Connect the physical world to AWS, with security and scale
We design and implement enterprise IoT platforms on AWS IoT Core: secure telemetry ingestion, device fleet management, edge computing with Greengrass, real-time analytics and continuous operation. Real cases with ESP32, Raspberry Pi and industrial sensors.
Enterprise IoT goes beyond connecting a sensor — it's about building a real-time data platform with end-to-end security, managing thousands to millions of devices, edge computing where latency matters and analytics that generate business value. Caleidos designs, implements and operates IoT platforms on AWS IoT Core, AWS IoT Greengrass for edge, AWS IoT Device Management for fleets, and integration with Lambda, Kinesis, S3 and Bedrock for analytics and artificial intelligence. From pilot projects with ESP32 and Raspberry Pi to industrial deployments with thousands of sensors.
What you get with Caleidos
Secure ingestion with AWS IoT Core
MQTT/HTTPS connection with X.509 certificates per device, mutual TLS authentication and granular IAM policies. End-to-end security from sensor to cloud.
Edge computing with Greengrass
Local logic at the edge for minimum latency, offline operation and reduced cloud traffic. Lambda functions running directly on industrial devices.
Device Shadows and Fleet Management
Virtual state of each device replicated in cloud (Device Shadows), thousands of devices managed with AWS IoT Device Management, secure OTA updates and continuous monitoring.
Real-time analytics
Pipelines with Kinesis Data Streams, Lambda and Timestream for time series. Dashboards in QuickSight or Grafana and intelligence with Amazon Bedrock for anomaly detection.
How we work
Discovery and proof-of-concept
We define the use case, devices and SLOs (latency, throughput, availability). We build a functional PoC in 2-4 weeks that validates the end-to-end architecture.
Architecture and security
IoT platform design with AWS IoT Core as core, identity model per device, communication policies, certificate management and rotation plan.
Edge computing
When applicable, AWS IoT Greengrass deployment at edge for local logic, buffering against connectivity drops and latency reduction. Secure OTA update pipelines.
Analytics and applications
Analytics pipeline construction with Kinesis, Lambda and Timestream. Executive and operational dashboards. Bedrock integration for anomaly detection or prediction.
24×7 Operation
[Caleidos Lens©](/en/services/caleidos-lens) operates the platform with fleet health monitoring, alerts, incident management and continuous evolution.
Auna Ideas IoT
Healthcare IoT platform
Construction of an IoT platform with connected devices, secure ingestion to AWS IoT Core, analytics and dashboards. Demonstration of the Caleidos team's technical capability in enterprise IoT.
Read full case →Tech stack
What we get asked the most
What types of devices connect?
Any device capable of communicating via MQTT/HTTPS over TCP/IP. We work with microcontrollers like ESP32 and Raspberry Pi, industrial sensors, IoT gateways, OT equipment with Ethernet/cellular connectivity and commercial devices with AWS IoT SDK.
What is AWS IoT Core and what does it solve?
It's the AWS managed service for connecting and communicating IoT devices at scale. Solves secure connectivity (MQTT with TLS and mutual authentication), message routing to other AWS services, per-device state storage (Device Shadows) and fleet management.
When to use Greengrass at the edge?
When latency matters (industrial control, robotics), when there's intermittent connectivity (remote sites, vehicles), when there are regulatory restrictions to process data locally, or when the cost of transmitting to the cloud is prohibitive. Greengrass runs Lambda code directly on the device.
How are thousands or millions of devices managed?
AWS IoT Device Management lets you register, organize, monitor and update massive fleets. Secure OTA (Over-The-Air) updates, logical device grouping, mass jobs and per-fleet health dashboards.
How much does an IoT platform cost on AWS?
AWS IoT Core charges per message and connected device, and Greengrass per active edge device. Cost scales with real telemetry volume and device count. We model it with you in the discovery based on your concrete case. Let's have a conversation to put together a tailored proposal.
Do you do IoT with AI use cases on top?
Yes. The IoT + AI combination is where most value is generated: anomaly detection in sensors with SageMaker or Bedrock, failure prediction, industrial operations optimization. Learn more at /en/services/agentic-ai-aws.
Ready to get started?
Tell us about your challenge. No pitch, no commitment. Just understanding.
Let's talk about your IoT case