Free emotion detector open source live with webhook capability and metrics and anayltics customizable
VibeCheck is a free, lightweight, completely offline emotion detection engine that runs fully in the browser,
converting live webcam pixels into real‑time emotional insights without ever touching the cloud. It follows the same
edge‑AI pattern used by modern privacy‑focused emotion tools: all inference happens locally, no frames are stored,
and only optional, anonymized signals are sent out via user‑controlled webhooks.
Core value proposition
VibeCheck turns any modern browser into a real‑time emotion sensor, powered by on‑device AI and your CPU/GPU. This
gives teams and individuals the benefits of emotion recognition—safety, accessibility, and customer insights—without
introducing a backend, an SDK dependency, or a data‑collection risk.
Under the hood it uses a visual model that infers emotional states frame‑by‑frame, exposing clean, structured
outputs (labels and confidence scores) that front‑end code can react to instantly. Because everything runs offline,
it works in low‑connectivity and high‑sensitivity environments where cloud‑based emotion APIs would be a
non‑starter.
Key features
100% private, offline by design: Webcam data never leaves the device; frames are processed in‑memory and not
uploaded or stored, mirroring the 'server‑free emotion AI' architecture seen in other privacy‑centric engines.
Runs in any modern browser: Built on standard web technologies (WebRTC + WebGL/WebGPU), so it works across operating
systems without installs, drivers, or native apps.
Lightweight and efficient: Optimized to run on consumer laptops and tablets, leveraging GPU acceleration when
available for smooth, real‑time emotion inference.
Configurable thresholds and alerts: Users or integrators can define which emotional states matter and when alerts
should trigger, aligning the engine with their domain logic.
Webhook‑ready: Emotion events can be streamed as JSON to any HTTPS endpoint directly from the browser, letting you
plug VibeCheck into dashboards, automation tools, or custom backends without ever shipping raw video.
Real‑world use cases
Safety & operations
VibeCheck can act as a continuous, privacy‑preserving safety layer for heavy machinery operators, truck drivers, and
other high‑stakes roles where fatigue or inattention is a critical risk. By monitoring facial cues linked to
drowsiness or low engagement, it can trigger escalating local alerts (sound, visual overlays, or device
notifications) when risk thresholds are crossed.
Because inference is on‑device and offline, it is suitable for constrained or regulated environments such as
industrial sites, logistics fleets, and remote locations, similar to other edge‑deployed FER systems that avoid
centralizing biometric streams. Optional webhooks can send anonymized 'fatigue events' or risk scores to an
operations API for fleet‑wide analytics without transmitting any identifiable video.
Customer insights
For retail counters, kiosks, and remote video support, VibeCheck offers anonymous emotional telemetry on how
customers react during key interaction moments. Instead of recording sessions, it exposes only aggregate sentiment
states (e.g., rising frustration, satisfaction, confusion) that can be tied to steps in a flow, agent actions, or UI
changes.
Front‑end webhooks allow organisations to push these emotion metrics into CRMs, contact‑centre platforms, or BI
tools alongside operational data, similar to privacy‑oriented browser emotion systems that forward only anonymised
metrics. This yields powerful CX analytics—drop‑off points, emotional bottlenecks, script effectiveness—without
building a surveillance stack.
Accessibility and Blind Mode
VibeCheck’s Blind Mode turns visual emotional cues into accessible output—spoken feedback, tones, or haptic
signals—so visually impaired users can better perceive how people around them might be feeling. Running entirely on
the user’s own device aligns with emerging best practices for privacy‑preserving assistive technologies, where
sensitive perception stays local.
The browser‑based design makes it usable on commodity hardware with screen readers, and developers can map specific
emotions to custom sounds, vibration patterns, or braille displays via standard web APIs and local integrations.
Interoperability via webhooks
VibeCheck treats emotions as a real‑time data stream that you control, not a service you rent. Every detection cycle
can emit structured events—emotion label, confidence, timestamp, optional session context—to user‑defined webhook
URLs configured in the Settings panel.
This enables patterns like:
Pushing emotion time‑series into your own analytics pipeline.
Triggering downstream automation (Slack alerts, incident systems, workflow engines).
