Indeed, artificial intelligence is no longer confined to basic automation or rule-based responses; its veins and arteries are growing to all corners of the CX world.
Yet despite its promise, agentic AI often lacks something profoundly human: vision.
Even the most advanced systems can misjudge or stall without seeing what’s happening in real time.
Brion Johnson, Director of PreSales at TechSee, explained that the role of visual support in data solutions is a “fantastic way to present information.”
“If you have a router or a Wi-Fi extender and don’t know how to set it up, TechSee can provide detailed visual instructions on top of your images, guiding you on how to set it up, plug it in correctly, and ensure the right cables are connected.”
The Visibility Gap: Why Context Can Still Elude AI
Whether it’s a broken appliance, a damaged product, or a misconfigured device, AI systems frequently rely on secondhand descriptions, which can often be incomplete, ambiguous, or imprecise.
This “visibility gap” leads to delayed resolutions, misdiagnoses, and over-reliance on human intervention.
The real issue? Without visual input, AI can’t assess environmental context, confirm visual clues, or adapt to nonverbal variables.
Johnson picked up on this notion, “Through our guided resolution, users can take a picture at each step of troubleshooting, be told if they’re doing the right thing, and visually guided at each step.”
“These tools allow AI and agents to access what the customer sees jointly, translating physical context into actionable intelligence, and practical guidance.”
TechSee’s platform leads this evolution, offering visual interaction layers that integrate seamlessly with existing CX systems.
Contact centers need to verify that the issue has been successfully resolved. According to Johnson, the best way is by capturing images, annotating live feeds, and overlaying step-by-step guidance.
Introducing SophieAI Agents
TechSee is on the frontline of closing the visibility gap through its SophieAI Agents.
Sophie’s Visual Agentic AI continuously learns from every interaction and system asset, capturing and building on organizational expertise.
It leverages this evolving knowledge to enhance or automate service experiences across onboarding, contact centers, and field operations.
SophieAI Agents engage users through natural language, both chat and speech, coupled with augmented reality overlays for real-world visual support.
Combining visual input, text, voice, and contextual data gives the AI a “deep understanding of issues and delivers intuitive visual guidance.”
This closes the experience gap, empowering even novice users to easily solve complex problems.
Empowering the Human-AI Partnership – Seeing is Believing
This technology empowers users, and visual data can be a key to unlocking significant barriers for the contact center agents and field teams.
Far from replacing agents, visual AI elevates them. Contact center teams gain clarity on situations when connecting with the customer.
This confidence translates into faster interactions, less stress, and better outcomes.
Meanwhile, the AI acts as a silent partner, guiding agents and reducing the guesswork that typically bogs down service calls.
We don’t just see the problem; we can see the solution.
Johnson added, “Several companies take seven calls to close a ticket fully. With visual, it’s one, period.”
Agentic AI Needs Eyes, Not Just Brains
Johnson explained, “Take a trainee field service technician. Maybe they don’t know the answer to a technical problem. Who do they call? How do they get the support they need? Our perspective is visual.”
Through visuals, this hypothetical trainee can get a subject matter expert to examine the issue and give the guidance they need more efficiently.
To unlock the full potential of agentic AI, we must let it “see.”
Visual interactions aren’t just a technological add-on; they can become a foundational capability, a bridge between initiative and understanding, automation and empathy.
Want to hear more TechSee insights? Catch our latest CX Today Video here.
