We built this because we lived it.

Osora was born inside a 4,000-person NASDAQ company where the AI team spent 12 months doing organizational intelligence by hand — sitting in hundreds of meetings, running requirement sessions across every team, building spreadsheets tracking 150+ use cases, iterating a Benefits Tracker through nine versions.

The result: $5M+ in identified AI value, $1.25M in influenced revenue, and a playbook that proved the approach works. But it took a year of manual work, and the knowledge lived in people's heads.

Osora is the platform that automates that process. It does in minutes what took months: captures how the organization works, extracts what matters, scores what's automatable, and provides the business case to act.

Why now

Three thresholds crossed simultaneously: meeting bots made conversations capturable at near-zero cost. Vision AI made screens readable without interrupting work. And extended context windows mean language models can reason over a 90-minute meeting and produce structured process definitions.

The gap between what AI can theoretically automate (94%) and what's actually deployed (33%) isn't a technology problem. It's a visibility problem. Osora closes it.