MultiSensor AI · Industrial IoT & AI
AI-Powered Condition-Monitoring Platform
Application development and integrations for a platform combining thermal, visual, acoustic and vibration sensor data with AI, edge and cloud, connected to PLC, DCS, SCADA, CMMS, BMS and EAM systems.
Project Snapshot
- Client
- MultiSensor AI
- Project
- AI-Powered Condition-Monitoring Platform
- Engagement
- Software Engineering · Application Development · Integrations
- Data handled
- Industrial sensor, asset, and operational data
Technology & Integrations
- Thermal sensors
- Visual sensors
- Acoustic sensors
- Vibration sensors
- AI
- Edge computing
- Cloud
- PLC
- DCS
- SCADA
- CMMS
- BMS
- EAM
- Sites
- 100+
- Implementation
- 6–8 wks
- ROI over 5 years
- Up to 8×
The Starting Point
Where the product started
MultiSensor AI was an emerging technology company focused on transforming industrial monitoring through AI and multi-sensor technology. Its condition-monitoring platform combines sensor data, AI, edge computing, and cloud technologies.
Codeinity Solutions became involved to provide software engineering support, working alongside MultiSensor AI's product and engineering teams to develop and enhance the digital platform as it evolved.
The platform was being designed for enterprise-scale operations. That meant software able to handle diverse sensor types and connect with the enterprise systems industrial customers already rely on.
The Problem
The challenge wasn't just building it
The key challenge was handling diverse sensor data at scale while maintaining reliable, real-time monitoring. Industrial customers depend on continuous data availability, so the platform had to keep pace with both the scale and the complexity of what it monitored.
- 01
Diverse Sensor Data
Thermal, visual, acoustic, and vibration sensors, all feeding one platform.
- 02
Enterprise Scale
A platform designed for enterprise-scale operations, now deployed across 100+ sites.
- 03
Real-Time Reliability
Monitoring that stays reliable and real-time, with continuous data availability.
- 04
System Integration
Connecting sensors with enterprise systems including PLC, DCS, SCADA, CMMS, BMS, and EAM.
- 05
Continuous Evolution
A platform that keeps developing, with enhancements delivered alongside MultiSensor AI's teams.
The Codeinity Response
How we approached it
Codeinity worked alongside MultiSensor AI's product and engineering teams, providing software engineering expertise across application development, integrations, and platform enhancements.
The central problem was handling diverse sensor data at scale without losing real-time reliability. The focus was on scalable integrations and software capabilities that support continuous data processing and deliver actionable insights.
Application Development
Software engineering for the AI-powered monitoring platform.
Sensor & System Integration
Thermal, visual, acoustic, and vibration sensors, plus PLC, DCS, SCADA, CMMS, BMS, and EAM systems.
Scalable Data Processing
Software capabilities built for continuous data processing.
Real-Time Monitoring
Reliable, real-time visibility across sensor streams.
Platform Enhancement
Ongoing development as the platform evolved.
Actionable Insights
Monitoring data turned into insight teams can act on.
The Impact
What changed
- Sites
- 100+
- Deployed across 100+ sites, supporting large-scale industrial monitoring
- ROI over 5 years
- Up to 8×
- Return on investment reported across deployments
- Payback
- 2 months
- Payback in as little as two months
- Implementation
- 6–8 wks
- Typical platform implementation, from kickoff to full deployment
Payback, ROI and deployment figures are reported by MultiSensor AI and describe platform-level outcomes across its deployments, not results attributable to a single scope of work. The business goal: reducing unplanned downtime and improving asset reliability.
Client Perspective
“Codeinity Solutions has been a reliable technology partner throughout our development journey. Their technical expertise, responsiveness, and ability to deliver scalable solutions helped us move faster and continuously improve our platform.”
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