Most productivity tools track what you do. sentinelOS understands how you function and helps you make better decisions.
sentinelOS is a behavioral intelligence platform that detects performance patterns, predicts decision risk, and provides personalized recommendations to improve execution and prevent burnout.
Instead of acting as a passive tracker, sentinelOS serves as an active decision partner.
People rarely fail due to lack of discipline.
They fail because they cannot see their behavioral patterns:
- Overestimating energy
- Scheduling deep work at the wrong time
- Repeating decisions that historically fail
- Ignoring early burnout signals
Existing tools collect data but do not reason about it.
sentinelOS closes that gap.
sentinelOS is not a to-do app.
It is a decision intelligence engine that:
✅ Detects behavioral patterns
✅ Correlates energy, mood, and performance
✅ Identifies high-risk scheduling decisions
✅ Surfaces invisible productivity traps
✅ Provides explainable insights
The goal is simple:
Help users make decisions their future self would thank them for.
Structured data capture including:
- Planned vs actual execution
- Energy and mood levels
- Task type
- Time-of-day context
High-quality inputs enable meaningful intelligence.
Analyzes behavioral data to uncover performance drivers such as:
- Success rate by time block
- Energy-performance correlation
- Task difficulty trends
- Failure clusters
Transforms raw data into actionable knowledge.
Converts statistical findings into human-readable guidance:
“You complete deep work tasks 68% more often before 1PM.”
No dashboards without interpretation.
No data without meaning.
Before committing to a plan, sentinelOS evaluates historical behavior and flags risky decisions:
sentinelOS doesn’t just observe behavior — it challenges it.
Detects dangerous trends early, including:
- Rising failure rates
- Overplanning patterns
- Sustained low-energy execution
- Burnout trajectories
Prevention > recovery.
sentinelOS is built around a layered intelligence architecture:
-
Data Layer
Stores structured behavioral events optimized for analysis. -
Logic Layer
Processes correlations and performance metrics. -
Insight Layer
Transforms analytical output into explainable recommendations.
This separation ensures scalability and future ML integration.
Frontend: Next.js (app directory)
Backend: Node.js (Express or similar)
Database: PostgreSQL (Prisma schema added under server/prisma)
Tech stack (updated):
Notes:
- A Prisma schema and seed script were added at
server/prisma/schema.prismaandserver/seed-prisma.ts. - The client folder was switched to a Next.js scaffold (
client/app,client/package.json).
Designed for clarity, performance, and analytical flexibility.
Most software helps users stay organized.
I wanted to build software that helps users become self-aware.
sentinelOS explores a question that fascinates me:
What if software could detect the decisions we are statistically likely to regret?
This project reflects my interest in:
- intelligent systems
- human-centered engineering
- behavioral data
- decision support software
- Predictive performance modeling
- ML-driven behavioral forecasting
- Personalized workload calibration
- Cross-user anonymized insights
- Mental load scoring
- Adaptive planning engine
✅ Actively developed
🔬 Intelligence features expanding
📈 Architecture designed for scale
Built by a systems-focused computer science student passionate about designing software that augments human decision-making.