Recommender System
Our recommender solutions apply machine learning to analyze user behavior and item attributes, delivering individualized suggestions that drive engagement and satisfaction.
01
Content-Based Filtering
Algorithms match user preferences to item attributes to suggest similar offerings.
02
Collaborative Filtering
Analysis of purchase/rating patterns across all customers informs personalized recommendations.
03
Hybrid Approach
Uses both content and collaborative data for improved accuracy.
04
Real-Time Personalization
Continuous model retraining ensures relevance as customer tastes evolve over time.

Intelligent Search

Our intelligent search solutions apply machine learning to index vast semi-structured repositories and surface the most useful information to answer queries.

Computer Vision

By customizing models to your unique content domains, we help organizations harness insights from visual assets to optimize operations, enhance experiences and more.

Enterprise Knowledge Graph

Connected Intelligence for Strategic Advantage As organizations gather extensive volumes of diverse data across business lines, the opportunity to extract unified understanding grows exponentially. However, information residing in application silos or disconnected systems limits strategic perspective. An enterprise knowledge graph (EKG) addresses this challenge by establishing a virtual intelligence nucleus linking relevant entities and semantics from distributed sources.

Anomaly Detection

Our knowledge graph solutions build contextual taxonomies linking entities across your data ecosystem to power predictive analytics, personalization and more.

Embedded AI

Our embedded AI solutions develop custom machine learning models optimized for deployment on edge devices to power autonomous functionality.

Cost Monitoring & Optimization

Managing Spending in Cloud Environments Public cloud models bill customers for actual resource usage rather than fixed capacity reservations. While this usage-based pricing model provides flexibility, it can be difficult for organizations to track spending across different accounts and services. Left unchecked, cloud costs may spiral out of control.

DevOps

Breaking Down Silos for Faster Delivery Traditional development and operations teams tended to work sequentially, with long handoffs between code completion and deployment. This resulted in slow, error-prone releases. DevOps aims to align development processes end-to-end from code to monitoring. It unites previously siloed teams through automation and shared tooling.

Application Migration

Embracing Cloud-Native Development and Operations As application portfolios grow in size and complexity, maintaining costly on-premises infrastructure can strain IT budgets and slow innovation. Meanwhile, public cloud platforms now deliver virtually unlimited scalability and high availability at lower costs. Migration provides a path for organizations to streamline operations and empower developments.

Cloud Architecture

Designing Scalable and Robust Cloud Solutions As more workloads transition to the cloud, a well-architected infrastructure becomes essential to fully unlocking the benefits of elasticity, availability and agility. Cloud architecture refers to frameworks and best practices for deploying distributed systems across on-premises datacenters and public clouds in a standardized, scalable and secure manner.

Native Cloud Application

Building Software the Cloud-Native Way As organizations embrace cloud-first strategies, developing applications native to public clouds delivers clear advantages over merely migrating existing software. Cloud-native apps are purpose-built for modern infrastructure like compute services, storage and databases. They leverage elasticity, high availability zones, auto-scaling and other cloud services by design.

USE CASES 1

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