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A laptop on navy showing the VVResponse live exercise screen: the exercise VFR Lost Above Cloud, a step timer and a weather radar with two aircraft, REX21 and JETSTAR126

VVResponse: from a proof of concept to an air traffic control training simulator

Rocket Lab rebuilt VVResponse, Visual Vectoring's web-based training simulator for air traffic control communications, from a proof of concept. Trainees speak over a virtual radio, and an LLM plays the pilots and other parties, then evaluates their performance.

  • Aviation training
  • Product Discovery
  • UX/UI Design
Client
Visual Vectoring
Platform
Industry
Aviation training
Services
  • Product Discovery
  • UX/UI Design
  • Technical Design
  • Web App Development (Next.js, TypeScript, AWS)
  • LLM Integration

About the Client

Visual Vectoring is an Australian company that provides simulation training for air traffic control, used by air navigation service providers and training institutions.

VVResponse, by Visual Vectoring, is a web-based training simulator for air traffic control communications. Trainees work through emergency and abnormal scenarios by speaking over a virtual radio. An LLM plays the pilots and other parties, then evaluates the trainee's performance. It is for air traffic controllers, trainees and trainers, to refresh skills or train new controllers.

The Challenge

Visual Vectoring had an early proof of concept that used an LLM and had no database. It came to Rocket Lab to review it and turn it into a real product. Rocket Lab recommended a full rebuild.

The brief was a web app for a trial rollout, with:

  • User accounts.
  • An exercise library, with shared exercises and exercises private to each organisation.
  • Voice interaction over simulated radio frequencies.
  • Step-based scenarios that advance when the trainee meets the objectives in time.
  • Practice and exam modes.
  • A performance report written by the LLM.
The live exercise screen in VVResponse, practice mode: the exercise VFR Lost Above Cloud at its Initial contact step with a step timer, a weather radar showing two aircraft, REX21 and JETSTAR126, and on the right the send mode, a message box, two radio frequencies (121.500 and 130.900) and the Supervisor, Tower and Ground intercom channels

The Solution

Rocket Lab ran discovery, then rebuilt VVResponse in full.

  • Discovery

    In June and July 2025, over two sprints, Rocket Lab ran workshops, wrote the user stories, designed the web app in Figma and produced the technical design.

    The technical design covered the AWS infrastructure, multi-tenancy, the scenario format, the voice and radio system, and an LLM abstraction layer, so the model can be swapped later.

  • The build

    From September to December 2025, Rocket Lab rebuilt VVResponse in Next.js and TypeScript on AWS:

    • Exercise selection.
    • The live exercise screen.
    • Radio communication driven by the LLM, with speech-to-text and text-to-speech.
    • Step evaluation and final reports.
    • An admin mode for testing prompts.
  • The VVResponse exercise selection page: Please select your simulation exercise, a category filter, and two Approach exercises, VFR Lost Above Cloud with an intercom or a radio initial event, each described and with a Select button
  • Exercises the client writes

    Rocket Lab also wrote an Exercise Guide, so Visual Vectoring can author and upload its own exercises. Training organisations can run shared exercises alongside their own private ones.

  • The Step 1 Initial contact window over the VVResponse live exercise screen, listing the step's assumptions, such as the pilot being VFR above a continuous cloud layer and two-way communication on 121.500 being established, with a Start Step 1 button
  • Improvements

    In August 2026, a further sprint made the LLM prompts configurable and visible to admins.

The Outcome

Rocket Lab took VVResponse from a proof of concept to a rebuilt web app: user accounts, a shared and private exercise library, voice over simulated radio, step-based scenarios, practice and exam modes, and an LLM-written performance report, with exercises Visual Vectoring authors itself.

Next step

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Founder and Fractional CPTO

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