Replace 25+ cloud services with one industrial lakehouse.
Stitching Kinesis + Timestream + S3 + Glue + EMR + SageMaker + IAM + Cognito + IoT Core is the dominant cost and timeline killer for OEMs. Flex83 collapses them into one platform — one contract, one API, 6× lower TCO at production scale.
The hyperscaler stack is 25 services, 25 bills, and 25 ways to break.
Every industrial OEM that builds on AWS, Azure, or GCP ends up assembling the same 20+ service stack. The cost isn’t the compute. It’s the team you need to keep it running.
15–25
Stream ingest, time-series store, lakehouse, catalog, IAM, federation, batch compute, ML serving, alerting, visualization — each with its own SDK and SLA.
3–5×
Building on hyperscaler primitives costs 3–5× more in engineering time than starting with an integrated AIoT platform — before factoring in the platform team you’ll need to keep operating.
20 people
Up from 14 in 2014 — pure operational overhead. Most of that growth is the platform team, not the team building product.
One platform that does what 25 services did — better, governed, and yours.
Flex83 is an industrial data lakehouse with stream processing, batch compute, ML, governance, and visualization built in. The data lands once. It’s queryable by every workload. It’s governed by one catalog. It’s deployed on any cloud.
Your team operates one platform. Not twenty-five.
Lakehouse storage with open table formats and time-series optimization.
OLAP analytics engine for cross-asset, cross-tenant queries.
Backpressure-aware ingest from 70+ device and OT protocols.
Unified lineage, schema registry, and access policies across the lakehouse.
Scheduled jobs and Spark workloads on the same governed data.
SQL editor across stream, lake, and cube — no copies, no exports.
From device to dashboard on one stack.
A reference architecture for replacing the hyperscaler IoT stack with a single Flex83 industrial lakehouse.
FlexStream pulls every device, PLC, MES, and ERP source.
Data lands in FlexLake under one governed schema.
Catalog handles lineage, access, and audit across workloads.
Stream, batch, OLAP, and ML run against the same data.
Dashboards, apps, and APIs consume from one platform.
A flatter cost curve and a smaller platform team.
Three things that change when 25 services become one platform.
Cost predictability instead of cost surprises
One contract, one billing model. No more 2 a.m. CloudWatch bill spikes from a misconfigured Kinesis shard.
A platform team you can actually staff
One platform requires a handful of people to operate — not the 15-to-25-person platform team a stitched hyperscaler stack demands at scale.
Governed data, queryable everywhere
Stream apps, batch jobs, ML pipelines, and SQL dashboards all read from one governed lakehouse. No copies, no exports, no drift.
Production scale on a fraction of the footprint.
Lower TCO vs. hyperscaler-equivalent stack
Higher engineering productivity vs. DIY platform
Lower data streaming cost at 1.5M-device scale
Platform, one contract, one API to operate
Stop paying twenty-five vendors. Start owning one platform.
Talk to a Flex83 platform expert about replacing your hyperscaler IoT stack. We’ll walk you through the architecture, the cost model, and the migration path.