The public Organization JSON-LD for Be My Eyes includes numberOfEmployees value 432; 432 maps to Mid-market under the enrichment thresholds.
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