Privesa Launches AI Platform to Automate Charter Brokerage Workflows

Privesa, a Naples, Florida-based startup founded by Logan Cassidy, has launched an AI-powered platform designed to automate workflows for business aviation charter brokerages. The company launched in August and is currently running its first proof of concept with an unnamed charter brokerage, whose founder is the platform's current sole user as he evaluates it ahead of a broader internal rollout.

Cassidy describes Privesa as an intelligent orchestration layer between supply and demand in business aviation. The platform automates 80-85% of the repetitive back-office work charter brokers perform, including sourcing operators, evaluating quotes, and generating client proposals. It draws on proprietary data covering aircraft positioning, operator quoting and response history, and safety and reliability records to identify matched operators for each trip, then sends each a structured request. As quotes arrive, Privesa's sourcing agents extract details such as wi-fi availability, maximum passenger count, or seat configuration, and compile options into a client proposal within minutes; unusual queries are escalated to the broker.

Cassidy cited two examples of the system in operation. In one, the platform identified an option $10,000 below the next-best quote before the broker arrived at his desk. In another, on an international trip, conflicting information about Starlink wi-fi availability appeared within a single operator email thread; the platform flagged the discrepancy and alerted the broker before it reached the client.

Cassidy's near-term goal is to sign the first ten brokerages, with a longer-term ambition to reshape the charter market for both brokers and operators. He previously worked in enterprise IT sales and artist management, and said he moved into charter brokerage after connecting with a jet operator at a music festival in Jacksonville, Florida. He built Privesa over approximately six months, working twelve-hour days.

Charter brokerage has long depended on brokers manually chasing operators for quotes, comparing cabin and connectivity details by hand, and assembling proposals under time pressure — work that is repetitive but still requires judgment when quotes conflict or data is incomplete. Tools that automate sourcing and first-pass comparison target exactly that layer, leaving brokers to handle exceptions rather than routine matching.

The Starlink wi-fi discrepancy example points to a structural issue in the segment: quote data often arrives unstructured, by email, and inconsistencies between what an operator states and what is actually available can reach a client undetected. A system that catches those gaps before a proposal goes out addresses a real operational risk rather than just a time-saving convenience.

Whether this becomes a broader shift depends on what happens after the single pilot user expands to the rest of that brokerage, and whether Privesa converts its near-term target of ten signed brokerages into paying, multi-user accounts. Those adoption numbers, not the proof-of-concept results alone, will indicate if the platform changes how brokers operate rather than simply assisting one founder's workflow.