As more enterprises – and users – embark on their AI-led transformational journey, it’s important to realize that this transition is not a one-step process, but multi-phased. To achieve AI excellence, organizations require a solid foundation in data knowledge and representation. With this mindset, they can chart a successful transition to AI enablement.

As a trusted Google Cloud partner, Onix has enabled AI-powered transformations across numerous companies. With its suite of proprietary tools, Onix has accelerated the “data to AI” journey, as well as enabled data migration and modernization in “half the time and double the value.”

Here’s a look at Onix’s 3-step process in AI adoption – and how its solutions have supported companies at each of these stages.

Step #1 – Laying the foundation with cloud migration and modernization

As the first phase of the AI journey, enterprises need to build a robust, scalable, and cost-efficient cloud infrastructure and modernize their legacy systems. This stage sets the foundation for the development of efficient AI models. 

This stage essentially comprises:

• Cloud migration – moving the existing data and applications to cloud platforms like Google Cloud.
• Data modernization – the process of capturing and managing data on the cloud to enable real-time analytics.
• Cloud modernization – the process of improving performance and cost-efficiency through cloud optimization.

Onix facilitates this initial phase with its proprietary tools, namely:

• Eagle – the cloud migration & planning tool that helps in data discovery and assessment, as well as migration planning and cloud optimization.
• Raven – the automated workload conversion tool that automatically converts and optimizes workloads from legacy systems to the modernized cloud platform.

Here are some real-world case studies of Onix customers implementing this phase successfully:

• In collaboration with Google Cloud, TELUS modernized its on-premises legacy systems on Google Cloud, thus improving its data-driven decision-making process.
• This U.S.-based grocery retailer achieved 40% faster runtime and 30% cost savings over 5 years by migrating their Snowflake and Azure-powered workloads to Google Cloud for real-time analytics.
• A multinational telecom provider achieved real-time analytics by migrating from Teradata and Google BigQuery.
• U.S.-based insurance holding company State Auto leveraged Onix’s Birds suite and Google Cloud to improve its performance, lower costs, and manage its data scalability.
• Retail chain company Kohl’s facilitated an omnichannel customer experience for its shoppers through Google Cloud.
• A U.S.-based toy manufacturer modernized its data warehouse on Google Cloud to improve its analytical capabilities.

Step #2 – Building AI capability with AI/ML solutions

The next step is to build AI capability by deploying AI and machine learning (ML) solutions. The key focus on this transformational phase is to leverage AI in specific business functions to automate business processes, optimize operational efficiency, and discover business opportunities.  

This stage addresses each of the following key areas:

• Process automation – or leveraging AI to automate manual or repetitive tasks.
• Customer experience (CX) – or deploying AI tools in customer-focused areas like customer support chatbots, virtual agents, and personalized recommendations.
• Operations – or using AI to optimize business operations, including supply chains and inventory management.

With its powerful AI and ML solutions, Onix has guided its customers through this intermediary phase. Here are some of the customer success stories:

• A London-based digital bank successfully automated its marketing compliance by using Generative AI solutions.
• U.S.-based O’Neal Industries leveraged AI-enabled data extraction and summarization to streamline its document processing activity.
• Healthcare services company Metricwire utilized an AI-enabled scheduling tool to improve its customer support efficiency, resulting in a scheduling accuracy of 90% and a latency of under one second.
• A U.S.-based telecom network operator successfully transformed its customer experience with an AI-enabled contact center.
• This multinational electronics retail company used AI-enabled intelligent virtual agents to transform its customer experience.
• A Canada-based telecom provider expanded its customer support to multiple languages by using AI and machine learning technology.
• A multinational advertising firm accelerated its AI-enabled innovation by adopting GenAI and MLOps solutions.

Step #3 – Transforming to a super user with advanced AI optimization

The final stage of the AI journey is for enterprises to maximize the value of their AI investment for business benefit. This stage involves embedding AI in their business processes and leveraging advanced techniques and tools to build a competitive advantage. During this stage, AI adoption goes beyond selected processes to an enterprise-level business transformation.

Here are some key aspects for enterprises to become a “super user”:

• Validating data for AI readiness – This process is necessary to validate the quality and readiness of data being fed into training the AI models for an optimum output.
• Generating synthetic data – This step is necessary to address any data gaps for model training purposes and secure simulations for sensitive data.
• Implementing advanced AI agents – This process is all about leveraging Agentic AI and advanced AI platforms for faster, integrated business solutions.
• Achieving long-term ROI and business growth – This encompasses using modern cloud platforms to increase cost savings, improve decision-making, and encourage innovation.

Onix facilitates this advanced stage with its proprietary tools, namely:

• Pelican – the AI-powered tool used for data validation and reconciliation. 
• Kingfisher – a synthetic data generation tool that can generate accurate synthetic data required to train advanced AI models and address any data gaps. 
• Wingspan – a pioneering Agentic AI platform built to accelerate the “data to AI” journey by 2-3x as compared to traditional methods.

Here are some real-world case studies of Onix customers successfully implementing this advanced stage:

• A leading global bank saved 85% of time in data preparation by using the Kingfisher tool for synthetic data generation.
• Cisco, the Fortune 500 company, leveraged the Pelican tool for 100% data validation during its internal cloud migration.
• A leading American retailer achieved 90% savings by using Pelican for data validation when migrating data to Google Cloud.
• This healthcare company achieved 60% time efficiency by using Pelican to perform its data validation.
• Powered by cloud modernization, TELUS successfully elevated its GenAI capabilities for improved decision-making.
• Sweden-based healthcare company Humana successfully migrated its 13,000 employees to Google Workspace for improved security and productivity.
• Milwaukee-based HR company HarQen implemented AI-enabled hiring to boost recruitment for its customers.
• A marketing solutions company accelerated its innovation through a secure, scalable AI foundation. 

Onix – the partner in AI transformation

As more companies embrace AI technologies, they need a strategic approach to transition from a novice to a super AI company. In this transformational journey, Onix delivers strategic value through its comprehensive approach, ranging from the initial foundation to the final modernization phase.
Our team of AI/ML experts is ready to support you through this critical journey. Contact us to explore how we can accelerate your “data to AI” journey.