NeLeSo GmbH · Munich · since 2010

Software for charging infrastructure, energy and Edge AI

We build production platforms for CPOs, fleets, OEMs, energy companies, industrial operators and wallbox manufacturers: OCPP/OCPI, CPMS, OCPP Broker, test automation, Azure, Python and AI-assisted edge operations.

eMobility since 2012 Test lab since 2014 OCPP 1.6 / 2.0.1 Azure · Python · AI

Where customers bring us in

Engineering for the hard parts of charging, energy and industrial operations.

NeLeSo works where product ideas meet field reality and live operations. We build systems that work with real charge points, machines, roaming partners, metering data and existing OT/IT landscapes.

01

Charging platforms

CPMS, OCPP Broker, OCPI/OICP, Hubject integration, digital twins, monitoring and migrations of existing charge parks without a big-bang switch.

02

Wallbox development & testing

OCPP backends, real-world test cases, firmware and configuration validation, load management, ISO 15118 and remote support for complex field issues.

03

Edge AI & Industrial AI

Azure and IoT architectures, time series, edge controllers, energy monitoring and AI that turns operational data into causes, recommendations and local decisions.

Edge AI product line

Local intelligence for critical sites that have to keep running.

Cloud systems are strong in analytics, reporting and fleet control. But critical decisions often belong closer to the asset: where charge points, machines, meters, sensors and controllers actually run. NeLeSo builds Edge AI systems that understand local data, explain incidents and keep operating logic available on site.

Resilient operations Local rules, priorities and decisions stay active, even when connectivity is degraded.
AI-assisted troubleshooting Logs, sensor values, status messages and events become understandable cause chains.
On-site optimization Energy, peak loads, maintenance, availability and process quality are balanced locally.
Edge AI for EV Charging The charging site stays intelligent, even when the cloud is gone. Edge controller, local CPMS, OCPP Broker and AI diagnostics for resilient charging sites. Industrial Edge AI The plant detects incidents and optimizes operations directly on site. Predictive maintenance, plant copilot, energy optimization and OT anomaly detection.
Offline-first Local AI OT/IT integration Brownfield-ready Diagnostics Energy optimization
Check an Edge AI use case
Edge Device EV Charging · Industrial AI · Energy
Charge points Machines Meters Sensors Cloud Sync
Open wallbox with display and wiring in an OCPP test setup

Wallbox development and validation

Tests from real life, not only from the lab.

Since 2014 we have operated test environments with vehicles, wallboxes, metering points and OCPP backends. The result: more than 250 practical test cases for authentication, backend communication, load management, ISO 15118, firmware and operator processes.

  • OCPP test backends and charger simulators
  • Firmware, configuration and rollout validation
  • Field issue analysis and reproducible test scenarios

Proof

Built from projects that already run in production.

Multiple charge points in a load-management test setup

eMobility since 2012

Product definition, software development and rollout support for charging and vehicle data.

Edge controller and lab power supply for energy integration

Energy & Edge

IoT energy monitoring, time series, edge integration and transparent energy data.

Monitoring dashboard for charging infrastructure in test operations

Production operations

Architectures for charge parks, fleets, home charging, roaming, monitoring and reporting.

Insights

Technical articles on Edge AI, OCPP, CPMS at the edge and Industrial AI.

Read insights

How we work

Short path to architecture, fast into the system, clean into operations.

  1. Clarify Make requirements, protocols, operator roles, existing systems and risks visible.
  2. Prototype Validate quickly with Pipelet modules, Azure/Python services or focused custom code.
  3. Launch Include monitoring, DevOps, data models, test automation and migration paths from day one.
  4. Improve Turn operational data into new features, AI assistants and stable processes.