Product Concept: CinemaTech AutoTrack

Date: 28.11.2025
Client: CinemaTech Systems
Partner: Promwad
Concept: "Autonomous Director for Premium Broadcasts"

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1. Executive Summary

CinemaTech Systems today sells the best cinema hardware, but live broadcasters and rental houses lack built-in autonomy. Insight: combining CinemaTech Systems brand with Promwad engineering stack can create the first market-certifiable AI tracking that reduces operator workload, cuts costs, and opens new ARR source. Solution — AutoTrack: edge-AI + robotics + CinemaTech Systems lenses + cloud analytics. Benefit — transition from one-time sales to subscription, margin growth, and CinemaTech Systems ecosystem protection.

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2. Context & Vision

2.1 The Problem (Why is this important?)

• Broadcasters and organizers depend on large operator teams, who get tired during long broadcasts and make mistakes.
• No premium camera vendor has a boxed AI solution with native cinema optics support and safety certification.
• Rental market has no differentiator: everyone offers the same cameras without automation and subscription services.
• CinemaTech Systems risks losing share in growing sports/virtual production segment if it doesn't add an intelligent layer.

2.2 The Vision (Where are we going?)

Imagine an arena where autonomous CinemaTech Systems cameras catch the player themselves, know when to hand off the shot to a neighboring camera, and automatically pull focus/aperture. Data goes to the cloud, director sees system status in the app, and CinemaTech Systems gets monthly ARR for subscription and analytics. AutoTrack — new standard for premium live content without quality compromises.

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3. Strategic Roadmap: The "Autonomous Studio" Evolution

AutoTrack is not just a product, it's the first step (Phase 1) in building a fully autonomous CinemaTech Systems studio. We're selling not a "robot", but an entry ticket to the ecosystem.

Phase 1: AutoTrack (The Body) — "Hands & Eyes"

• Concept: "Smart tripod". Autonomous head that sees and tracks.
• Technical Goal: Implement Single-Camera Autonomy. Camera must be able to keep person in frame (Framing), maintain focus (Focus Pulling), and follow them (Tracking) without operator involvement.
• Key Product: CinemaTech Systems AutoTrack Head (Motorized Pan/Tilt + AI Module).
• Business Goal: Enter Live Sports and Broadcast market as "operator assistant", reducing personnel workload.
• Status: Current focus (MVP).

Phase 2: EdgeFlow (The Nervous System) — "Connectivity"

• Concept: "Camera swarm". Unified network where cameras communicate with each other.
• Technical Goal: Implement Multi-Camera Orchestration. If Camera A loses object (it went behind a column), it tells Camera B: "It's coming to you, catch it!". Timecode, metadata, and focus synchronization with <10ms delay.
• Key Product: CinemaTech Systems EdgeFlow Server (local data aggregation server).
• Business Goal: Sell not individual units, but "system solutions" for stadiums and studios. Upsell networking equipment.

Phase 3: AIDirector (The Brain) — "Decision Making"

• Concept: "Virtual director". AI that edits the broadcast.
• Technical Goal: Implement Automated Editorial Decisions. System analyzes streams from all EdgeFlow cameras, selects best angle (where face is visible, where there's no defect) and switches broadcast itself (Video Switching).
• Key Product: CinemaTech Systems AIDirector (SaaS Cloud Platform).
• Business Goal: Transition to Recurring Revenue model (subscription to "AI director"). Full automation of routine broadcasts (corporate events, local sports).

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4. The Solution (Our Solution)

3.1 What is it?

Name: CinemaTech Systems AutoTrack
Metaphor: "Autopilot and nervous system for CinemaTech Systems live cameras"
Essence: Edge-AI and robotics system integrated with CinemaTech Systems cameras and lenses that autonomously tracks players/talent, manages pan/tilt/zoom/focus, coordinates multiple cameras, provides cloud analytics, and supports human-override.

