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AI for Aerospace

The fault is in the data days before it reaches the tarmac.

We engineer AI for fleet reliability and MRO teams: condition monitoring, predictive maintenance, parts forecasting, and AD and SB compliance search.

Built on your own sensor data, your maintenance platform, and the oversight your regulator expects.

Discuss your fleet reliabilitySee how the system works

The operational reality

A fleet is thousands of parts. Each has a service life. Each has a regulatory record.

The next AOG is already in the sensor data. It arrives at the gate days later.

Uptime is the business. Vigilance is the product.

Felt by Fleet Reliability, Maintenance, Flight Ops, Engineering, and the MRO leaders who absorb the schedule when an aircraft goes AOG.

  1. 01

    Condition monitoring

    Sensor data streams off the aircraft between flights and during flight; engineering watches a handful of parameters against known thresholds.

    Friction · The signal that mattered was in a different parameter nobody was watching.

  2. 02

    Maintenance planning

    Planners schedule C and D checks around the flight schedule, parts availability, and crew certifications.

    Friction · A slipped check cascades into cancellations; a check pulled early loses the asset for days.

  3. 03

    AD and SB compliance

    Airworthiness Directives and Service Bulletins land continuously; engineering decides applicability, planners decide when.

    Friction · The applicability search is a long afternoon in a document pile that never shrinks.

  4. 04

    Parts and forecasting

    Rotables and consumables move through pools, repair shops, and vendors; shortages ground aircraft that could have flown.

    Friction · Forecasting runs on last quarter spreadsheet; actual demand already moved.

  5. 05

    Flight ops data

    FOQA, QAR, and CVR data lands after every flight; events and exceedances are reviewed for safety trends.

    Friction · Trends emerge months later; the aircraft has already been flying the pattern.

Swipe the workflow

Where the work breaks

The friction is in the places nobody budgets for.

  • 01

    A sensor drift is visible days before the component flags.

    How we fix it · A system we build catches this before it costs you.

    Impact · The AOG happens on the tarmac instead of a scheduled check; the aircraft loses a day of flying.

  • 02

    AD applicability searches eat an engineering afternoon per bulletin.

    How we fix it · A system we build catches this before it costs you.

    Impact · Compliance is on time but engineering time is the single scarcest resource in the department.

  • 03

    Parts forecasts are a quarter behind the actual flight schedule.

    How we fix it · A system we build catches this before it costs you.

    Impact · Rotables sit in a pool that is not the one the fleet needs; aircraft wait on a part that was in another city.

  • 04

    MEL open times stretch past the operational limit.

    How we fix it · A system we build catches this before it costs you.

    Impact · Dispatch reliability drops; the schedule starts to absorb delays that should not exist.

  • 05

    FOQA trend reviews surface the pattern months after the first exceedance.

    How we fix it · A system we build catches this before it costs you.

    Impact · Safety response lags; a known-bad behaviour has already been flown dozens of times.

What we would build

Systems, not features. Each with its own job.

  • 01

    Predictive maintenance on your sensor data

    The failure is in the data days before it shows up on the ramp.

    Who benefits · Fleet Reliability, Director of Maintenance, and the engineering leads.

    Inputs
    ACARS and QAR downloads, in-service sensor streams, component service-life records from your maintenance platform, and historical removal data for the fleet.
    What the system does
    A per-component model learns the drift pattern that precedes a removal, from your own fleet history, and flags the aircraft and the component with a confidence score and the window to act.
    Output
    A flag inside your maintenance platform, with a trend chart, a suggested maintenance action, and the regulation reference most likely to apply.
    Benefit
    Unscheduled AOGs become scheduled checks; dispatch reliability holds across the fleet.
    Human stays here
    Every flag is a draft task for a licensed engineer. The system drafts, cites, and queues; it never signs off on airworthiness.
  • 02

    AD and SB compliance search

    The applicability question is in a document pile that is still growing.

    Who benefits · Engineering, airworthiness, and compliance leaders.

