Serving as a unified platform for Data Engineering, Analytics and AI/ML
RustIQ provides a high-performance data engineering and machine learning platform for the modern companies. Make powerful, seamless workflow using our SQL and Python DataFrame APIs.
USE cases
RustIQ exposes both SQL and Python DataFrame interfaces for:
DataFrames
Data Engineering
Combine the performance of DuckDB, Pythonic UX of Polars and scalability of Apache Spark for data engineering from MB to PB scale.
Scale ETL workflows effortlessly from local to distributed environments.
Enjoy a Python-first experience without JVM dependency hell.
Leverage native integrations with cloud storage, open catalogs, and data formats.
Scale ETL workflows effortlessly from local to distributed environments.
Enjoy a Python-first experience without JVM dependency hell.
Leverage native integrations with cloud storage, open catalogs, and data formats.
SQL
Data Analytics
Dataloader
ML/AI
Blend the snappiness of DuckDB with the scalability of Spark/Trino for unified local and distributed analytics.
Utilize complementary SQL and Python interfaces for versatile analytics.
Perform snappy local exploration with DuckDB-like performance.
Seamlessly scale to the cloud, outperforming distributed engines like Spark and Trino.
Utilize complementary SQL and Python interfaces for versatile analytics.
Perform snappy local exploration with DuckDB-like performance.
Seamlessly scale to the cloud, outperforming distributed engines like Spark and Trino.
Streamline ML/AI workflows with efficient dataloading from open formats like Parquet and JPEG.
Load data efficiently from open formats directly into PyTorch or NumPy.
Schedule large-scale model batch inference on distributed GPU clusters.
Optimize data curation with advanced clustering, deduplication, and filtering.
Load data efficiently from open formats directly into PyTorch or NumPy.
Schedule large-scale model batch inference on distributed GPU clusters.
Optimize data curation with advanced clustering, deduplication, and filtering.
Industry
Industry overview
Retail
Discover how RustIQ addresses these challenges with scalable, real-time, and multimodal solutions. Explore our innovative platform today!
Healthcare
Healthcare organizations must integrate diverse data types—ranging from patient medical records to diagnostic imaging and IoT health devices. These disparate data sources often lack interoperability, resulting in fragmented workflows that slow innovation and affect patient outcomes.
Retailers rely on data from inventory systems, customer purchasing patterns, and digital behavior analytics. However, siloed data systems and fragmented tools hinder their ability to generate timely insights, delaying predictive modeling and strategic decision-making.
Finance
In the finance industry, real-time data processing is critical for detecting fraud, managing risk, and ensuring compliance with ever-evolving regulations. However, traditional systems struggle to handle the sheer volume of transactional data efficiently, creating bottlenecks that delay critical decisions.
Our work
How we solve your problems
products
Products
RustIQ Core
This scalable cloud synchronization solution supports distributed data management, enabling teams to securely and efficiently collaborate across locations. With dynamic data partitioning and low-latency transfers, CloudSync ensures optimal performance for remote or hybrid infrastructures.
MLBoost
RustIQ’s GPU-accelerated module for machine learning offers seamless integration with frameworks like PyTorch and TensorFlow. It provides high-speed model training and inference capabilities, reducing processing times while maintaining precision for real-time applications.
RustIQ Studio
An interactive, user-friendly environment designed for real-time data manipulation and visualization. RustIQ Studio empowers teams to explore datasets, develop machine learning models, and generate actionable insights without needing deep technical expertise.
Our high-end rust-based engine optimized for processing multimodal data. It unifies text, images, vectors, and tensors into a single framework, enhancing efficiency for analytics and machine learning tasks.
CloudSync
capabilities and features
Blazing efficiency, designed
for seamless workflow
for seamless workflow
Rust-Based Engine
The platform seamlessly integrates diverse data types into one unified framework, enabling businesses to process and analyze structured and unstructured data efficiently within the same pipeline.
Multimodal Data Integration
RustIQ leverages the Rust programming language for its core engine, ensuring lightning-fast performance, superior memory safety, and scalability to handle massive datasets. Its efficient architecture minimizes runtime errors and optimizes resource use.
Built-In ML Support
RustIQ simplifies machine learning workflows with native support for popular frameworks. GPU acceleration ensures faster model training and inference, eliminating the need for external preprocessing.
Distributed Architecture
RustIQ’s distributed system is designed for scalability, effortlessly managing data at petabyte scales. Kubernetes-based orchestration ensures dynamic load balancing, high availability, and optimal resource utilization.
Qureshi Luqman Mahmood
Chief Executive Officer
(CEO)
(CEO)
Kupoluyi Olubunmi Folahanmi Paul
Chief Technology Officer (CTO)
El Habib Kallouch
Chief Business Development
Officer (CBDO)
Officer (CBDO)
Omar Kinzi
Chief R&D Officer
(CRDO)
(CRDO)
our Team
Leadership