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 2,700+ real implementations → Prioritise by what's already paying off
Measurable ROI and competitive edge
Your shortlisted ideas, validated against 2,700+ 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 2,700+ real implementations → Prioritise by what's already paying off
Measurable ROI and competitive edge
Your shortlisted ideas, validated against 2,700+ 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 →
Decades of archive footage, each clip taking 1–2 hours to hunt and cut. AI now tags players and moments — from idea to content in minutes.
Weeks of scattered workshops to scope a single use case. An AI intake agent now delivers briefs, architecture, and prototypes in days.
Multi-step research ran one search at a time, burning tokens on extended reasoning. Astra takes fewer steps and fans work across sub-agents.
Even business analysts had to learn SQL just to run queries. Now teams ask in plain Portuguese — logistics, sales, and fraud self-serve.
Finance, supply chain, and field data scattered across cloud and on-prem systems—no unified view of profitability. One lakehouse, real-time.
Each funding partner took 12 hours to vet. A Copilot agent now scans their news and websites, handing fundraisers a risk summary to review.
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.
Foundation models that read sensor streams alongside maintenance logs, manuals, and technician notes to predict equipment failures.
Real-time fraud and identity verification that combines scoring models with AI reasoning over transaction context, customer history, and unstructured signals.
Decades of archive footage, each clip taking 1–2 hours to hunt and cut. AI now tags players and moments — from idea to content in minutes.
Weeks of scattered workshops to scope a single use case. An AI intake agent now delivers briefs, architecture, and prototypes in days.
Multi-step research ran one search at a time, burning tokens on extended reasoning. Astra takes fewer steps and fans work across sub-agents.
Even business analysts had to learn SQL just to run queries. Now teams ask in plain Portuguese — logistics, sales, and fraud self-serve.
Finance, supply chain, and field data scattered across cloud and on-prem systems—no unified view of profitability. One lakehouse, real-time.
Each funding partner took 12 hours to vet. A Copilot agent now scans their news and websites, handing fundraisers a risk summary to review.
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.
Foundation models that read sensor streams alongside maintenance logs, manuals, and technician notes to predict equipment failures.
Real-time fraud and identity verification that combines scoring models with AI reasoning over transaction context, customer history, and unstructured signals.