    Inputs
    The regulator feeds (FAA ADs, EASA ADs, OEM SBs), your fleet configuration, your component serials, and your prior applicability decisions.
    What the system does
    A retrieval system indexes the regulatory corpus and your configuration; a question returns the ADs and SBs that apply to this tail, with the paragraph that matched and your prior decisions on similar bulletins.
    Output
    A direct, cited answer per bulletin: applicable, not applicable, or borderline for engineering review.
    Benefit
    Compliance work compresses from an afternoon per bulletin to a few minutes of review per flagged match.
    Human stays here
    Every answer cites the regulatory source. Applicability decisions remain an engineering sign-off, never the system.
  • 03

    Parts forecasting that moves with the schedule

    Rotables sit in the wrong pool while aircraft wait on the right part.

    Who benefits · Supply chain, materials, and the MRO shop leaders.

    Inputs
    Fleet schedule, component removal history, repair-shop turnaround times, pool movements, and vendor lead times.
    What the system does
    A per-SKU, per-base forecast model that updates as the schedule changes, so the pool reflects next month usage rather than last quarter spreadsheet.
    Output
    A moving stocking plan per base, with suggested transfers, repair-shop prioritisation, and vendor orders.
    Benefit
    AOG hours caused by parts drop; working capital tied up in the wrong pool drops with it.
    Human stays here
    Materials leaders approve every transfer and every order. The system drafts; it never buys.
  • 04

    Flight ops data triage

    FOQA trends emerge months after the first exceedance.

    Who benefits · Flight Ops, Safety, and the training leaders.

    Inputs
    FOQA and QAR downloads, event taxonomies, aircraft and route metadata, and your historical trend baselines.
    What the system does
    A clustering model groups exceedances across the fleet and surfaces the ones that are rising, with a route and aircraft breakdown and a sample of events for a safety analyst.
    Output
    A weekly review packet of rising clusters, each with the aircraft, routes, and sample events behind it.
    Benefit
    Safety response moves from months to weeks; training interventions land before the pattern becomes a report.
    Human stays here
    A safety analyst owns every classification. The system groups and ranks; it never writes a safety recommendation on its own.
  • 05

    MEL and deferral workflow

    MELs stay open past the operational limit because the queue is manual.

    Who benefits · Line maintenance, planning, and dispatch control.

    Inputs
    Open MEL state from your maintenance platform, aircraft rotation, parts availability, and the operational interval for each deferral.
    What the system does
    The system watches every open MEL against its interval and the next planned maintenance opportunity, and flags the ones at risk of expiring before they are addressed.
    Output
    A prioritised queue of MELs with the aircraft, the deadline, and the nearest planned maintenance window.
    Benefit
    MEL open times drop; dispatch reliability holds without pulling aircraft off the line unexpectedly.
    Human stays here
    Maintenance planners and dispatch control approve every rescheduling. The system surfaces risk; it does not move the aircraft.

Show the system

What it could look like in your hands.

A design concept, not a shipped product. Interfaces like this get drawn out before any code lands, so the system reads back the way the people using it work.

reliability / predictive maintenance

Aircraft in fleet

68

A320 and B737 narrowbody

Open MELs

41

7 within 48h of interval

Predicted alerts (7d)

9

across 6 aircraft

AOG prevented (30d)

122 h

scheduled vs unscheduled

Fleet watchlist

TailModelHrs sinceNext checkSensor health
N-XXX1A320-200912C-check in 48h94
N-XXX2A320-2001180C-check in 220h78
N-XXX3B737-800640A-check in 310h86
N-XXX4B737-8001420C-check in 95h71
N-XXX5A320neo420A-check in 420h92
Synthetic data. This is a design concept of how a KPI strip, a fleet watchlist, and a sensor drill-down could sit together in a reliability engineer hands.

End-to-end workflow

From the trigger to the outcome.

A representative path from a sensor stream to a signed task card. Automated stages run continuously; every airworthiness decision stays with a licensed engineer.

  1. 01

    Sensor stream lands

    ACARS and post-flight QAR downloads land per flight; in-service streams land continuously; data is tagged to aircraft, component, and flight leg.

    Integration
  2. 02

    Drift model watches

    Per-component models trained on your fleet history score the drift pattern that typically precedes removal, with a confidence band.

