# Screen-Aware AI Support at West Coast University > Source: https://ibl.ai/case-study/west-coast-university ## Case Study 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. ### Quick Stats - **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 > "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 --- ## The Challenge ### 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. --- ## Screen-Aware Agents ### 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. --- ## Partnership ### "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. --- ## Model-Agnostic ### 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. --- ## No Per-Seat Pricing ### 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. **Why it matters:** the goal is to help every user who gets stuck, at any hour. A pricing model that charges per head punishes exactly that. ibl.ai's usage-based, flat-license model lets WCU expand support broadly instead of rationing it. [See the cost math](/llm-price-calculator) --- ## For University Leadership ### 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. --- ## Get Started 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. [Book a Demo](https://cal.com/iblai/30min) | [Calculate your savings](/llm-price-calculator)