Founding Partners Program 2026 · Limited spots for operators, airlines and training centers.
ApplyWe are building aviation's predictive intelligence layer. It analyzes weather, fuel, route, terrain and nearby airports, simulates what could happen next and shows the crew their best options in seconds. The final decision always belongs to the pilot.
Prototype in developmentPartner program open
Best options now
Best options now
Best options now
Best options now
Conceptual visualization · illustrative scenario, not flight guidance
Designed around the data your operation already uses
The problem
When something goes wrong, the crew has to integrate weather, NOTAMs, performance, terrain and fuel while still flying the airplane. The data exists, but it is scattered, and the time to bring it together runs out.
70–80%
of civil and military aviation accidents involve human error.
Human factors are not just “pilot error”: they include workload, fragmented information and time pressure.
FAA Office of Aerospace Medicine · DOT/FAA/AM-00/7 (Shappell & Wiegmann, 2000)Weather, NOTAMs, performance, terrain and fuel live in different sources.
An abnormal event shrinks the time available to integrate information and compare options.
Checklists and the QRH are essential, but they don't synthesize the geospatial context of the moment.
Wind, runway, terrain, obstacles and margin can change the right decision.
More data doesn't guarantee a better decision. Crews need less noise, not more screens.
The idea
Aviantis is designed to integrate the full context of the flight and reduce it to what matters right now.
How it works
Aviantis combines physics-based and geospatial models with AI to detect a relevant condition, simulate possible futures and rank the alternatives with their reasons.
Planned sources
Conceptual visualizationIdentifies the condition that matters: a failure, low fuel, adverse weather or a restriction.
Generates possible futures from the aircraft's actual state, not from a static plan.
Compares trajectories, constraints, margins and uncertainty for every alternative.
Ranks the options, explains why and shows what would change the recommendation.
Reproducible physics where safety demands it. AI where it adds verifiable value.
Before and during the flight
A focused analysis of what's unusual before departure, and an adaptive analysis when something changes in flight.
Focused preflight
Low fuel, a reported failure, a restriction or adverse weather: it analyzes only what is relevant.
3 conditions to review
Adaptive in-flight analysis
When a new failure appears or the weather shifts, it recomputes from the current state and compares scenarios in seconds.
Never an endless list.
Reach, margin, wind, runway, terrain and missing data.
Separates verified, estimated and missing data.
Compare decisions and learn from every scenario.
Illustrative scenario
Normally the pilot reviews procedures, searches for airports, checks weather and computes distances while still flying. This is how that analysis could look with Aviantis, in seconds.
Illustrative scenario and values based on a case study. Not flight guidance.
Total loss of power at 8,500 ft. Wind from 270° at 12 kt.
The glide envelope bends with the wind: the reach is not a circle.
Three airports and runways fall within theoretical reach.
A, 18 NM away, crosses terrain the glide cannot clear with margin. C, 33 NM away, has uncertain weather.
B, 26 NM away: suitable runway, lower terrain and an estimated margin of +3 min. If the wind veers, the ranking can change.
The nearest wasn't the best. The final decision always belongs to the pilot.
Who it's for
We start in simulation and training, alongside operators who want to shape the product from day one.
How we start together
Scenarios from your most frequent routes, in the simulator first.
How we start together
A simulator pilot program alongside your training department.
How we start together
Scenarios built into your simulator sessions.
Safety by design
In aviation, safety and evidence are part of the product from day one.
Decision support, never control of the aircraft.
Shows alternatives and margins, not false certainty.
Every recommendation links back to its data, assumptions and model version.
When data is missing or confidence is low, it says so instead of improvising.
Deterministic models where safety demands reproducibility. Generative AI never replaces official procedures.
We test first in simulators and controlled environments, with pilots and instructors.
Aviantis is not a certified system yet. Today its use is limited to simulation and training.
Founding Partners Program
We are looking for a small group of operators, airlines and training centers to validate the product in simulation and define its path to operations together.
Apply to the programWe learn about your fleet, your routes and the scenarios that worry you most.
We design critical scenarios specific to your operation.
60 to 90 days with your pilots or instructors, measuring clarity, decision time and calibrated trust.
Together we prioritize integrations, aircraft and scenarios.
A sequence of dependencies, not a promised calendar.
Company
At 17, Alan crashed his first airplane. Luckily, it was in a simulator.
It took only a few seconds for one bad decision to lead to another. That's when he understood that when something goes wrong, the pilot has to decide with too much information and too little time.
So we asked ourselves: what if the pilot had a second mind helping them think?
A simulator has a reset button. A real flight doesn't.
That's why we're building Aviantis.
Close to the aviation domain, with in-house software and AI capability and a quantitative background.
Alan Greco Hernández López
CEO & Co-founder
Aeronautical training at Aeria. Aviation, product, scenarios and partnerships.
Braulio Noé Hernández López
Co-founder · AI & Software Systems
AI, data, quantitative modeling and a financial perspective.
Jorge Lino Isaías Ponce Murguía
Co-founder · AI & Software Development
Software architecture, AI and product engineering.
FAQ
No. It is a decision-support system: it analyzes, simulates and explains alternatives. It does not control the aircraft.
No. The final decision always belongs to the pilot. Aviantis gives them a second mind that analyzes while they focus on flying.
Not yet. Today we work in simulation and training, which is where validation begins. Certification is part of the roadmap, with no promised dates.
It is designed to combine aircraft state and performance, weather (METAR/TAF), NOTAMs, terrain, airports and runways, and fuel. Every data point is recorded with its source and age.
The first demonstrator focuses on a training aircraft and a total engine-loss scenario. Together with our founding partners we decide which aircraft and scenarios come next.
A 60 to 90 day program in the simulator with your pilots or instructors, with tailored scenarios and metrics for clarity, decision time and trust.
It tells you. When data is missing or confidence is low, Aviantis states the limitation instead of improvising a recommendation.
We work on a B2B model: a pilot program and then a license sized to your operation. We quote each case.
Request a demo
Tell us about your operation. We'll walk you through the conceptual demonstrator and what a pilot program with your team would look like.
Prefer email?contacto@navryx.co
Quick answers
Pre-written answers. Not a live AI assistant.
No. It is a decision-support system: it analyzes, simulates and explains alternatives. It does not control the aircraft.
No. The final decision always belongs to the pilot. Aviantis gives them a second mind that analyzes while they focus on flying.
Not yet. Today we work in simulation and training, which is where validation begins. Certification is part of the roadmap, with no promised dates.
We work on a B2B model: a pilot program and then a license sized to your operation. We quote each case.