avint
Three agents live: Cost, Reliability, Lease

The airline planning stack,
rebuilt as agents.

avint is a suite of AI agents for airline network, fleet and cost decisions. Each agent owns one domain, calls the others when it needs them, and shows every step of its work.

Cost Modelagent
0.0sReady
Trace
  1. aerocost.search
    Resolve the codes
  2. aerocost.coverage
    Check what the answer will rest on before giving it
  3. aerocost.block_hour_cost
    Price the block hour on Lufthansa Group's own unit cost
  4. aerocost.cost_structure
    Split it into the slices that move independently
  5. aerocost.fuel_scenario
    Restate at today's jet fuel, because the published figure predates the step
Task

Hallo, what is the cost of a 32N for LH?

Waiting for a task

Showing Lufthansa Group. Nine carriers are loaded, all from their own filings.

The Cost Model is the pricing authority for the whole suite. Ask it in plain language, get the figure, what it rests on, and how far to trust it. Every number traces back to a source, and an unknown is shown as unknown, never defaulted.

Built to replace
  • Sabre
  • MIDT
  • Cirium
  • Custom BI
  • Consulting decks
  • The spreadsheet
The $40B problem

Airlines spend $40B a year on tools that don't talk to each other.

Distribution in one system, market data in another, schedules in a third, and the real analysis in a spreadsheet someone built in 2019. Every planning cycle starts by stitching these together by hand, and the stitching is where the weeks go.

The cost isn't the licences. It's the decisions that arrive late, the routes never evaluated because nobody had the time, and the signals that were sitting in one department while another one needed them.

$200K+
spent per planning cycle on manual route analysis
3 to 4%
of incremental revenue left on the table for lack of analysis time
6 to 8 wks
of delay per cycle from disconnected tools and siloed data
The platform

One system that reasons across the whole airline.

Every avint agent is also a tool. The Cost Model prices a block hour for the Lease agent, the Lease agent constrains the Fleet agent, the Fleet agent feeds the Network agent. Each one you add makes the others sharper, because they share context rather than exports.

01

Every agent is a tool

Each agent exposes what it knows over a standard interface, so any other agent, or your own systems, can call it mid-reasoning. No exports, no copies of the numbers.

02

Every answer shows its trace

You see which tools ran, what came back, and how long it took. A figure you can't trace is a figure you can't defend in a board meeting.

03

Your cost base, not an average

Fuel at your region's price for your period. Non-fuel on your carrier's published unit costs. A narrowbody in Scandinavia does not cost what one in Texas costs, and the model knows it.

Fleet Reliability agent

Where the operation loses time, from what actually flew.

ADS-B traces of every leg matched against the published schedule. Not a punctuality dashboard: it says which turnarounds are scheduled too tight, which routes are padded, how delay travels through the day, and what to change in the next schedule.

Fleet Reliabilityagent
0.0sReady
Trace
  1. schedule.load
    Load the published schedule and convert every leg to UTC
  2. adsb.match
    Match ADS-B traces to scheduled legs, reassemble split flights
  3. reliability.otp
    Measure punctuality against the published times
  4. reliability.propagation
    Trace delay through every rotation to find where it is born
  5. schedule.evaluate
    Test block padding and turnaround times route by route
Task

Where did we lose time in August, and what should we actually change in the winter schedule?

Waiting for a task
Lease Management agent

Return conditions, checked against reality.

Every lease clause tested against your live maintenance data, every shortfall priced by the Cost Model, and the whole portfolio ranked by money at risk per month you have left. Nothing rekeyed from a PDF.

Lease Managementagent
0.0sReady
Trace
  1. lease.load_portfolio
    Load active leases and return condition clauses
  2. maintenance.sync
    Sync maintenance status from your MRO system
  3. lease.check_conditions
    Test every clause against current and forecast status
  4. cost_model.penalty
    Price each shortfall via the Cost Model agent
  5. lease.rank
    Rank by exposure and time left to act
Task

Which leased aircraft have return conditions at risk in the next 12 months, and what does it cost if we miss them?

Waiting for a task
The agents

Each one owns a domain. Three are live today.

Every agent below runs on the same trace-and-output pattern you saw above. New ones ship as the suite grows, and each one already knows how to call the others.

  • Live

    Cost Model

    Localised block hour, delay cost by channel, Regulation 261 exposure and reactionary propagation, with provenance on every figure.

  • Live

    Fleet Reliability

    ADS-B traces matched to the published schedule. Where time is lost, how delay propagates through rotations, and what to change.

  • Live

    Lease Management

    Return conditions tested against live maintenance status, shortfalls priced, and the exposure ranked by how long you have to act.

  • Coming

    Route Planning

    Evaluate new routes, simulate launch scenarios and see the ripple across the hub before committing an aircraft.

  • Coming

    Network Simulation

    Model how adding or cutting a route cascades through the whole network.

  • Coming

    Fleet Management

    Match types to routes and utilisation, with lease and cost constraints already in the loop.

  • Coming

    Pricing

    Fare class and elasticity driven pricing that responds to market signals rather than last year's spreadsheet.

  • Coming

    Competitive Landscape

    Competitor capacity moves, market share shifts and schedule changes, tracked as they happen.

  • Coming

    Loyalty & Revenue

    Programme analytics, ancillary revenue and customer value, fed back into demand and pricing.

Working with

Airlines and the advisors airlines trust.

avint is built alongside operators and the strategy firms they already work with, so the agents answer the questions that actually come up in a planning meeting.

Talk to the team

Bring us a decision you're working on.

Half an hour with someone who has done airline network planning for twelve years. Bring a real route, a real lease, or a real delay problem and we'll run it through the agents live.