Scaling left knowledge trapped in 20+ tools. AI indexed the stack, letting agents instantly pull answers from Slack and Salesforce.
A cloud-native data streaming provider rapidly scaled from 250 to over 2,000 employees while serving more than 4,000 customers with real-time data infrastructure.
Essential knowledge became fragmented across 20 distinct tools, creating "sand in the gears" that slowed down distributed teams. Support and sales...
“We had a lot of sand in our gears when it came to finding information. Our challenge wasn’t having too many duplicative tools — it was that knowledge was spread across best-of-breed systems.”
Data streaming and processing platform built on Apache Kafka.
AI-powered enterprise search and assistant platform for workplace knowledge.
Related implementations across industries and use cases
Documentation sprawled as staff doubled. AI now synthesizes notes and specs, replacing hours of hunting with instant answers.
Staff scoured dispersed docs to answer technical queries. An AI now scans internal data to provide answers in under a minute.
Buried info forced staff to recreate existing documents. Unified AI search now connects data across apps, saving 2,000+ hours monthly.
Engineers manually correlated alerts across systems. AI agents now diagnose issues and suggest fixes, cutting recovery time by 35%.
Minor edits required days of crew coordination. Now, staff use avatars to modify dialogue and translate languages instantly.
Seven analysts manually wrote notes for 200 products. AI agents now digest fact sheets to draft compliant commentary instantly.
Forty entities duplicated work, stalling claims for days. A global AI engine standardized workflows, cutting settlement time to one day.