Context Windows brings together credible AI case studies from the open web,
so you can pick and prioritise the use cases that are already working.
Real-world implementations from
Ideas from your team, no outside signal → Best guess prioritization
Demos that impress, outcomes that don't
Ideas from your team, no outside signal
Best guess prioritization
Demos that impress, outcomes that don't
Your shortlisted ideas, validated against 2,400+ real implementations → Prioritise by what's already paying off
Measurable ROI and competitive edge
Your shortlisted ideas, validated against 2,400+ real implementations
Prioritise by what's already paying off
Measurable ROI and competitive edge
Use case intelligence lets you see the winners,
so you can be in the 5%
Context Windows brings together credible AI case studies from the open web,
so you can pick and prioritise the use cases that are already working.
Real-world implementations from
Ideas from your team, no outside signal → Best guess prioritization
Demos that impress, outcomes that don't
Ideas from your team, no outside signal
Best guess prioritization
Demos that impress, outcomes that don't
Your shortlisted ideas, validated against 2,400+ real implementations → Prioritise by what's already paying off
Measurable ROI and competitive edge
Your shortlisted ideas, validated against 2,400+ real implementations
Prioritise by what's already paying off
Measurable ROI and competitive edge
Use case intelligence lets you see the winners,
so you can be in the 5%
Quality reviews dragged for weeks, gated by a handful of specialists. Now employees build agents that move them through in about an hour.
Post-merger, consultants scattered across Zendesk and Outlook, leaving leadership blind. AI agents now back each consultant on one platform.
Robot voice undercut accurate answers: callers tuned out. Natural voice changed that — more engaged, longer calls, fewer human handoffs.
One AE held the team's institutional knowledge—90% of his day in Slack. A digital double in his voice freed him to sell.
Managers split between guiding 78-question calls and typing notes, losing context at handoff. AI transcribes calls; they focus on the match.
Rugby match data existed but never reached fans live. AI now turns it into 65+ on-screen insights per game, built and approved by analysts.
AI agents that engage website visitors and inbound prospects 24/7 — qualifying interest, scoring intent, and booking meetings with sales reps automatically.
AI agents that autonomously handle customer requests — processing refunds, modifying accounts, making bookings, and resolving issues without human intervention.
Forecasting demand, credit risk, churn, and sales pipelines — foundation models extending traditional forecasting with reasoning over unstructured signals like emails, calls, and reports.
LLMs that analyze customer calls, chats, and meetings — generating coaching summaries, deal insights, quality scores, and sentiment trends.
AI-assisted creation of written, visual, and multimedia content across marketing, communications, and publishing workflows.
Foundation models that read sensor streams alongside maintenance logs, manuals, and technician notes to predict equipment failures.
Quality reviews dragged for weeks, gated by a handful of specialists. Now employees build agents that move them through in about an hour.
Post-merger, consultants scattered across Zendesk and Outlook, leaving leadership blind. AI agents now back each consultant on one platform.
Robot voice undercut accurate answers: callers tuned out. Natural voice changed that — more engaged, longer calls, fewer human handoffs.
One AE held the team's institutional knowledge—90% of his day in Slack. A digital double in his voice freed him to sell.
Managers split between guiding 78-question calls and typing notes, losing context at handoff. AI transcribes calls; they focus on the match.
Rugby match data existed but never reached fans live. AI now turns it into 65+ on-screen insights per game, built and approved by analysts.
AI agents that engage website visitors and inbound prospects 24/7 — qualifying interest, scoring intent, and booking meetings with sales reps automatically.
AI agents that autonomously handle customer requests — processing refunds, modifying accounts, making bookings, and resolving issues without human intervention.
Forecasting demand, credit risk, churn, and sales pipelines — foundation models extending traditional forecasting with reasoning over unstructured signals like emails, calls, and reports.
LLMs that analyze customer calls, chats, and meetings — generating coaching summaries, deal insights, quality scores, and sentiment trends.
AI-assisted creation of written, visual, and multimedia content across marketing, communications, and publishing workflows.
Foundation models that read sensor streams alongside maintenance logs, manuals, and technician notes to predict equipment failures.