01
Connect
Bring your signals together
Wearables, labs, symptoms, medications, meals, mood, sleep, movement, and notes can all help. You can begin with only some of them.
Building the health operating system of the future.
Join us.Private, personal health intelligence from the signals you already have.
Discover equ, the most advanced health companion
Mood, sleep, meals, movement, social patterns, symptoms, labs, and daily energy become one private view of which patterns are forming, why the patterns matter, and what action to take next.
Available context
Signals that can start the model
Mood
Sleep
Meals
Movement
Social
Energy
You can begin with the signals available today. More context sharpens the model over time.
CONNECTED MODEL
Explains the relationships behind each recommendationequLifestyle brief
CONNECTED MODEL
Signals become one private health picture
equ reads mood, sleep, meals, movement, symptoms, labs, and energy together instead of treating each signal as a separate score.
TODAY'S GUIDANCE
Start with the most useful next step
When sleep, movement, food, and connection shift together, the brief explains the pattern and gives a practical action for today.
NEXT 48 HOURS
Watch the pattern change
equ keeps the model adaptive, so guidance updates as your signals and context change.
Research Foundation
equ is built on research, not guesswork
These four papers show the scientific foundation behind equ's explainable, multi-signal health intelligence, developed with collaborators from leading institutions including MIT, Harvard, and the University of Cambridge.
2025
Selected paperComorbid anxiety predicts lower odds of MDD improvement in a trial of smartphone-delivered interventions
Journal of Affective Disorders
Authors
Morgan B. Talbot, Jessica M. Lipschitz, Omar Costilla-Reyes
How this shaped equ
Shows why equ models interacting signals instead of treating mood, anxiety, and behavior as isolated variables.
2024
Selected paperSymbolic regression with a learned concept library
Advances in Neural Information Processing Systems
Authors
Arya Grayeli, Atharva Sehgal, Omar Costilla-Reyes, Miles Cranmer, Swarat Chaudhuri
How this shaped equ
Informs equ's neurosymbolic foundation: structured, reusable concepts that make reasoning easier to inspect.
2023
Selected paperIndividual behavioral insights in schizophrenia: A network analysis and mobile sensing approach
International Conference on Pervasive Computing Technologies for Healthcare
Authors
Andy Davies, Eiko I. Fried, Omar Costilla-Reyes, Hane Aung
How this shaped equ
Supports equ's connected view of daily behavior, where mobile signals become useful when modeled jointly.
2025
Selected paperEstimation of total body fat using symbolic regression and evolutionary algorithms
International Conference on the Applications of Evolutionary Computation (Part of EvoStar)
Authors
José-Manuel Muñoz, Odin Morón-García, Omar Costilla-Reyes, J. Ignacio Hidalgo
How this shaped equ
Shows that health models can stay compact and interpretable while remaining useful for real decisions.
How equ works
From scattered signals to clear next steps
equ shows what is changing, why the pattern matters, and what to try next.
02
Reason
See the pattern
equ connects the relationships across signals and shows the drivers, timing, and confidence behind each insight.
03
Act
Choose the next step
Guidance turns the explanation into actions you can review, follow, and refine.
The result: less dashboard guessing, more timely guidance, even with incomplete data.
The difference
Not another tracker. A thinking health system.
Trackers show what happened. equ connects the health signals you already have to show which patterns are forming, why the patterns matter, and what to try next, even when the picture is incomplete.
Typical tracker view
Separate signals, separate guesses
Sleep
Restless sleep
Meals
Lighter intake
Movement
Lower activity
Mood
Energy dip
Labs
Context needed
Scores
Separate charts
More health data helps, but relationships between signals can stay hidden without a reasoning layer.
equ reasoning
Connects the relationships behind the guidanceequSystem brief
CONNECTED MODEL
Signals become one health picture
equ interprets behavior, biology, symptoms, medication, energy, and environment together so guidance is more personal than tools that score each input alone.
