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%
Every new meeting question triggered days of data prep. Finance teams now ask the data lake directly and test hypotheses in minutes.
Friday inquiries sat until Monday; prospects had moved on. AI now responds in seconds, and agents return to a calendar of confirmed tours.
Rapid growth buried staff in admin; employees had already turned to ungoverned AI. Weeks of controls, then Copilot replaced shadow use.
23% of turns were disengaging — Cait only found out after each conversation ended. State inference now runs live and adjusts mid-turn.
One BD person, 3–10 leads daily, days behind on research. Clients moved on. A plugin now scores fit, creates deals, and posts to Slack.
Every shoot meant assembling a full studio in his living room—he'd go months between videos. A mic and an AI avatar replaced the cameras.
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.
LLMs that analyze customer calls, chats, and meetings — generating coaching summaries, deal insights, quality scores, and sentiment trends.
Forecasting demand, credit risk, churn, and sales pipelines — foundation models extending traditional forecasting with reasoning over unstructured signals like emails, calls, and reports.
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.
Every new meeting question triggered days of data prep. Finance teams now ask the data lake directly and test hypotheses in minutes.
Friday inquiries sat until Monday; prospects had moved on. AI now responds in seconds, and agents return to a calendar of confirmed tours.
Rapid growth buried staff in admin; employees had already turned to ungoverned AI. Weeks of controls, then Copilot replaced shadow use.
23% of turns were disengaging — Cait only found out after each conversation ended. State inference now runs live and adjusts mid-turn.
One BD person, 3–10 leads daily, days behind on research. Clients moved on. A plugin now scores fit, creates deals, and posts to Slack.
Every shoot meant assembling a full studio in his living room—he'd go months between videos. A mic and an AI avatar replaced the cameras.
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.
LLMs that analyze customer calls, chats, and meetings — generating coaching summaries, deal insights, quality scores, and sentiment trends.
Forecasting demand, credit risk, churn, and sales pipelines — foundation models extending traditional forecasting with reasoning over unstructured signals like emails, calls, and reports.
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.