Integrate.ai

Developer-friendly APIs for federated learning and analytics

Deploy federated machine learning and analytics in days, not months.
Privacy Enhancing Technology

Build trust with data custodians.

Federated Learning and Analytics

Stop moving data for modeling and analytics.

Data is decentralized: Local models are trained and analytics are run privately where the data is accessible.
Only model parameters move: Aggregated models and analytics are calculated at the central server based on local model parameters, not raw data.
Differential Privacy

Use the gold standard in privacy.

Assure your partners that their sensitive data will remain private.
Prevent re-identification: Add noise during local model training so individual data cannot be inferred from model parameters.
Built-in privacy tooling: Differential privacy is included in models configuration by default, so you always get the best in privacy.
Privacy Settings

Make practical privacy decisions.

Differential privacy settings are abstract. integrate.ai helps users understand the practical impacts of differential privacy on their models.
Adversarial models: We simulate a range of attacks on models to calculate the risk of private information being leaked.
Vulnerability reports: Every model is scored for privacy risk so that users can optimize for privacy and accuracy.
Trusted deployment

Privacy by design

You and your partners need to trust your infrastructure security. integrate.ai builds security into our platform and processes, enabling you to optimize for trust and ease of deployment.
Federated learning central server: Isolated cloud architecture and robust enterprise security measures protect again data leakage.
Client software: Always deployed where the data resides, whether in a private cloud, on-prem, or at the edge.
Federated Learning and Analytics

Stop moving data for modeling and analytics.

Data is decentralized: Local models are trained and analytics are run privately where the data is accessible.
Only model parameters move: Aggregated models and analytics are calculated at the central server based on local model parameters, not raw data.
Differential Privacy

Use the gold standard in privacy.

Assure your partners that their sensitive data will remain private.
Prevent re-identification: Add noise during local model training so individual data cannot be inferred from model parameters.
Built-in privacy tooling: Differential privacy is included in models configuration by default, so you always get the best in privacy.
Privacy Settings

Make practical privacy decisions.

Differential privacy settings are abstract. integrate.ai helps users understand the practical impacts of differential privacy on their models.
Adversarial models: We simulate a range of attacks on models to calculate the risk of private information being leaked.
Vulnerability reports: Every model is scored for privacy risk so that users can optimize for privacy and accuracy.
Trusted deployment

Privacy by design

You and your partners need to trust your infrastructure security. integrate.ai builds security into our platform and processes, enabling you to optimize for trust and ease of deployment.
Federated learning central server: Isolated cloud architecture and robust enterprise security measures protect again data leakage.
Client software: Always deployed where the data resides, whether in a private cloud, on-prem, or at the edge.
Developer Tools

Focus on building. We'll take care of the federation.

Accelerate your product roadmap with our production-ready platform.
integrate.ai SDK: APIs seamlessly integrate the federated learning and analytics workflow directly into your product.
Managed Infrastructure: Save engineering time with automated infrastructure provisioning and orchestration.
Built-in admin tools: You don't need to build admin tools from scratch to manage users, generate secure tokens, and connect datasets, unlike using open source.
Data Science Tools

Empower users with a complete data science toolset.

Data scientists and researchers get the tools they need for their end-to-end workflow.

Model training

Train deep learning models, GLMs, CNNs, LSTMs, Transformers, FFNNs, and decision trees.

Exploratory data analysis

Calculate basic statistics and generate visualizations to understand datasets individually and in aggregate.

Feature engineering

Run data cleaning and generate new features on decentralized data to prepare for model training.
Integrate.ai vs NVIDIA FLARE

Move quickly with production-ready Federated Learning.

integrate.ai
NVIDIA Flare
Infrastructure
Managed end-to-end platform
Python SDK
Web API Access
Data Science Tools
Out-of-the-box support for most models
Exploratory data analysis
Feature engineering
Privacy
Built-in differential privacy
Understandable privacy settings
Observability
Real-time network monitoring
Data network value metrics
blog

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