Patent Pending AU2026903561
·
Melbourne, Australia
·
April 2026

Your emotions
decide before
you do.

EMPATHIQ is a patented emotion-aware agentic AI that continuously monitors physiological and behavioural signals, learns each person's unique emotional patterns, and intervenes — gently — before emotionally-driven decisions are executed.

Explore Collaboration → View Technology
75K+
Consumers in meta-analysis confirming emotion drives impulsive decisions
$20B
Projected emotion AI market by 2034 at 22% CAGR
20
Patent claims filed — DEH, RDRS, Pattern Mirror, on-device privacy
5
Novel integrated system layers — the combination not found in prior art
The Problem

We make our worst decisions when we feel the most.

"The same person, returned to emotional baseline, will frequently reach a different — and better — decision."

High arousal emotional states — stress, excitement, loneliness, anger — systematically impair the prefrontal cortical functions responsible for deliberative reasoning. No existing system links an individual's real-time emotional state to their personal decision history and acts proactively to protect them.

See the Evidence Base →
231
Meta-analysis · JAMS · 75,000+ consumers
High-arousal emotional states and hedonic motives confirmed as primary drivers of impulsive purchasing behaviour at population scale.
51
Meta-regression · PMC 2023 · 14,957 participants
Emotion-related impulsivity positively predicts risky decision-making across age, gender, and clinical vs. non-clinical populations.
90%+
Classification accuracy · Multimodal EEG + biosignals · 2025
Multimodal emotion classification in real-world settings — confirming the technical feasibility of always-on consumer emotion monitoring.
The Technology

Five layers. One integration that no prior patent has achieved.

EMPATHIQ combines multimodal sensing, personalised emotional baseline modelling, real-time decision risk scoring, agentic LLM-powered intervention, and proactive wellbeing support — deployed for daily consumer use entirely on-device. The research foundations and problem framing are openly published on this site. The full technical specification, algorithms, and patent claims are available to qualified partners under NDA.

01
Layer 1
Multimodal Emotional State Sensing
HRV, EDA, BVP, skin temperature from wearables; voice acoustic features; keyboard patterns; contextual signals. Fused by on-device Multimodal Transformer into a real-time Emotional State Vector (ESV) — Valence × Arousal × Dominance.
Layer →
02
Layer 2 · Novel Claim
Personal Baseline & Decision-Emotion History
Each user's unique emotional fingerprint built from their own data — not population norms. The DEH links every decision event to the emotional state preceding it and the outcome that followed. No prior art patent does this.
★ Novel
03
Layer 3 · Novel Claim
Rash Decision Risk Score (RDRS) Engine
A personalised LSTM model trained on each user's own DEH computes a real-time risk scalar [0,1] — the probability this person is about to make a decision they will regret, based on their own historical patterns.
★ Novel
04
Layer 4 · Novel Claim
Agentic Intervention Engine & Pattern Mirror
Tiered interventions from soft nudge to LLM-generated Pattern Mirror — showing the user their own decision-emotion history in natural language at the moment of a detected decision event. Always dismissible.
★ Novel
05
Layer 5
Personalised Wellbeing Support Engine
ESV-matched content recommendations, weekly longitudinal emotional health reports, clinical escalation pathway. All processing on-device — no raw biometric data ever transmitted.
Layer →
Full Technical Architecture →
Collaboration

Seeking world-class partners across four domains.

EMPATHIQ requires partners who bring research rigour, hardware capability, platform scale, or institutional support. A full technical briefing is available under NDA.

🔬
Academic Research
Research Institutions & Universities
The world's first dataset linking continuous physiological emotional data to real-world decision events and outcomes does not yet exist. We need empirical research partners to build it using EMA methodology.
Enquire about research partnership →
 🏢
B2B Partnership
Enterprise & Platform Integration
EMPATHIQ's decision-protection capabilities can be embedded into financial wellbeing platforms, digital health applications, consumer banking, and workplace wellness programmes as an API or SDK.
Enquire about B2B licensing →
 ⌚
Hardware Manufacturing
Wearable & Biosignal Devices
The first preferred embodiment requires continuous HRV, EDA, BVP from a wrist-worn wearable. Hardware partners achieve meaningful product differentiation as the sensing layer of a patented decision-protection system.
Enquire about hardware licensing →
 🎓
Industry PhD / ARC Linkage
University & Higher Education
The EMPATHIQ research programme is structured for an ARC Linkage Project or Industry PhD programme, providing the empirical foundations for clinical and commercial validation of the invention.
Enquire about academic partnership →
Intellectual Property

Patent pending.
Priority date: April 2026.

A provisional patent application has been filed with IP Australia under the Patents Act 1990 (Cth) — Application No. 2026903561 — establishing an international priority date recognised across 170 countries.

The research foundations, theoretical frameworks, and gap analysis are openly published on this site — no registration required. The full patent specification, architectural blueprints, algorithm pseudocode, DEH schema, and 20 patent claims are available to qualified partners under a signed NDA.

Request Technical Briefing View Architecture →
CLAIM 01
Decision-Emotion History (DEH) — Links each decision event to the user's emotional state in the preceding time window and to the outcome. No prior art creates this record.
CLAIM 02
Rash Decision Risk Score (RDRS) — Personalised LSTM model trained on the individual's own DEH. Not population norms — this person's patterns only.
CLAIM 03
Pattern Mirror — LLM-generated natural language presentation of the user's own decision-emotion history at the moment of a detected decision. Not in any prior art.
CLAIM 04
On-Device Federated Architecture — All personal biometric data stays on device. Only differentially private gradient updates transmitted. Individual reconstruction infeasible.

20 total claims filed · 3 independent · 17 dependent · Full claims available under NDA