Skip to solutionCurrent approach Operational impact 
Big world.
Smart Meter Data Management Systems (IoT + Python Pipelines)
Build scalable smart meter data management systems using IoT and Python. PySquad enables utilities and enterprises to process, analyse, and visualise high-frequency energy data.
Built around your operation
- Utility companies managing smart meter networks
- Energy providers handling large-scale consumption data
- Grid operators monitoring load and performance
The business case
Reduced manual effort through automation
Early detection of anomalies and system issues
Scalable platform handling large data volumes
Results depend on scope, integrations and adoption.
The operating context
A clearer view of the whole operation.
Smart meters generate continuous streams of energy data across grids, buildings, and industries. To extract value from this data, businesses need systems that can handle real-time ingestion, ensure data quality, and support large-scale analytics without breaking under volume.
Where friction builds
High-volume meter data becomes unusable without structure
Organizations struggle to process massive volumes of smart meter data due to inconsistencies, missing readings, and limited system scalability. Without proper pipelines, billing becomes inaccurate, anomalies go undetected, and operators lack visibility into consumption patterns and system health.
- Storing raw meter data without proper validation
- Handling data processing manually or in batches
- Using systems not designed for time-series data
- Limited integration with billing and analytics tools
- Inaccurate billing due to poor data quality
- Delayed detection of anomalies or faults
- System performance issues at scale
- Limited operational visibility and insights
Inside the solution
The capabilities behind the operation.
Review the functional scope, then discuss the requirements specific to your team.
Real-time data ingestion
Collect high-frequency data from IoT gateways and meter networks
Python data pipelines
Clean, validate, and transform data using scalable ETL processes
Time-series storage
Store and manage large volumes of meter data efficiently
Analytics dashboards
Visualize consumption trends, peak demand, and system health
Anomaly detection
Identify abnormal usage, faults, or tampering using ML models
System integrations
Connect with billing, ERP, and grid management platforms
From requirements to implementation
Grounded in the way your team works.
How we work- 01
Understand data sources, volume, and operational needs
- 02
Design scalable ingestion and processing architecture
- 03
Build pipelines for validation, transformation, and storage
- 04
Enable analytics, alerts, and system integrations
Our approach
We design end-to-end data platforms that ingest, clean, process, and analyze smart meter data in real time. Our systems focus on reliability, scalability, and turning raw data into actionable insights for operators and businesses.
Make an informed decision
Is this the right fit?
The right solution starts with the right operating requirements.
Check the fit with usDesigned for
- Utility companies managing smart meter networks
- Energy providers handling large-scale consumption data
- Grid operators monitoring load and performance
- Enterprises optimizing energy usage across facilities
- IoT platforms dealing with high-frequency data streams
May not be suitable for
- Businesses without high-volume data requirements
- Teams looking for simple reporting tools only
- Projects without IoT or real-time data integration
- Systems that do not require scalable data pipelines
Trusted by clients worldwide
See it on your workflows
Discuss your requirementsWalk through the solution with your operation in mind.
Before you decide
Questions worth asking.
Ask something elseWhich smart meter communication protocols do you support?
MQTT, Modbus, LoRaWAN, DLMS/COSEM, REST APIs, and custom gateways.
Can the system process millions of readings per day?
Yes. Our time-series architecture is built for horizontal scale.
Can this integrate with billing or ERP software?
Absolutely. We provide APIs for seamless system integration.
How do you handle missing or faulty data?
We apply validation rules, ML-based estimation, and anomaly tagging.
Do you support both cloud and on-premise deployments?
Yes. We offer flexible deployment options based on regulatory needs.
Start with your requirements
Let’s define your next step.
Tell us what needs to work better, the systems you use, and the scope you have in mind.
Discuss your requirementsShare your requirements through our enquiry form.A little closer, wherever you are
Big world.
Close partnership.
Good work travels. We bring product engineering, AI and Odoo ERP to the conversation, and make room for your way of working.
01 / BaseAhmedabadIndia, remote
02 / ApproachOne shared planDiscovery to delivery
03 / ConnectionBuilt around youAgreed meeting rhythm