    Automated
  3. 03

    Candidate flag raised

    When drift exceeds a configured threshold, a draft task is created in your maintenance platform with the trend, the suggested action, and the regulation reference.

    Automated
  4. 04

    AD and SB match checked

    The system checks the flagged component against open ADs and SBs for the type; if the match is borderline, the flag is marked for engineering review before planning sees it.

    Guardrail
  5. 05

    Engineering review

    A licensed engineer reviews the flag, the trend, and the cited regulation; approves, modifies, or rejects the task. Nothing routes to planning without this step.

    Human in loop
  6. 06

    Planning scheduling

    Planning slots the task into the next viable check, with parts availability confirmed through the forecasting view.

    Human in loop
  7. 07

    Audit trail written

    The flag, the review, the decision, and the task card all log with model version, inputs, engineer ID, and planner ID in your maintenance platform.

    Integration

How exceptions are handled

  • If model confidence is below threshold, the flag is deferred rather than drafted, so engineering is not noise-fed.
  • If the regulatory reference is ambiguous, the flag is routed to engineering review instead of being auto-cited.
  • If a part is on backorder, the forecasting view flags the schedule risk rather than quietly slipping the task.
  • If a sensor stream fails to land, the system reports the gap rather than scoring on partial data.

How it is engineered

Built on your stack, not ours.

Design choices that make this work with your maintenance platform, your regulator posture, and your engineering team, not against them.

01

Maintenance platform integration

Compatible with AMOS, TRAX, and the common MRO platforms through their supported interfaces. We write back only where the platform approves it; we never silently update airworthiness state.

02

Sensor and flight-data ingestion

ACARS, QAR, FOQA, and vendor telemetry (compatible with GE Digital, Boeing AnalytX, Honeywell Forge) are tagged to aircraft, component, and flight leg, with bounded staleness guarantees.

03

Regulatory retrieval

FAA ADs, EASA ADs, and OEM SBs are indexed with your fleet configuration and your prior applicability decisions. Every answer carries a cited paragraph and the matched aircraft serial.

04

Identity and access

SSO through your existing identity provider. Every engineering review and every planner decision is attributable; agents never act under a shared service account.

05

Data boundary

Operational and sensor data remain in your tenant or a dedicated environment we operate for you. Where ITAR or EAR applies, environments are segregated by cleared personnel and audited.

06

Observability and evaluation

Every flag, every citation, every forecast logs its inputs, model version, and outcome; an evaluation harness watches prediction precision, false-positive rate, and parts-forecast error.

What the business will measure

Numbers the operator already watches.

We agree on metrics and baselines before building. These are the numbers a reliability team usually watches when deciding whether a system is working.

  • 01

    Unscheduled AOG hours

    Baseline today

    AOG hours per month, by base, aircraft type, and root cause.

    How it moves

    Predictive flags move unscheduled events to scheduled task cards, converting ramp AOGs to planned checks.

  • 02

    Dispatch reliability

    Baseline today

    Share of departures within fifteen minutes of schedule by base and type.

    How it moves

    MEL and deferral risk visibility stops open items from stretching past their operational interval.

  • 03

    MEL open time (median)

    Baseline today

    Time from MEL open to close, by category and base.

    How it moves

    The system watches each open MEL against its interval and the next check opportunity, surfacing those at risk.

  • 04

    Mean time between removals

    Baseline today

    Per-component removal history across the fleet.

    How it moves

    Earlier flagging drives earlier intervention; replacement cycles better match the component actual service life.

  • 05

    Maintenance cost per flight hour

    Baseline today

    Direct maintenance cost per flight hour, by type and base.

    How it moves

    Fewer unscheduled events, more accurate parts forecasting, and tighter MEL cycles compound into lower cost per hour.

Human in the loop

Oversight, safety, and the regulatory posture

Where the humans stay in control.

An airworthy fleet answers to the FAA, EASA, your Chief Inspector, and a safety culture that pre-dates any model. The system is designed around that posture.

  • 01

    Airworthiness sign-off

    No airworthiness decision is final without a licensed engineer. The system drafts tasks, cites regulations, and queues reviews; it never signs off.