EXPLAINED REASONING
Every insight includes the reasoning
Recommendations show the relationships, assumptions, and timing behind the guidance so the decision path is easier to evaluate.
ADAPTIVE GUIDANCE
Guidance changes as your context changes
As patterns, goals, constraints, and context change, equ updates guidance while keeping the reasoning private and inspectable.
Useful logs, limited interpretation
Typical trackers
- Logs isolated metrics and charts
- Shows what happened after the fact
- Leaves you to interpret the pattern
- Uses generic scores with limited context
- Often depends on cloud-first data flows
A private reasoning layer for health
equ
- Connects the health signals you already have into one private model
- Explains which health patterns are forming
- Suggests the next useful action
- Adapts to your biology and constraints
- Keeps intelligence private and accountable
See how private, explainable intelligence can turn fragmented health data into clearer, more personalized decisions.
Join the equ betaProduct intelligence
How equ is unlike today's AI
equ is not a chat layer over health data. The platform is a private health reasoning system built to connect context, explain patterns, and support more personalized decisions.
Built for health context
General-purpose AI waits for prompts. equ uses available signals, routines, constraints, and daily decisions so guidance becomes sharper with context and still works when inputs are missing.
Reasons across relationships
equ connects behavior, biology, routines, and symptoms to reveal the pattern behind the recommendation.
Models the individual
Guidance adapts to personal patterns, goals, schedule, preferences, and real-world limits instead of relying on generic advice.
Shows the reasoning
Insights include the inputs, assumptions, and reasoning behind each recommendation so the decision path stays inspectable.
Core capabilities
Capabilities that matter for real health decisions
The product focuses on the moments where people need clarity: which health patterns are forming, why the patterns matter, and what action to take next.
Unified health context
Wearables, labs, symptoms, medications, meals, sleep, mood, movement, and notes can form one working health context when available.
Adaptive recommendations
Actions change as biology, behavior, goals, constraints, and confidence in the pattern change.
Early pattern detection
equ helps surface meaningful shifts before they become obvious, so you can respond earlier.
Accountable guidance
Recommendations are explainable, privacy-first, and grounded in evidence users can review.
Latest Research and Insights
Explore the latest research and analysis from Equ Healthcare.
White Paper
Neurosymbolic AI in Healthcare: From Foundations to Clinical Translation
By Dr. Omar Costilla Reyes•October 19, 2025
Neurosymbolic AI integrates neural networks with symbolic reasoning to create systems that are high-performing and clinically auditable. This review examines current paradigms, clinical applications, and a path toward safe clinical translation.
Trust architecture
Privacy Is the Foundation
A health reasoning system only works when people trust the platform. equ is designed so sensitive health data, reasoning, and model improvement stay private, minimized, and under user control.
On-device first
Sensitive health intelligence is designed to run locally whenever possible, keeping personal context close to the user.
Encrypted by default
Data is protected in transit and at rest, with controls built for health-grade confidentiality from the start.
No resale model
equ is not built around selling personal health data. The product is designed around user ownership, consent, and control.
Healthcare-ready standards
The architecture is designed for HIPAA-ready and SOC 2-ready workflows as equ moves toward clinical and enterprise use.
The equ Longevity Podcast
Conversations at the frontier of explainable AI and precision health.
Latest Episode
Mental Health Innovation with Dr. Thomas R. Insel
Former Director, National Institute of Mental Health•Episode 001 • 58 min
Explore how technology, data, and empathy are transforming mental health care, from digital biomarkers to community-based approaches for the 21st century. Hosted by Dr. Omar Costilla Reyes, featuring conversations across neurosymbolic AI, precision health, and evidence-based science.
Backed by Leaders in Research and Innovation
Supported by world-class institutions and technology partners committed to advancing health AI.
Ready to join the private beta?
Join the beta to see how equ connects the health signals you already have, shows which health patterns are forming, and becomes more specific as context arrives while keeping sensitive data private by design.
Start with the signals you have
Explainable guidance
Encrypted by default
More context, more personalized guidance