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 2,500+ real implementations → Prioritise by what's already paying off
Measurable ROI and competitive edge
Your shortlisted ideas, validated against 2,500+ 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 2,500+ real implementations → Prioritise by what's already paying off
Measurable ROI and competitive edge
Your shortlisted ideas, validated against 2,500+ 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%
Fraud signals buried in unstructured bank data. Generative AI now categorizes each account before models score 500 transactions per second.
Outsourced tools kept the team blind to their own data—no transcripts, no metrics—until they migrated everything in-house in 7 months.
With 96% of calls unreviewed, recurring patterns took months to surface. Now every call is evaluated for agent tone, empathy, and sentiment.
Manually updated profiles left skills stale. The first prototype took two hours per 1,000 consultants—now the agent covers 130K in minutes.
Debugging agents meant replaying sessions by hand. ML updates took a day to validate. Now every step is traceable in real time.
Most employees couldn't reach the data without an analyst. Refinery experts now build soft sensors through conversation, no code needed.
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.
Real-time fraud and identity verification that combines scoring models with AI reasoning over transaction context, customer history, and unstructured signals.
Fraud signals buried in unstructured bank data. Generative AI now categorizes each account before models score 500 transactions per second.
Outsourced tools kept the team blind to their own data—no transcripts, no metrics—until they migrated everything in-house in 7 months.
With 96% of calls unreviewed, recurring patterns took months to surface. Now every call is evaluated for agent tone, empathy, and sentiment.
Manually updated profiles left skills stale. The first prototype took two hours per 1,000 consultants—now the agent covers 130K in minutes.
Debugging agents meant replaying sessions by hand. ML updates took a day to validate. Now every step is traceable in real time.
Most employees couldn't reach the data without an analyst. Refinery experts now build soft sensors through conversation, no code needed.
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.
Real-time fraud and identity verification that combines scoring models with AI reasoning over transaction context, customer history, and unstructured signals.