Product hub

One video platform, twelve AI workflows.

VidScanner turns uploaded video into searchable moments and structured outputs: meeting briefs, bug reports, property listings, flashcards, datasets, movement counts, rubric evaluations, and more.

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Meeting intelligence

Meetings

Turn a recorded meeting into a structured, searchable summary.

Executive summary (1 paragraph)

Key Points

Action Items (with assignees + due dates when mentioned)

Bug report automation

Bug Reports

Convert a screen recording into a complete written bug report.

Title (auto-generated)

Severity (critical / high / medium / low)

Numbered reproduction steps

Real estate listing generator

Listings

Generate an MLS-ready property listing from a walkthrough.

Property facts (price, beds, baths, sqft, lot, year built)

MLS-ready marketing description (1–3 paragraphs)

Per-room cards with feature lists + timestamped screenshots

UX research synthesis

UX Sessions

Auto-analyse a usability test recording.

Usability score (0–100)

Dropoffs — moments where the user got stuck or quit

Confusion — places they hesitated or asked questions

Construction reporting

Construction

Generate a daily site report from a walkthrough.

Progress items (with completion %)

Issues (with severity and recommended action)

Materials on site (with quantities when stated)

Security incident reporting

Security

Turn a CCTV clip into a structured incident report.

Title (auto-generated)

Severity (critical / high / medium / low)

Location (extracted when visible)

Game film analysis

Sports

Auto-generate a game report from game tape.

Scoreline (e.g. Warriors 110 — Celtics 108)

Sport (auto-detected)

Home / away teams

Lecture to study materials

StudyHall

Turn a lecture recording into flashcards, a quiz, and notes.

Subject (auto-detected)

Lecture summary

Key concepts (1–2 paragraphs of notes)

Call to draft contract

Contracts

Turn a recorded conversation into a structured draft contract.

Parties (with role: client / contractor / agency / vendor)

Scope (1–2 paragraphs)

Deliverables (numbered list)

Video to ML dataset

AI Training Datasets

Generate a frame-level ML training dataset from a video.

Per-frame labels (class names + bounding boxes + confidence)

Scene attributes (weather, lighting, density, etc.)

Event tags (e.g. 'person_crossing', 'vehicle_approaching')

Traffic and movement dataset

Traffic & Movement

Build an aggregate movement dataset from fixed-camera footage.

Per-frame object counts (e.g. {'car': 5, 'pedestrian': 2})

Per-zone aggregated counts (e.g. 'north sidewalk': 47 pedestrians)

Entry / exit counts (where zone boundaries are detectable)

Rubric video evaluation

Evaluations

Score videos against configurable rubrics with reviewable evidence.

Per-rubric-item status and confidence

Timestamped evidence text

Screenshot from the evidence moment