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Research Reports.

Browse our collection of detailed market research reports. Click on any report to view comprehensive analysis and insights.

Flight compensation recovery agent for frequent flyers

Airlines don't make it easy to collect what they owe. Regulations mandate compensation for qualifying delays. Airlines reject most first-attempt claims, counting on travelers not to follow up. The claims industry that sprang up around this takes 35% and only engages after the disruption is over. For frequent flyers, the bigger cost isn't the missed payout. It's the hour on hold rebooking instead of prepping for the meeting. Reroute monitors flights in real time and acts the moment something breaks. A cancellation triggers instant rebooking based on stored preferences for seat, loyalty program, and connections. The platform checks whether the delay qualifies for compensation, assembles documentation, and files the claim. A text lands before the gate agent finishes the first in line. Outcome data feeds back into the filing engine, sharpening which claims succeed by airline, route, and disruption type. The first build is a monitoring layer connected to public airline data feeds. When a disruption hits, the system matches it against compensation rules for the relevant carrier and generates a prefilled claim. Rebooking logic layers on top, pulling stored preferences to rank alternatives by loyalty program, seat type, and connection risk. The claims engine is the hardest piece. Airlines reject on technicalities and slow-walk payouts. Starting with European carriers makes sense because payout rules are standardized. U.S. regulations are still carrier-specific, so filing logic needs to be modular from day one.

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360 responses
24 personas
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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.

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240 responses
48 personas
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