Staff couldn't manually link 500k reviews to businesses shifting names. AI now phonetically matches and classifies every record.
A data-driven counter-trafficking organization monitors over 10,000 illicit massage businesses that pose as legitimate operations to facilitate illegal services.
Manual data collection could not scale to analyze 500,000 reviews or reconcile listings that lacked unique identifiers like tax IDs. Staff struggled...
“There are a lot of nuanced steps associated with data scraping and analysis, and we really wanted to automate the entire process instead of relying on our own data pipelines, which weren’t as efficient.”
The Network's Illicit business identification is part of this use case:
Nonprofit using data and research to disrupt human trafficking networks in the US.
Cloud computing platform and on-demand infrastructure services.
Helped The Network design and develop an AWS-based data ingestion pipeline using ML and AI.
Related implementations across industries and use cases
Manually sifting wartime data was dangerously slow. Now, AI scans social media to filter noise, flag threats, and locate missing civilians.
Surging texts buried urgent cases. Swahili-trained AI answers 70% of queries, freeing nurses to focus on high-risk symptoms.
Staff spent 30 minutes compiling one dossier. AI builds it in five, shifting focus from paperwork to career counseling.
Manually sifting wartime data was dangerously slow. Now, AI scans social media to filter noise, flag threats, and locate missing civilians.
Complex reverse engineering took experts a month. Now, AI agents dissect code and build defense plans in under 30 minutes.
Fragmented CRM data and manual spreadsheets bottlenecked a lean team. Now, staff use AI to clean records, segment donors, and draft emails.
Off-hour callers in crisis waited days for help. Now, voice AI fields calls, routes urgent cases to humans, and automates documentation.
Ad-hoc queries required custom dashboards. Now, specialized agents answer natural language questions with 99.9% accuracy.
Central IT couldn't reach the long tail of daily tasks. Now, 50% of staff use opt-in AI to scan contracts and prep for meetings.
Staff couldn't manually link 500k reviews to businesses shifting names. AI now phonetically matches and classifies every record.
A data-driven counter-trafficking organization monitors over 10,000 illicit massage businesses that pose as legitimate operations to facilitate illegal services.
Manual data collection could not scale to analyze 500,000 reviews or reconcile listings that lacked unique identifiers like tax IDs. Staff struggled...
“There are a lot of nuanced steps associated with data scraping and analysis, and we really wanted to automate the entire process instead of relying on our own data pipelines, which weren’t as efficient.”
The Network's Illicit business identification is part of this use case:
Nonprofit using data and research to disrupt human trafficking networks in the US.
Cloud computing platform and on-demand infrastructure services.
Helped The Network design and develop an AWS-based data ingestion pipeline using ML and AI.
Related implementations across industries and use cases
Manually sifting wartime data was dangerously slow. Now, AI scans social media to filter noise, flag threats, and locate missing civilians.
Surging texts buried urgent cases. Swahili-trained AI answers 70% of queries, freeing nurses to focus on high-risk symptoms.
Staff spent 30 minutes compiling one dossier. AI builds it in five, shifting focus from paperwork to career counseling.
Manually sifting wartime data was dangerously slow. Now, AI scans social media to filter noise, flag threats, and locate missing civilians.
Complex reverse engineering took experts a month. Now, AI agents dissect code and build defense plans in under 30 minutes.
Fragmented CRM data and manual spreadsheets bottlenecked a lean team. Now, staff use AI to clean records, segment donors, and draft emails.
Off-hour callers in crisis waited days for help. Now, voice AI fields calls, routes urgent cases to humans, and automates documentation.
Ad-hoc queries required custom dashboards. Now, specialized agents answer natural language questions with 99.9% accuracy.
Central IT couldn't reach the long tail of daily tasks. Now, 50% of staff use opt-in AI to scan contracts and prep for meetings.