Shadow AI detection for companies without a compliance team

Stack Breach scans a company's tools for unauthorized AI usage: browser extensions, API calls, third-party integrations running through Slack, GSuite, and Microsoft 365. That Chrome extension support installed? It sends every ticket to an external API with no data retention policy. Stack Breach flags it, maps the exposure, and generates a report formatted for the auditor, not the engineer. Every company monitored sharpens what the system knows about how shadow AI actually shows up in practice. Build a monitoring agent that logs outbound calls from company devices to known AI provider APIs. Each flagged call gets tagged with what data it carried and which compliance rule it broke. A healthcare company routing patient notes through ChatGPT is a different violation than a design agency using Midjourney on client assets, so the rule engine needs to be configurable per customer from day one. Onboard three companies manually. Sit with their IT teams, learn what real violations look like versus normal usage, and tune the detection logic until it catches 90 percent of unauthorized AI without generating noise that gets ignored. A 200-person company pays less for a year of Stack Breach than one hour of legal cleanup after a failed audit. The first customers are companies where the audit already happened and the cleanup is still fresh. One fund relationship seeds 30 customers overnight. Every company monitored adds data on which tools create which risks in which industries. That library makes detection more accurate for every future customer and harder to replicate without matching volume.