Turning ideas into beautiful and intuitive digital experiences

Technology for Businesses, Solutions for People

World-class engineering services powering brands to deliver exceptional experiences

Engineering Solutions for the Now and Next

Our technology team has the expertise and experience to meet any technological need. We have built digital experiences for every industry from insurance to construction, from banking to home automation and commerce–no project is too complex. We take pride in delivering solutions on time and on budget through rapid prototyping and agile development.

What we do

Turning ideas into beautiful and intuitive digital experiences

The Internet of Behaviors (IoB) captures the “digital dust” of people’s lives from a variety of sources, and that information can be used by public or private entities to influence behavior. The data can come from a range of sources, from commercial customer data to social media to facial recognition, and as more and more data becomes available, the IoB will capture increasing amounts of information. Additionally, the technology that puts all the data together and draws insight is growing increasingly sophisticated.

Total experience combines traditionally siloed disciplines like multiexperience (MX), customer experience (CX), employee experience (EX) and user experience (UX), and links them to create a better overall experience for all parties. Not only does this streamline the experience for everyone, because organizations are optimizing across all experiences, it offers an excellent opportunity to differentiate an organization from competitors.

Privacy-enhancing computation comprises three types of technologies that protect data while it’s being used to enable secure data processing and data analytics:

  • The first provides a trusted environment in which sensitive data can be processed or analyzed. It includes trusted third parties and hardware-trusted execution environments (also called confidential computing).

  • The second performs processing and analytics in a decentralized manner. It includes federated machine learning and privacy-aware machine learning.

  • The third transforms data and algorithms before processing or analytics. It includes differential privacy, homomorphic encryption, secure multiparty computation, zero-knowledge proofs, private set intersection and private information retrieval.

Anywhere operations refers to an IT operating model designed to support customers everywhere, enable employees everywhere and manage the deployment of business services across distributed infrastructure. The model for anywhere operations is “digital first, remote first.”

The cybersecurity mesh is a distributed architectural approach to scalable, flexible and reliable cybersecurity control. COVID-19 has accelerated an existing trend wherein most assets and devices are now located outside traditional physical and logical security parameters. The cybersecurity mesh enables any person or thing to securely access and use any digital asset, no matter where either is located, while providing the necessary level of security.

As organizations accelerate digital business, security
must keep pace with the rapid change. Cybersecurity mesh enables a security model that retains the plasticity necessary to operate in the current conditions and offers security without hindering growth for the company.

Organizations have spent the past years focusing on efficiency, which meant when hit with a major disruption like COVID-19, many business processes were too brittle to quickly adapt and they simply broke.

During the rebuilding process, leaders must design an architecture that:

  • Enables better access to information

  • Can augment that information with new insights

  • Is composable, modular, and can change and respond more quickly as decisions are made

Hyperautomation is a process in which businesses automate as many business and IT processes as possible using tools like AI, machine learning, event-driven software, robotic process automation, and other types of decision process and task automation tools.

Organizations are often dragged down by “organizational debt,” which includes technical, process, data, architecture, talent, security and social debt. Collectively this debt affects value proposition and brand. The cause is an extensive and expensive set of business processes underpinned by a patchwork of technologies that are often not optimized, lean, connected or consistent.

AI projects often fail due to issues with maintainability, scalability and governance. However, a robust AI engineering strategy will facilitate the performance, scalability, interpretability and reliability of AI models while delivering the full value of
AI investments. Without AI engineering, most organizations will fail to move AI projects beyond proofs of concept and prototypes to full-scale production.

AI engineering stands on three core pillars: DataOps, ModelOps and DevOps.