We work with founders across industries who need field-tested data instead of assumptions. Our first available dataset is also our rarest: five years of adult-industry booking and safety intelligence, information almost impossible to source ethically anywhere else — now available for license.
We're building out licensable data across multiple sectors. Most are still in development — our adult-industry dataset is live today because it's the one hardest to source, and the one safety-focused products need most urgently.
Booking and service-timing behavior for hospitality platforms.
Variation and scope-creep patterns from commercial trade work.
Risk-signal data for independent and mobile service workers.
Every dataset in this space is a bad-client blacklist. That's maybe 10% of the job. This is the other 90%: spotting time-wasters, converting inquiries into bookings, working the hustle and timing across a week, keeping clients calm — outcome-linked, not guessed.
Ugly mugs lists tell an agent who to avoid. Nobody has structured the harder skill: turning a first message into a booked, repeat client.
Most contacts aren't a safety problem — they're time-wasters or genuine clients who need the right handling. None of that is in a warning list.
Reply speed and day-of-week matter as much as what you say — a pattern that only exists in outcome-linked field data.
Lowering a nervous client's anxiety is built from hundreds of reps, not a canned line. A generic dataset can't reproduce that.
A booking closing is one data point. Whether it became a repeat client is what actually trains an agent to improve.
The dataset is organized around getting a booking confirmed and run well — with safety screening included as one supporting category, not the whole product.
Scraped text approximates what was said. It can't capture the operational judgment that only comes from running the booking — what it costs to deliver and how it's paced without burning out.
This is my own field experience, converted to structure. It is not scraped, not third-party, and not sold as raw communications.
Every record comes from my own five years in the field. Nothing sourced from other workers, forums, or third parties.
Names, numbers, and locations are stripped before a record is categorized. The taxonomy is built from pattern, not personal data.
Each pattern is tagged to what actually happened after — booked or not, repeat or not. Validated signal, not assumption.
Access is a data license with clear terms on use, exclusivity, and retention — reviewed before anything changes hands.
A small refundable deposit reserves your place. Full taxonomy sample, terms, and pricing follow an initial fit check.