Levo Integrates With Portside's Avianis to Match Charter Requests to Operator Fleets and Pricing

Levo has integrated with Avianis, the flight scheduling and charter management solution from Portside. Operators using Avianis can connect their account to Levo and run an AI-powered sales workflow, instead of working inbound charter demand across a shared inbox and a scheduling system. The operator handles setup from its own Avianis and Levo settings, and no developer work is required.

Requests reach Levo from channels the operator already uses: its own shared sales inbox, demand originating in Levo, and NBAA AirMail. Once the two systems are connected, Levo checks each request against the operator's fleet and the aircraft's actual location at the time. Operators set their own controls, including how far they are willing to reposition, how recent a request is, and the booking timeline.

Matched requests appear in a live list that updates as new requests arrive. Each row shows the requested itinerary, the matched aircraft and its current location, an estimated price, and whether the request came from a broker or a retail contact, as classified by Levo AI.

Pricing comes from the operator's own configuration in Avianis. A matched request arrives with the quote already assembled (legs, fees, taxes) and priced by Avianis against the operator's pricing rules and any contract rates set up. Joe Moeggenberg, president and CEO of Levo, said the AI matches against the operator's own fleet and pulls the price from the operator's own system. Janine Jamison, vice president of Growth and Product Strategy at Levo, said nothing leaves Levo without someone on the operator's team reviewing and sending it.

Charter sales has long depended on people reading requests, checking where aircraft are, and building quotes by hand. Linking the intake layer to the scheduling system's live fleet positions and pricing rules moves that work toward a model where the quote exists before a person looks at it. The human step that remains is review and sending, which is the control point Levo's own executives emphasise.

For operators, the practical effect is on response time and consistency. A quote built from the operator's own Avianis configuration, including contract rates, reflects the pricing logic already in place rather than a salesperson's recollection of it. The repositioning and timeline controls also mean the operator, not the software, decides which requests are worth pursuing.

The broker versus retail classification shown on each row matters because the two request types are usually handled differently in charter sales. How accurately that classification holds up in daily use, and how operators tune their repositioning limits, will be the clearest tests of whether the matching earns trust.