Enriching internal dashboards or AI agents with 'live emotional state' signals, similar to how other JS‑based
emotion AI engines augment digital experiences with on‑device analysis.
Suggested SEO keywords for the webmaster
offline emotion detection engine
browser‑based emotion recognition
100% private emotion AI (no cloud)
on‑device facial emotion analysis
edge AI for fatigue and drowsiness detection
emotion analytics for customer service without recording video
accessibility emotion reader for visually impaired users
Blind Mode emotion feedback (audio and haptics)
real‑time emotion data webhooks
open, lightweight emotion AI for modern browsers
Vibecheck.cam is a free, browser-based emotion detection tool that runs fully on-device to infer facial emotions in
real time while emphasizing privacy and offline use.
Core purpose
The site provides a live 'emotion AI' dashboard that reads your webcam feed locally and estimates states like smile,
anger, sadness, surprise, drowsiness, fatigue, and similar signals, exposing them as intensities or percentages on
screen. It is presented as an open-source, privacy-first utility aimed at practical safety, accessibility, and
customer-experience use cases rather than a gimmicky face filter app.
How it works
VibeCheck uses visual language models and lightweight emotion-recognition models that run in the browser via WebRTC
and GPU acceleration (WebGPU/WebGL/MediaPipe), with all video processing kept in memory on the device. No raw
images, video, or biometric data are uploaded or stored by default; only optional numeric emotion scores can be sent
out if the user configures webhooks.
Key features
Live multi-emotion classification (happiness, sadness, anger, fear, surprise, disgust, neutral plus
drowsiness/fatigue-type patterns) suitable for commodity laptops and mobile devices.
Configurable thresholds and alerts so specific states (for example drowsy, frustrated) can trigger visual, audio, or
haptic feedback.
Front-end webhooks that POST JSON emotion events to arbitrary HTTPS endpoints, enabling integrations with analytics
stacks, automations, or custom apps without handling video.
Intended use cases
The site explicitly frames use around:
Drowsiness and attention monitoring for drivers or operators, including offline scenarios.
Assistive tech for blind or visually impaired users, narrating others’ emotions via audio or haptics while keeping
everything local.
Customer support and CX analytics, running on agent or kiosk devices to infer emotional trajectories without
recording faces centrally.
Overall vibe
The positioning is 'edge-native emotion AI': open, hackable, and integration-friendly, but with strong privacy
guarantees and no vendor lock-in. It reads less like a consumer toy and more like a small, opinionated platform for
on-device emotion sensing and webhook-driven workflows, especially in regulated, accessibility, or safety-critical
contexts.
what other best use cases u think will make good commercila value or solve high impact society problems
The most interesting commercial and societal opportunities sit where 'read the vibe locally, act on scores, never
ship video' is a hard requirement.
Safety and risk monitoring
In-vehicle 'fatigue and frustration' copilot that runs completely on the head unit or phone, nudging drivers when
drowsy or agitated and optionally logging only scores for fleet safety analytics.
Industrial or construction helmets/tablets that watch for distress, confusion, or microsleeps in operators handling
dangerous equipment, with local alarms and opt-in escalation to supervisors.
Assistive and therapeutic tech
AR glasses or phone-based assistive app that narrates others’ likely emotions in real time for autistic or visually
impaired users, processed entirely at the edge to avoid cloud video.
'Mood mirrors' for mental-health journaling that correlate facial affect with self-reported mood over weeks,
generating insights that clinicians can use without ever seeing raw footage.
Education and skills coaching
On-device classroom agent that senses global engagement, confusion, or boredom from a group, feeding only aggregated
scores to the teacher dashboard for adaptive pacing.
Presentation and sales coaching tools that sit on the learner’s laptop, measuring their own expressiveness, anxiety,
and energy across practice sessions to give targeted feedback and progress tracking.
Privacy-preserving CX and research
Retail kiosks or digital signage that adapt content to the current viewer’s emotional state (e.g., frustrated vs
curious) but only export anonymized emotion time-series for analytics.
High-consent UX research rigs in labs or usability tests that log emotion curves alongside clickstreams, enabling
premium insight services without video retention risks.
High-stakes screening and triage (with guardrails)
Emergency-room or crisis-hotline side panels that estimate distress and agitation from patient faces to help staff
prioritize de-escalation, with strict governance and human-in-the-loop policies.
