70% of Industrial IoT Initiatives Never Scale. Yours Will.

Flex83 breaks the pilot trap with a production-grade AIoT platform that delivers 10x faster time-to-market, 90% lesser cloud costs, and full IP ownership—so you can turn connected assets into revenue streams without rebuilding your digital infrastructure.

Trusted by Industry Leaders Globally

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The Pilot Trap Is Costing You More Than Time

85% of companies remain stuck in pilot mode for over a year.

McKinsey research confirms what CXOs already feel—most IoT projects never escape proof-of-concept. Delayed launches, stalled ROI, and misaligned teams compound into strategic liability.

Bar chart showing 15% of AIoT solutions in wide scale production and 85% failed to reach production.
Bar chart showing current and expected use of AI in core processes, use cases, pilots, research, and no use.

Only 7% enterprises have
AI in core processes today

While competitors scale with AI, you're rebuilding data plumbing, resolving integration failures, and managing vendor dependencies that increase TCO without delivering business value.

From Connected Assets to Intelligent Revenue—In Weeks, Not Years

1

Real-Time Visibility Across All Assets

Flex83's Connection Manager unifies 50+ industrial protocols (OPC UA, Modbus, MQTT, Kafka) and enterprise systems (MES, ERP, SCADA) into one governed data foundation. No fragmented pipelines. No orphaned data lakes.

Dashboard showing energy optimization with 92.3% accuracy and anomaly detection training at 67% progress.
2

Governed Data Without Separate Data Stacks

Publish secure, governed data products via Open Catalog APIs. Your operational data flows to BI tools, analytics platforms, or external partners—without rebuilding ETL infrastructure or losing control.

API response showing a successful GET request with code 200 and message about fetching custom dashboards.
3

AI/ML That Runs at the Edge and in the Cloud

Deploy predictive maintenance, anomaly detection, and autonomous insights across 65 million devices. Flex83's embedded ML operates on-device for real-time inference and in-cloud for enterprise-scale training—no separate MLOps stack required.

Bar chart showing feature importance with is_international having the highest importance of 0.3930.

From MVP to Enterprise-ready in Weeks

Flex Edge Agent, Analytics Studio, and Dashboard Builder eliminate custom plumbing—so your team focuses on differentiation, not infrastructure.

2 Weeks
Proof of Concept (50 devices connected)
4 Weeks
Minimum Viable Product (50,000 devices)
4-5 Months
First Customer Deployment (500,000 devices)
6 Months
Enterprise Production (65M devices, 99.99% SLA)

Resources

Whitepaper

How to Build a Vision AI Application

Whitepaper

Hyper-Connected Applications & Middleware

Blogs

​Top 10 Real-World Utilization of IoT Technology in Manufacturing

Blogs

Why is Equipment-as-a-Service Need of the Hour

Case study

Why do industrial equipment manufacturers struggle with business transformation?

Videos

Flex83 Runtime Observability