How a Utility provider Scaled to 5 Million+ Endpoints Without Losing Control of TCO

About the Client

A power and utilities provider needed to scale its platform to support millions of connected endpoints across its service territory. As the organization grew, it wasn't just endpoints that needed to scale; users, data, integrations, analytics, and AI all had to grow together, without losing control of total cost of ownership.

Business Challenges

The problem was never growth but the complexity that comes with it. Platforms rarely fail because they get too big; they fail because complexity accelerates faster than the architecture holding it together can adapt. That's the pressure the client faced as they scaled from 100K to 1M to well past 5M endpoints, each leap multiplying the demands on a system that was never meant to stretch that far. What leadership wanted was room to keep growing without surrendering to a full redesign every few years.

Six sources of complexity compounded as the platform grew:

• More systems — legacy, modern, and partner systems all needing to coexist.
• More users — internal teams and external stakeholders alike.
• More data — growing volume, velocity, variety, and veracity.
• More integrations — ERP, CRM, SCADA, IoT, and other systems requiring seamless exchange.
• More analytics — operational, historical, and AI-driven demands.
• More expectations — real-time, 24x7, global-scale requirements.

Left unaddressed, this growth curve heads toward a platform breaking point; performance drops, cost escalates, and innovation stalls. Leadership's mandate was clear: support millions of endpoints and thousands of users, operate across multiple regions, deliver real-time analytics, remain AI-ready, and control total cost of ownership, without a platform rebuild.

The Solution

IoT83 built the architecture on a unified data foundation, one designed to scale every dimension simultaneously so that assets, users, data, integrations, analytics, and intelligence all advanced on the same system instead of fracturing into a separate platform for each capability.

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The foundation enabled the organization to:

• Scale assets to 5M+ endpoints, handling millions of telemetry streams, without re-platforming.
• Support thousands of users across multi-tenant operations spanning multiple regions.
• Handle data at scale across volume, velocity, variety, and veracity through a single pipeline.
• Integrate with hundreds of systems — ERP, CRM, SCADA, files, and APIs through seamless exchange.
• Run real-time, historical, batch, and predictive analytics from the same foundation.
• Deploy and scale AI models, agents, embeddings, and tokens as a native part of the platform.
• Run on a technology stack combining Apache Iceberg, Apache Druid, Apache Spark, Apache Flink, and Kafka, deployable across AWS, Azure, GCP, or on-premises.

Instead of building separate data, analytics, and AI platforms, the client operates on one shared foundation — data, analytics, AI, and applications all built on the same base.

Platform Capabilities

Scale Foundation Built to scale from day one, with an architecture designed to support every dimension of growth rather than optimizing for a single metric.

Reusable Services Shared, reusable services avoid rework across capabilities and accelerate delivery of new use cases.

Distributed Architecture An elastic, resilient, and highly available architecture designed to keep performing as complexity and scale increase together.

Elastic Infrastructure Scale up or out on demand, paying only for what is used, so cost tracks actual consumption rather than growing ahead of it.

Business Outcomes

With Flex83, the client was able to:

• Scale to 5 million+ connected endpoints without re-architecting the platform.
• Support thousands of users across the organization on a multi-tenant foundation.
• Maintain total cost of ownership of under $0.10 per asset, per month.
• Grow with no re-platforming, no architecture rewrite, no performance bottlenecks, and no cost explosion.
• Shift from a traditional scale path, where more assets meant more infrastructure, more cost, and lower margins to a predictable cost curve that holds steady over time even as scale increases.

Engagement Snapshot

• Industry: Power & Utilities
• Endpoints: 5 Million+
• TCO: <$0.10 / Asset / Month

Why Flex83

Most platforms can prove they scale, yet few can prove they scale economically. Flex83's unified data foundation was built so that assets, users, data, integrations, analytics, and intelligence all grow together, which means reaching a new dimension of scale never forces a rebuild. 

Since the platform runs on reusable services and elastic, distributed infrastructure, the client pays for what it actually uses rather than stockpiling capacity ahead of demand, and that turns scale from a rising cost curve into a predictable one, leaving the organization with a platform that keeps growing without ever losing control of TCO.