Public-service kiosks (immigration, social services) that watch only for escalating frustration or distress to
trigger offers of human assistance rather than automated 'profiling'.
Where the money likely is
Regulated industries (health, mobility, industrial, government) that need emotion signals but cannot ship biometrics
off-device: sell SDK + appliances + compliance story.
Creator, coaching, and CX tooling (presenter coaches, call-centre sidekicks, signage/kiosk brains) that license
emotion-inference as an on-device component, integrating via simple webhooks.
Vibecheck.cam is a free, open‑source, browser‑based emotion detection tool that runs entirely on the user’s device,
using AI and VLMs to read facial expressions without sending any data to a server. It is designed for high privacy,
practical real‑world safety use cases, and simple integration into existing workflows via front‑end webhooks.
What makes vibecheck.cam different
Vibecheck.cam processes webcam video locally in the browser, so faces and emotions never leave the user’s machine,
reducing exposure to surveillance, leaks, or misuse. Unlike cloud‑based emotion AI, it requires no account, no
backend, and no data retention, aligning with privacy‑by‑design principles and modern device‑edge emotion AI
patterns.
The tool relies on a visual language model (VLM) and lightweight emotion recognition models optimized for real‑time
performance on commodity laptops and mobile devices. Developers can inspect, fork, and extend the code because it is
open source, avoiding vendor lock‑in while enabling domain‑specific tuning and custom UI flows.
Key features
100% on‑device processing: All video frames are analyzed in the browser using WebRTC and WebGPU/WebGL pipelines,
with no upload to remote servers. This makes it suitable for regulated sectors, accessibility tools, and personal
monitoring where cloud recording would be unacceptable.
Live emotion classification: The model continuously detects core facial emotions such as happiness, sadness, anger,
fear, surprise, disgust, and neutral, and can expose them as probabilities or labels for downstream logic.
Customisable alerts and thresholds: Users can configure what emotional states matter (for example, drowsy/low
attention or frustrated ) and define when visual, audio, or haptic alerts should fire.
No recording, no storage by default: Frames are processed in memory; nothing is stored to disk unless the user
explicitly toggles logging for debugging or analytics under their own control.
Front‑end webhooks: When specific emotion patterns are detected, the browser can POST JSON payloads directly to a
user‑defined webhook URL, enabling serverless integrations and real‑time analytics without handling raw video.
Use case 1: Drowsiness and attention while driving
A key application is detecting drowsiness or loss of attention for drivers using an in‑car device or laptop mounted
safely, with the browser open to vibecheck.cam. The system can watch for eye closure, low arousal, or repeated
bored/tired signals and trigger escalating alerts such as beeps, voice prompts, UI flashes, or even integration with
car systems where available.
Because everything runs locally, it can function in offline environments (highways, rural areas) and does not stream
or store video, preserving driver privacy while still providing a safety net. Webhooks allow fleet operators or
personal automation platforms (like Home Assistant or custom APIs) to receive anonymized drowsiness events without
ever accessing the raw face data.
Use case 2: Assistive tech for blind and visually impaired users
For blind or visually impaired users, vibecheck.cam can act as a social emotion narrator , turning facial
expressions of nearby people into spoken or haptic feedback. The browser interface can be paired with screen readers
and audio output so that, when the camera sees a face, it announces the likely emotion (for example, smiling ,
confused , angry ) in real time.
Because nothing leaves the device, sensitive social situations (family interactions, healthcare settings,
classrooms) remain private while still granting the user access to non‑verbal cues they would otherwise miss.
Developers can customise vocabularies ( relaxed vs neutral ), sensitivity, and languages, or connect the webhook
output to more sophisticated assistive apps via their own APIs.
Use case 3: Customer support and CX emotion analytics
In customer support scenarios—retail kiosks, service counters, or remote video support—vibecheck.cam can run on an
agent’s or kiosk’s device to gauge customer emotion during interactions without recording or transmitting video.
Real‑time emotion trends (for example, rising frustration or confusion at step 3 ) can guide agents to slow down,
offer clarification, or escalate to a supervisor.
