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.
NewConnect ChatGPT & Claude to this data — now available as API & MCP →
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%
Also available as API & MCP — bring the data into ChatGPT, Claude, or your own tools|API reference →
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.
NewConnect ChatGPT & Claude to this data — now available as API & MCP →
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%
Also available as API & MCP — bring the data into ChatGPT, Claude, or your own tools|API reference →
Reports read one by one, cohorts assembled in spreadsheets—weeks of work. Now physicians ask in plain language; answers arrive in seconds.
Their engineers were propping up overprovisioned LLM clusters instead of shipping. Bedrock took the upkeep; the team got back to building.
Three locations, three silos—headcount was guesswork, reports came back blank. One typed query now replaces an hour of manual merging.
Agents were evaluated on 4 calls a month. AI Scorecards now cover most conversations—QA became a coaching tool, not a compliance checkbox.
Recruiters juggled disconnected systems while managers fielded candidate calls from the back office. An AI now screens and engages 24/7.
Client analytics required SQL queries only engineers could write. Now CSMs pull performance reports in minutes with plain language prompts.
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.
Reports read one by one, cohorts assembled in spreadsheets—weeks of work. Now physicians ask in plain language; answers arrive in seconds.
Their engineers were propping up overprovisioned LLM clusters instead of shipping. Bedrock took the upkeep; the team got back to building.
Three locations, three silos—headcount was guesswork, reports came back blank. One typed query now replaces an hour of manual merging.
Agents were evaluated on 4 calls a month. AI Scorecards now cover most conversations—QA became a coaching tool, not a compliance checkbox.
Recruiters juggled disconnected systems while managers fielded candidate calls from the back office. An AI now screens and engages 24/7.
Client analytics required SQL queries only engineers could write. Now CSMs pull performance reports in minutes with plain language prompts.
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.