Operational intelligence for electric aviation
AeroMind is the physics-grounded intelligence layer for advanced air mobility. Plan networks that can pay, and dispatch airframes you can trust — from the first flight, for operators, lessors, and the insurers who underwrite them.
Why AeroMind
Route planning, insurance, financing, and dispatch all rest on one assumption: accumulated operating evidence. Electric aviation has none yet. Corridors are unplannable without route history. Individual aircraft are opaque without failure data. Every decision that keeps a fleet flying — underwrite, finance, dispatch, site infrastructure — structurally breaks.
AeroMind closes that gap with physics. Where data-driven methods have no signal to work with, a physics-grounded model of the aircraft and its environment produces calibrated, decision-grade intelligence from day one — and sharpens continuously as real operating data arrives.
The platform
A single physics-grounded core serves both the network-level questions — where can this aircraft profitably fly — and the per-aircraft questions — what is the condition of this specific tail, right now. Every neural-network output is accompanied by a certifiable provenance proof — the audit trail aviation regulation expects for AI-supported decisions.
Network layer
Physics-feasible route economics for the corridors that don't exist yet. Evaluate networks, routes, and infrastructure before a single revenue flight has been flown.
Per-aircraft layer
Per-aircraft state-of-health across the full electric powertrain. Calibrated condition and risk intelligence for each individual tail, from its first flight onward.
Regulatory readiness
Aviation authorities do not accept unexplained model outputs. AeroMind generates a structured provenance record for each decision produced by the neural network — inputs, model version, physics constraints, uncertainty, and the reasoning path — so operators, lessors, insurers, and regulators can reconstruct why a corridor score or dispatch recommendation was made. Built for the assurance bar of EASA, FAA, and the broader AI-in-aviation conversation — not as an afterthought.
Corridor Intelligence — multi-market network screening with physics-feasible route economics, risk bands, and ranked corridors. Live product; deeper methodology under NDA.
Operational Intelligence — per-aircraft health, battery SoH, dispatch go/no-go, and fleet alerts from first flight — with certifiable provenance on model decisions.
Technology
Conventional aviation intelligence calibrates on decades of accumulated failure data. AeroMind inverts the approach: start from the physics of the aircraft — the electrochemistry, the thermal behaviour, the aerodynamics — treat operating data as calibration, not prerequisite, and attach a certifiable provenance proof to every neural-network decision so the output remains auditable under aviation regulation.
Multi-domain physics models of the electric powertrain and its operating environment, calibrated against aerospace-grade reference behaviour and built for the specific failure modes of electric aviation.
Every flight tightens the model. Telemetry and operational data continuously refine per-aircraft predictions — with quantified uncertainty at every step, so downstream decisions know exactly how much to trust each number.
Decision-grade outputs, shaped for the stakeholder: corridor economics for planners, state-of-health for operators, calibrated risk evidence for insurers and lessors. One core, many decisions.
For each neural-network decision, the platform emits a certifiable provenance proof — model identity, inputs, constraints, intermediate evidence, and confidence — suitable for operational audit, underwriting files, and regulatory review. No opaque recommendation without a trail.
Detailed technical architecture, provenance schema, and methodology are shared under NDA.
Solutions
Primary: operators · lessors · insurers · Also: OEMs, city planners, consultants
Primary
Identify the corridors your fleet can profitably serve before committing capital. Make go/no-go dispatch decisions backed by per-aircraft prediction — with certifiable provenance proofs for every neural-network recommendation auditors can follow.
Primary
Underwrite multi-million-dollar aircraft over decade-long leases with independent visibility into operational condition — and a provenance trail on each condition call, not a black-box residual risk story.
Primary
Price hull and liability on aircraft with no actuarial precedent, with calibrated confidence intervals and certifiable provenance proofs from flight one — evidence files that stand up to regulatory and claims scrutiny.
Also serves
Close fleet orders with operational intelligence the buyer’s lessors and underwriters can independently trust.
Evaluate which corridors justify vertiport investment based on physics-feasible demand for the AAM era.
Strategy and advisory teams building business cases for advanced air mobility investment use Corridor Intelligence to stress-test which routes can actually pay — under transparent aircraft, energy, and utilisation assumptions — so client recommendations rest on physics-feasible economics, not fleet averages that do not yet exist.
The platform today
01
Demonstrable corridor-economics product with multi-market coverage, running on the public web. Reviewable under NDA.
02
The per-aircraft pillar: a production codebase in active development, with a coordinated module architecture across the powertrain.
03
Structured provenance proofs for neural-network outputs — model version, inputs, physics constraints, uncertainty, and decision path — designed for operational audit and aviation regulatory scrutiny.
04
Multiple physics domains — battery, motors, power electronics — calibrated against aerospace-grade reference behaviour for electric aviation failure modes.
05
Architecture shaped around certification, data governance, and AI assurance realities in Europe and beyond — not generic analytics retrofitted for aviation.
Company
AeroMind builds operational intelligence for the transition to electric and advanced air mobility — the systems that route planning, insurance, financing, and dispatch will depend on when historical fleet evidence does not yet exist.
Headquartered in Frankfurt, Germany, with active European regulatory engagement and a platform designed for certification, data governance, and AI-decision provenance — the assurance bar for operating aircraft in Europe and beyond.
Contact
AeroMind works with operators, lessors, and insurers first — and with OEMs, city planners, and consultants building AAM investment cases across the advanced air mobility ecosystem. A discovery call is the fastest way to see whether the platform fits your decisions — no deck walk-through, no pitch. Just a real conversation.
Discovery call · 30 minutes · Video
A short conversation to understand your context — what you’re working on, what you’re solving for, where AeroMind might fit.
Book a time30 min · no deck · optional NDA after if useful.
Prefer email first? We’ll respond from contact@aeromind-ai.com.