Product Overview
TrackHrs is a full-stack time tracking and activity intelligence platform designed for distributed teams. It combines a desktop agent, web applications, and event-driven microservices to capture work activity, classify it, and present actionable analytics for organizations.
Accurate time tracking
Time tracked across tasks and projects with reliable capture and aggregation.
Activity intelligence
Activity monitoring with automated categorization for clearer operational insight.
Operational visibility
Dashboards and reporting for HR, managers, and operations teams.
Service Map
Desktop Agent
Activity capture, local runtime, and offline-friendly sync.
Activity Engine
Ingestion and classification orchestration.
Analytics Provider
Read APIs and statistics for dashboards and reporting.
AI Classifier
ML/rule-based classification service.
Core Domain Service
Auth, users, organizations, leave, payroll core domain.
Project Intelligence
Project/task time duration aggregation.
Billing & Subscriptions
Subscription and billing domain.
Notification Engine
Email and notification processing.
Object Pipeline
Object upload pipeline (S3-compatible).
Distribution Server
Desktop release and update distribution.
Marketing Platform
Public marketing and lead capture.
Operations Portal
Authenticated operations and admin experience.
Activity Intelligence Pipeline
Desktop activity event
Captured by the Tauri agent and sent securely to the platform.
Kafka topic
High-throughput ingestion decoupled from downstream consumers.
Activity consumer
Processes streams with partition-aware scaling.
Redis dedup
O(1) deduplication for multi-replica-safe processing.
Batch service
Batches of up to 100 items or 5s windows — fewer immediate writes.
MongoDB bulk upsert
Document model fits evolving activity payloads and org structures.
BullMQ classification
Background jobs separate latency-sensitive writes from heavier work.
Classifier API
Bearer-key FastAPI service; ML iteration isolated from Node services.
Classification update
Categories persisted; failures use circuit breaker, retry, DLQ.
Cache invalidation
Fresh dashboard stats on next read without TTL-only dependency.
Technology Decisions
Achievement Highlights
Production-style distributed platform
Rust desktop + modern web + microservices end-to-end.
Up to 100× fewer immediate DB writes
Batching on the ingest path reduces write amplification.
High-throughput async processing
Kafka and BullMQ absorb spikes and keep pipelines resilient.
Multi-replica-safe coordination
Redis dedup keys and distributed locks for cron and idempotent work.
Isolated ML service
Dedicated Python classifier; core platform stays strongly typed in TypeScript.
Full product surface
Desktop app, admin portal, marketing site, update server, and backend ecosystem.
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