Pangeam

Pangeam faced several internal challenges that limited their growth and their ability to deliver value to clients:

• Hardware Dependency: Reliance on expensive, proprietary Raspberry Pi based sensors made deployments costly (over $100,000 per client) and limited scalability. Because the system was proprietary we had to manufacture and install all our own sensors.
• Operational Overhead: Managing custom hardware distracted the team from their core mission of providing actionable insights into office space utilization.
• Outdated Technology Stack: The older Django and Python platform resulted in inefficiencies and limited the ability to process data at scale.
• Scalability Limitations: The hardware-dependent model made it difficult to onboard larger clients or adapt to varying client needs.

To address these challenges, we focused on overhauling Pangeam’s internal operations and technology:

• Shift to a Hardware-Agnostic Platform: We re-engineered the platform to work with any commercial off-the-shelf (COTS) cameras and sensors, eliminating the need for proprietary hardware.
• Custom Neural Networks: Developed advanced neural networks capable of processing data from various camera feeds to track space utilization accurately, regardless of the hardware used.
• Modern Technology Stack: Migrated the platform to Next.js, improving performance by 10x and enabling more efficient data processing.
• API-First Architecture: Designed the system with an API-first approach, facilitating integration with clients’ systems and supporting scalability.
• Flexible Deployment Options: Enabled both cloud and on-premise deployment models, allowing Pangeam to meet diverse client requirements and process real-time data from over 1,000 camera feeds simultaneously.

After the internal transformation, Pangeam was able to deliver significantly improved value to their customers:

• Accurate Space Utilization Insights: Clients could now receive real-time data comparing actual space usage to design intent, enabling more informed decisions about office layouts and resource allocation.
• Cost-Effective Solutions: The reduction in hardware costs made the platform more financially viable for a broader range of clients.
• Flexibility and Integration: The hardware-agnostic, API-first platform allowed clients to integrate Pangeam’s insights with their existing systems seamlessly.
• Strategic Real Estate Investment: Clients could optimize their real estate spend, ensuring investments were aligned with actual usage and business outcomes.

• Cost Reduction: Halved hardware and deployment costs, making the solution more attractive to potential clients.
• Operational Efficiency: Streamlined operations by focusing on software development and data analytics rather than hardware management.
• Scalability: Positioned Pangeam to serve enterprise clients and handle large-scale deployments effectively.
• Strategic Focus: Freed up resources to focus on providing valuable insights into space utilization.