B EYE

B EYE is a consulting firm offering data, artificial intelligence, and enterprise performance management (EPM) services. The organisation is presented as a provider of senior expertise to build modern data platforms, deploy AI at scale, and accelerate business decision-making. Headquarters country is not specified in the source. Industry coverage and project references indicate operations across multiple regions aligned with clients in sectors such as life sciences, healthcare, supply chain, retail, manufacturing, sales and marketing, and energy.

Services and Capabilities

• Data platform design and implementation — delivering cloud and on-premises systems for consolidated data storage, ingestion pipelines, and governed data models.
• AI and machine learning solutions — developing and operationalising models, model deployment pipelines, and associated tooling to support prediction and automation.
• Enterprise Performance Management (EPM) — implementing budgeting, forecasting, consolidation, and reporting processes and systems that integrate financial and operational data.
• Analytics and business intelligence — building reporting layers, dashboards, self-service analytics environments, and metric frameworks for decision support.
• Data integration and ETL/ELT — creating automated data ingestion, transformation, and orchestration processes between transactional systems and analytical stores.
• Process automation and operational analytics — delivering software and workflows that reduce manual tasks and surface actionable insights to business users.

Industry Focus

• Life sciences and healthcare — work includes integrating clinical and operational data, supporting analytics for research or care delivery, and managing regulatory data needs.
• Supply chain and manufacturing — projects involve inventory and logistics data consolidation, demand forecasting models, and production analytics.
• Retail and sales & marketing — deliverables include customer and sales analytics platforms, campaign measurement, and point-of-sale data integration.
• Energy — implementations cover asset and operations data integration, performance monitoring, and analytics for operational efficiency.

Technology and Delivery Approach

• Emphasis on data integration and modern data platform architectures to centralise and govern data.
• Use of analytics and BI layers to deliver reporting, dashboards, and metric frameworks to business stakeholders.
• Automation of data pipelines and operational processes through ETL/ELT, orchestration tools, and deployment pipelines for models and applications.
• Application of AI and machine learning where indicated, including model development, deployment, and monitoring as part of delivery.
• Focus on combining technical implementations (systems and software) with process changes to enable decision-making and performance management.