The Complete AI Telemetry Platform

A comprehensive solution for monitoring, analyzing, and optimizing your data science projects. Built by ML engineers, for ML engineers.

Explore Features
0
Native Integrations
0
Models Tracked
0
% Platform Uptime
0
Minute Setup Time

Platform Core Features

Everything you need to monitor, debug, and optimize machine learning models in production, all in one unified platform.

📈

Experiment Tracking

Automatically log parameters, metrics, and artifacts from your ML experiments. Compare runs side-by-side with powerful visualization tools and never lose track of what works.

🔍

Model Monitoring

Real-time performance monitoring for production models. Detect data drift, concept drift, and model degradation before they impact your business metrics.

🎨

Interactive Dashboards

Build custom dashboards with drag-and-drop widgets. Share insights with stakeholders through intuitive visualizations that update in real-time.

🔔

Smart Alerting

Configure intelligent alerts based on custom thresholds. Get notified through Slack, email, or webhooks when anomalies are detected in your models.

🗄️

Model Registry

Centralized repository for all your models with version control, metadata tracking, and seamless deployment pipelines across environments.

🚀

AutoML Integration

Seamlessly integrate with popular AutoML frameworks. Track hyperparameter optimization runs and automatically register best-performing models.

🔐

Enterprise Security

SOC 2 Type II compliant with end-to-end encryption, role-based access control, and audit logging. Your data never leaves your infrastructure.

📊

Data Lineage

Track the complete lifecycle of your data from ingestion to model predictions. Understand dependencies and troubleshoot issues faster.

High Performance

Built for scale with distributed architecture. Process billions of data points with sub-millisecond latency and zero impact on training performance.

Live Telemetry Dashboard

Monitor your ML infrastructure in real-time with our intuitive dashboard interface

Model Accuracy
94.2%
Production Performance
Inference Latency
28ms
P95 Response Time
Data Drift Score
0.12
Kolmogorov-Smirnov
Predictions Today
2.1M
Requests Processed

Model Performance Trend (7 Days)

Seamless Integrations

Connect aitelemetry with your existing ML stack in minutes. Native support for the most popular frameworks and tools.

🔥
PyTorch
✓ Native Support
🧮
TensorFlow
✓ Native Support
🌲
Scikit-learn
✓ Native Support
XGBoost
✓ Native Support
🤗
Hugging Face
✓ Native Support
📓
Jupyter
✓ Native Support
🐍
Keras
✓ Native Support
☁️
AWS SageMaker
✓ Native Support
🔵
Azure ML
✓ Native Support
🌐
Google Cloud AI
✓ Native Support
🐳
Docker
✓ Native Support
Kubernetes
✓ Native Support

How aitelemetry Monitors Your Projects

Comprehensive ML Lifecycle Monitoring

From the first line of code to production deployment, aitelemetry tracks every aspect of your data science projects. Our platform provides end-to-end visibility into model development, training, deployment, and performance in real-world scenarios.

With automated instrumentation and minimal code changes, you can start monitoring in under 5 minutes. Our intelligent agents capture metrics, logs, and traces without impacting your model's performance.

  • Automatic experiment tracking with parameter and metric logging
  • Real-time model performance monitoring in production
  • Data quality checks and drift detection
  • Resource utilization tracking (CPU, GPU, memory)
  • Training progress visualization with live updates
  • A/B testing and champion-challenger comparison
  • Explainability and feature importance tracking
  • Custom metric definitions and business KPI monitoring

Monitoring Pipeline

Data Ingestion
15.2K
Events/Second
Active Models
247
In Production
Alert Rules
3
Triggered Today
Storage Used
124GB
Telemetry Data

Platform Architecture

Built on modern cloud-native principles for reliability, scalability, and performance

🎯 Collection Layer
Lightweight SDKs and agents collect telemetry data from your ML workflows with minimal overhead. Support for Python, R, Java, and REST APIs ensures compatibility with any technology stack.
🔄 Processing Layer
Distributed stream processing engine handles millions of events per second. Real-time aggregations, transformations, and anomaly detection powered by Apache Kafka and Flink.
🗄️ Storage Layer
Time-series optimized data stores with automatic compression and retention policies. Hot-warm-cold architecture ensures fast queries on recent data while maintaining cost efficiency.
🧠 Analytics Layer
Advanced analytics engine with ML-powered insights. Automatic pattern recognition, drift detection algorithms, and predictive analytics to surface issues before they impact production.
📊 Presentation Layer
Interactive dashboards and APIs provide access to insights. Real-time updates via WebSocket, comprehensive REST API, and embedded widgets for external applications.

Choose Your Plan

Flexible pricing that grows with your ML operations

Developer

$49/month
  • Up to 10 tracked models
  • 100K events per month
  • 30-day data retention
  • Community support
  • Basic dashboards
  • API access

Enterprise

Custom
  • Unlimited models
  • Unlimited events
  • Custom retention
  • Dedicated support
  • On-premise deployment
  • Custom integrations
  • SLA guarantees
  • Professional services