Air Traffic Control · Candidate Assessment

Know who belongs in terminal controlarea controloceanic controlthe tower before training starts.

Falcon is a web-based ATC simulation and assessment platform that gives Air Navigation Service Providers objective, data-rich reports on candidate aptitude — at a fraction of the cost of traditional screening.

~2.5hrs
End-to-end assessment per candidate
5+
Scored simulation runs per candidate
20+
Distinct performance metrics tracked
Web
No installs — runs in any modern browser

ATC training is expensive. Attrition is unpredictable.

Traditional ATC screening relies on aptitude tests and interview panels that struggle to predict real-world performance. Training can cost hundreds of thousands of dollars per candidate — and washout rates are high.

ANSPs need a better signal before committing to full training pipelines.

Study-level simulation, accessible in a browser.

Falcon delivers a realistic, browser-based radar simulation environment backed by our Separation Integrity Engine and voice recognition layer. Every session generates a detailed, objective candidate report.

Every candidate, quantified.

Simulator scores, skill grades, and AI-generated interview questions — one report per candidate, automatically.

Falcon — Candidate Assessment Dashboard
Candidate
#852
Simulator Score
68.4
Learning Score
82.4
Overall
75.4
Simulator Runs 5 sessions
Run Sep Loss Critical Significant Minor Score
1 0 0 0 0
100
2 2 1 2 1
47
3 2 1 3 2
21
4 0 1 2 3
74
5 0 0 1 1
93
Skills Grades
Track milesA
Transmission efficiencyA
Number of vectorsB
Proper phraseologyB
Readback monitoringA
Rate of speechA
Repeated commandsA
Proper prioritizationF
Strip updatesA
Most Common Errors
Radar separation 3/1000×4
Aircraft cleared to wrong waypoint×3
Incorrect turn direction×3
Late frequency change×2

Three steps from candidate to decision.

01

Candidates complete a short online course

Structured like a university module, the course walks candidates through ATC fundamentals with reading material and knowledge-check questions. Candidates who don't engage with the material will show it on the simulator.

02

Candidates complete simulation sessions

Using a browser and microphone, candidates work through a series of progressive radar scenarios — managing real flight strips, issuing voice commands, and handling live traffic.

03

Evaluators receive a structured report

A detailed per-candidate dashboard shows scores, skills grading, common error patterns, and AI-generated interview questions — giving hiring panels everything they need to make a confident decision.

Built by engineers obsessed with aviation safety.

Matthew Zhang
Co-founder

Leads Falcon's simulation environment. A mechatronics engineer currently interning on Tesla's crash analysis team, Matthew brings first-principles rigour to every aircraft dynamics and real-time systems problem.

Ian Tan
Co-founder

Ian trained as an ATC student at NAV CANADA, working toward Toronto terminal — responsible for all Pearson arrivals and departures up to FL230 within 26 miles. Falcon is built on what he learned there.

David Hood
Co-founder

Leads voice recognition and LLM inference. David built the pipeline that takes a controller's spoken words and produces scored, structured ATC instructions — connecting speech transcription to an LLM layer that understands what was meant, not just what was said.

University of Waterloo Waterloo Institute for Sustainable Aeronautics AC:Aerospace Accelerator

Ready to see Falcon in action?

We work directly with ANSPs to tailor the assessment pipeline to local airspace rules, traffic profiles, and phraseology standards.

Request a demo — desk@falconatc.com