3.2 Before vs. After

3.3 Key Features (MVP)

• Edge AI Tracking Core: YOLO/OC-SORT + LSTM on Jetson/Qualcomm, <100ms latency, >95% subject retention. Benefit: stable frame without manual adjustment.
• Lens Intelligence Layer: Native control of CinemaTech Systems lenses (focus/iris/ND) with depth distance estimation. Benefit: cinema quality maintained even in sharp scenes.
• Multi-Camera Orchestrator: EtherCAT/ROS2 coordination, predictive hand-off, anti-collisions and angle priorities. Benefit: director gets frame variety without micromanagement.
• Cloud Control & Analytics: AWS IoT, OTA, tracking intensity, coverage-scores, API for rental houses and leagues. Benefit: transparency, new data products, SaaS model.
• Human-in-the-Loop UI: Flutter/React control panel, instant override, autonomy levels, operator preference learning. Benefit: reduces staff resistance, eases implementation.

3.4 High-Level Architecture

graph LR
    subgraph Venue Edge
        VisionAI["Edge AI Module<br/>YOLO/OC-SORT/LSTM"]
        MotorCtrl["Motor & Lens Control<br/>ROS2 + EtherCAT + CinemaTech API"]
        Safety["Safety Layer<br/>FMEA, watchdogs, ISO 26262"]
        VisionAI --> MotorCtrl
        MotorCtrl --> Safety
    end
    subgraph Cloud
        DeviceTwin["CinemaTech AutoTrack Cloud<br/>Telemetry + OTA + Analytics"]
        DataAPI["Insights & API<br/>Coverage, players, SLA"]
    end
    Operator["Operator App<br/>(Web/Mobile)"]
    VisionAI --> DeviceTwin
    MotorCtrl --> DeviceTwin
    DeviceTwin --> DataAPI
    Operator --> DeviceTwin
    Operator --> MotorCtrl

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5. Implementation Path (How We'll Do It)

Phase 1: Pilot (Proof of Concept)

• Goal: Prove >95% tracking, <100ms latency and basic integration with CinemaTech Systems lenses on 2–3 beta clients.
• Scope: Edge prototype on Jetson/Qualcomm, basic multi-camera controller (2 cameras), human-override UI, pilot with selected broadcaster/rental house.
• Deliverables: PoC kit (hardware + firmware + UI), accuracy/latency report, two beta client cases, MVP roadmap.
• Timeline: 6 months (investment €250–350K).

Phase 2: Scale (MVP & Launch)

• Goal: Certified MVP for 10–15 paying clients, subscription model launch and safety audit preparation.
• Scope: Industrial edge unit (IP65/EMC), extended multi-cam orchestrator (up to 6 cameras), cloud analytics, ISO 26262/IEC 61508 gap analysis, rental bundle.
• Deliverables: MVP hardware, SaaS platform, reference deployments, certification readiness.
• Timeline: +12 months (investment €500–700K). Phase 3 (Scale) assumes mass deployment, OEM licensing, and data monetization.

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6. Business Case (Why This is Beneficial)

6.1 Value Proposition

6.2 ROI & Economics

• Investment (Pilot): €250–350K (6 months).
• Full Program (3 years): €1–1.5M (PoC + MVP + Scale).
• Payback (for CinemaTech Systems): 18–24 months (total cash flow +€30–60M by end of Y3, ROI 20–60x).
• Customer ROI (example): implementation at major arena pays back in 12–18 months through staff savings and new monetization formats.

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7. Mapping to Mini-Offer (Meeting Narrative)

Slide 1: Problem (Context)

• Premium broadcasts are still tied to manual labor and lose money on operator fatigue.
• No vendor combines CinemaTech Systems image quality and autonomous AI camera control.

Slide 2: Solution (Essence)

• Metaphor: "Autopilot for CinemaTech Systems cameras".
• Main Idea: Edge-AI + CinemaTech Systems lenses + cloud analytics = automated broadcasts with cinema quality and new subscription economy.

Slide 3: Proof (Why Us?)

• Promwad: Autonomous Service Robot (Qualcomm RB3) — real-time navigation <100ms.
• Promwad: 360° Truck Camera (ISO 26262 ASIL-B) — proven safety stack for video and motor control.

Slide 4: Next Step (Proposal)

• Proposal: Launch 6-month AutoTrack pilot on 2–3 arenas/studios.
• Investment: €250–350K (hardware + AI + integration).
• Result: >95% tracking accuracy, <100ms latency, MVP readiness and confirmed references.