Through browser‑side webhooks, anonymized emotion time‑series can be pushed to contact center dashboards, BI tools,
or CRM systems, enabling analytics such as average emotional trajectory by flow, NPS correlation, or script
variants. Organisations get rich qualitative signals without collecting biometric data centrally, which helps with
compliance and customer trust.
Webhooks and integration possibilities
The webhook mechanism is the bridge between private, on‑device perception and your broader digital ecosystem. Each
detected event (for example, anger > 0.8 for 5 seconds or drowsiness pattern detected ) can be turned into
structured JSON and sent directly from the browser to any HTTPS endpoint you control.
This enables patterns such as:
Logging aggregate emotion metrics to your own analytics stack (Mixpanel, Segment, custom API).
Triggering automations (Slack alerts to supervisors, home automation rules, or fleet alerts).
Training feedback loops, where you correlate emotion events with business KPIs, all without ever storing faces,
audio, or raw video.
Why vibecheck.cam matters now
Edge‑based emotion AI is becoming the preferred architecture for sensitive applications, because it combines
real‑time responsiveness with significantly lower privacy risk. Vibecheck.cam packages that pattern into a free,
open, and hackable browser app that anyone—from a solo developer to a large enterprise—can adopt, fork, or embed
without asking permission or handing data to a third party.
For SEO and positioning, strong keywords and phrases to align with this blog post include:
on‑device emotion detection
privacy‑first emotion AI
browser‑based emotion recognition
visual language model emotion detection
driver drowsiness detection offline
assistive emotion reader for blind users
customer support emotion analytics without recording video
webhook‑based emotion analytics
open‑source emotion AI in the browser
VibeCheck, Emotion Detection, Face Analyzer, AI Mood Tracker, Offline AI, Privacy Focused, Local Processing,
Browser Based Vision, Sean Lon, Facial Expression Recognition, Real-time Sentiment Analysis,
Blind Mode Accessibility, Haptic Feedback for Emotions, Surprise Detection, Sadness Detection,
Happiness Detection, Fear Detection, Anger Detection, Disgust Detection, Neutral Face,
Webhooks for Emotion Data, React AI App, MediaPipe Integration, TensorFlow.js,
No Cloud Data, Secure Emotion Sensing, Driver Fatigue Detection, Customer Service Training Tool,
Empathy Tech, Sentience Meter, Biofeedback
Free Privacy-First Live AI Emotion Detection
Sean Lon
Creator & Lead Developer
"I believe in a future where technology amplifies empathy, not replaces it. A noble pursuit to help others see what
is often unseen."
VibeCheck
A free, lightweight, and completely offline emotion detection engine.
Running entirely in your browser, VibeCheck transforms raw pixel data into meaningful emotional insights — without
ever sending a single frame to the cloud.
🔒 100% Private & Offline
- Zero data collection.
- Your camera feed is processed locally on your device’s CPU/GPU.
🌍 Universal Access
- Works on any modern browser.
- Optimized for low‑bandwidth environments.
Real‑World Applications
Safety & Operations
- Real‑time fatigue detection for heavy machinery operators, truck drivers, and high‑stakes operational roles.
Customer Insights
- Anonymous sentiment analysis for customer service interactions, ensuring quality without compromising identity.
Accessibility Tools
- Empowering visually impaired users with Blind Mode — audio and haptic feedback to perceive the emotions of those
around them.
Interoperability
- Stream real‑time emotional data to your own API endpoints via Webhooks (configurable in Settings) for custom
integration and logic.
📌 Sections
- USE CASES
- CONTACT
- PRIVACY
Privacy & Data Security
Local Processing Guarantee
VibeCheck runs 100% on your device. The video feed from your camera is processed frame-by-frame in your browser's
memory using GPU acceleration (MediaPipe).
No images or video frames are ever sent to any server.
No biometric data is stored permanently.
Emotion data (coordinates & scores) is transient and discarded immediately after rendering, unless you enable
Webhooks.
If Webhooks are enabled, only the numeric emotion scores you configure are transmitted to your specified endpoint.
Transparency Verification: Feel free to inspect your browser's network requests or turn off your internet connection
to verify that no data is being sent to our servers.
Offline Capability
After the initial page load, VibeCheck can function completely without an internet connection. This ensures no data
can physically leave your device even if it wanted to.