  • 02

    Regulatory posture

    Compatible with Part 121 and Part 135 operations under FAA, with EASA equivalents configured per operator. ASA-100 parts governance is enforced at the parts layer.

  • 03

    Attribution and audit

    Every flag, every citation, every forecast logs the model version, the inputs, and the engineer or planner who acted. Audits can reconstruct any decision.

  • 04

    Low-confidence refusal

    When prediction or retrieval confidence is below threshold, the system defers or routes to engineering review rather than guessing.

  • 05

    ITAR and EAR handling

    For defense-adjacent engagements, environments are segregated to cleared personnel, data flows are audited, and model inference runs with no cross-tenant retention.

  • 06

    Data boundary

    Operational and sensor data remain in your tenant or a dedicated environment we operate for you under contract. No training on your data without a separate written agreement.

Proof

Work we have shipped, and the shape of what we build.

Real engagements where we can speak to them, and representative use cases where we cannot.

  • Use case

    Per-component predictive maintenance

    A proposed design: per-component drift models trained on your fleet history, feeding draft task cards into your maintenance platform with the trend, the suggested action, and the cited regulation.

  • Use case

    AD and SB applicability retrieval

    A proposed design: a retrieval system over FAA and EASA ADs, OEM SBs, and your fleet configuration, returning the applicable paragraph and the matched aircraft serial for engineering review.

  • Use case

    Rolling parts forecast

    A proposed design: a per-SKU, per-base forecast that updates with the flight schedule, so the pool reflects next month usage rather than last quarter spreadsheet.

How the build runs

Scoped tightly, shipped in phases.

Fixed price per phase, approved before the phase starts. You own the code, the models, the data, and the deployment.

  1. 01

    Discovery

    Two weeks. We shadow a reliability meeting, map your maintenance platform and sensor flows, and agree on the metrics we will move and how we will baseline them.

  2. 02

    Prototype on real data

    Six to eight weeks. One aircraft type, one component family, one proof of mechanism. Shadow-run against your reliability team; we measure against the baseline.

  3. 03

    Production rollout

    Twelve to sixteen weeks per fleet. Maintenance-platform integrations, SSO, regulatory configuration, audit trails, evaluation harness, and the engineering workflow your Chief Inspector signed off on.

  4. 04

    Handover

    You get the full source, the runbooks, the evaluation suite, and a two-week walkthrough with your engineering, planning, and compliance teams.

  5. 05

    Optional ongoing support

    A fixed-term support agreement for model-drift monitoring, regulatory feed changes, and OEM SB coverage updates. Never a retainer dependency.

Common questions

Answers before the first call.

01Which maintenance platforms do you integrate with?
We build against the supported interfaces of AMOS, TRAX, and the common MRO platforms. We write back only through surfaces the platform approves and never silently update airworthiness state.
02Does this make airworthiness decisions?
No. The system drafts tasks, cites regulations, and queues reviews. Every airworthiness decision is signed by a licensed engineer, and every automated action logs its inputs for audit.
03How do you handle ITAR and EAR for defense-adjacent work?
Environments are segregated to cleared personnel, data flows are audited, and model inference runs with no cross-tenant retention. Where required, deployment is on-premise or in a sovereign cloud region.
04What sensor and flight-data sources do you work with?
ACARS, QAR, FOQA, and vendor telemetry across common OEM platforms (compatible with GE Digital, Boeing AnalytX, Honeywell Forge). We work with what you have; we do not require a clean sensor stack to begin.
05How do you handle false positives?
Confidence thresholds are configured with your reliability leaders; low-confidence predictions are deferred rather than drafted; precision and false-positive rate are measured and reported.
See the other details on the FAQ page

Next step

A thirty-minute conversation. Bring one component family that drains your schedule today, and we will walk through what the first phase would look like, where the measurements come from, and what has to be true for your Chief Inspector to approve it.

Discuss your fleet reliability

Helpful to have on the call

Helpful to have on the call: your maintenance platform, one aircraft type with a reliability or MEL pain point, and the person who owns the metric you would like to move.

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