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%
Mapping which companies built vs. bought AI agents would have taken months. Clay mined job postings and 10-Ks to rank 13K accounts in days.
Scheduling one interview took two weeks; now Maya handles every step via text, freeing recruiters to assess fit.
One advisor, booked weeks out. Refugees waited weeks for basics—housing, schooling, jobs. Viktor now answers instantly, 24/7.
Human sales teams clock out; buyers don't. Voice agents, accent-matched by region, now qualify and book site visits around the clock.
Hours searching SharePoint, days waiting for QA, reports rewritten when templates changed. Now two agents answer instantly from live docs.
No shared framework meant every AI initiative reopened control debates. Now teams independently reach the same governance decision.
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.
Foundation models that read sensor streams alongside maintenance logs, manuals, and technician notes to predict equipment failures.
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.
Mapping which companies built vs. bought AI agents would have taken months. Clay mined job postings and 10-Ks to rank 13K accounts in days.
Scheduling one interview took two weeks; now Maya handles every step via text, freeing recruiters to assess fit.
One advisor, booked weeks out. Refugees waited weeks for basics—housing, schooling, jobs. Viktor now answers instantly, 24/7.
Human sales teams clock out; buyers don't. Voice agents, accent-matched by region, now qualify and book site visits around the clock.
Hours searching SharePoint, days waiting for QA, reports rewritten when templates changed. Now two agents answer instantly from live docs.
No shared framework meant every AI initiative reopened control debates. Now teams independently reach the same governance decision.
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.
Foundation models that read sensor streams alongside maintenance logs, manuals, and technician notes to predict equipment failures.
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.