Case Study
Screen-Aware AI Support at West Coast University
How West Coast University deployed ibl.ai agents that can see the user’s screen — delivering a level of guidance no text chat or phone call can match, on a flexible, model-agnostic platform with no per-seat pricing.
"We brought ibl.ai genuinely hard problems, and the answer was never 'no' — it was 'let us figure it out,' and they did, every time. No request was too complex, no challenge ever met with 'that's not possible' — the hardest things we put in front of them were the ones they solved best. Add a flexible, model-agnostic platform backed by a team genuinely on the leading edge of AI, and you have a partner, not a vendor. That's real partnership."
Marwan Alamat
Chief Information Officer, West Coast University
Screen-aware
Agents see the user's screen
Any LLM
Model-agnostic platform
No per-seat
Flat-rate licensing
24/7
Always-on user support
Why text chat and phone support kept falling short
Support that can’t see
A help-desk agent on a chat or a call has no idea what the user is actually looking at. Every question turns into “what do you see on your screen?” — a slow, error-prone game of description.
Users can’t describe it
Users rarely know the right names for buttons, fields, or error messages. When they can’t describe the problem, even a knowledgeable human can’t guide them to the fix.
Complex portals, blind
Registration, financial-aid, and learning portals are multi-step and unforgiving. Walking a user through them without seeing their screen leaves users stuck and staff repeating themselves.
An AI agent that sees what the user sees
West Coast University deployed ibl.ai agents with screensharing access. The user shares their screen, and the agent guides them in real time — pointing to the exact field, catching the error message, and walking through the next step. It’s the level of help a person on a text chat or phone call simply cannot give when they can’t see the screen.
Text chat / phone support
- Can't see what the user is looking at
- Relies on the user to describe the problem
- Long back-and-forth to locate a single button
- Easy to give the wrong instruction blind
- Limited by staff hours and queue length
- Hard to support multi-step portal workflows
ibl.ai screen-aware agent
- Sees the user's screen in real time
- Reads the actual error and field on the page
- Points to the exact element to click
- Guides step-by-step through the real workflow
- Available 24/7 — no queue, no hold music
- Built for the portals users actually use
The result: users get unstuck on the spot instead of waiting for a callback, and staff are freed from narrating screens they can’t see. The agent handles the routine “where do I click” moments so people can focus on the cases that genuinely need a human.
“The hardest things we put in front of them were the ones they solved best”
Screensharing-aware user support wasn’t an off-the-shelf feature — it was a hard problem WCU brought to ibl.ai. As Marwan Alamat describes it, the answer was never “no”; it was “let us figure it out.” The team listened, adapted to feedback, and built around what WCU’s users actually needed.
No request was too complex
WCU raised requirements other vendors would have declined. ibl.ai treated them as engineering problems to solve, not scope to push back on — and shipped.
They built around the users, not the roadmap
Rather than bending WCU's needs to fit a fixed product, the team adapted the platform to serve the users — the goal Marwan says actually mattered.
A team on the leading edge of AI
WCU got a partner working at the front of the field — fast to adopt new model capabilities like screensharing-aware guidance as they became viable.
A flexible, LLM-agnostic platform
The benefit Marwan calls out by name: ibl.ai is model-agnostic. WCU isn’t locked to one vendor’s model. The platform can run Claude, GPT, Gemini, Llama, or others, and switch as capability, cost, and privacy needs change — so the screen-aware agents always run on whatever model serves users best.
Pick the best model per task
Route simple guidance to a fast, low-cost model and reserve the strongest models for harder questions — without re-platforming.
Switch as the market moves
When a better or cheaper model ships, WCU adopts it. No vendor lock-in to a single LLM's pricing or roadmap.
Match privacy to the use case
Sensitive workflows can run on the model that meets the institution's data and compliance posture for that scenario.
Support every user without a per-seat penalty
Per-seat SaaS pricing makes 24/7 support for an entire user base prohibitively expensive — the bill scales with headcount whether or not users use it. WCU runs ibl.ai on flat-rate licensing plus actual model usage, so screen-aware help can be offered to every user without the cost ballooning as enrollment grows.
What the partnership delivered
Reframed around the benefits West Coast University’s CIO names directly — a platform that bends to the institution, not the other way around.
Support no one else could give
Screen-aware agents close the gap that text chat and phone lines structurally cannot — guidance grounded in exactly what the user is looking at.
A partner who solves, not deflects
Hard, specific requirements got built rather than declined. The relationship behaves like an extension of WCU's team, not a vendor managing a contract.
Freedom to choose the model
Model-agnostic by design, so WCU follows the best capability and price over time instead of being locked to one provider's decisions.
Cost that doesn't punish scale
Flat-rate licensing plus usage means support can reach the whole user base without the linear per-seat blow-up of typical SaaS AI.
Want screen-aware AI support for your users?
Deploy ibl.ai agents that see the screen and guide users in real time — on a flexible, model-agnostic platform with no per-seat pricing, backed by a team that solves the hard problems.