With numbers to prove it.
Explore all use casesSifting 100k weekly logs took months. Now, AI personas simulate customer dialogue to test hypotheses in days for negligible cost.
Manual review of 18,000 entries was slow and inconsistent. AI now standardizes categorization, cutting process time by 75%.
Classifying 100 comments took an hour, forcing sampling. Llama 3.3 now sorts every review by issue type to prioritize fixes.
Managers manually tracked monthly volume. AI now analyzes 80,000 entries an hour to reveal long-term sentiment trends.
Analysts spent hours manually reviewing surveys. Gemini now processes unstructured feedback in minutes, speeding up reporting.
Manual analysis took months. AI now sorts input from 7,700 residents, saving 28 days of work and targeting projects for federal funding.
Social data bottlenecks slowed insights. Marketers now query live campaigns in plain English to spot emerging trends instantly.
Analysts manually sifted raw data for two days per cycle. Gemini now ingests and summarizes massive datasets in a single pass.
Transcripts mask uncertainty. Models now track vocal stress and facial cues to predict policy shifts that text tools miss.
Understand what's working with 2,876 recent AI case studies with quantified results. We break down every case study the same way, so you can find and prioritize high-impact strategies for your exact context.