
AI systems that see, decide and act.
Bluepolicy builds production-ready AI — from computer vision and energy platforms to agentic automation — designed for real operations.
- From PoC to production deployment
- Edge + cloud architectures
- Architecture & quality: Germany-led, delivered by our global team
AI for real-world use.
Automation that works. Engineered in Germany.
MeruX
Clean billing for home charging – automatic, kWh-precise, audit-ready.
- Auto-assignment: Car / User / Guest
- Monthly PDF for HR/Finance
- No meter photos, no Excel
Craftfluence
Get locally visible: AI turns job photos into posts, stories, and Google updates – automatically.
- Connect: Instagram, Facebook, Google Business Profile
- AI writes in your tone including call-to-action
- Plans & publishes – no marketing know-how needed
JamDetect
Detects jams, blockages, and snags on conveyor belts in real-time – via camera and AI directly at the edge.
- Output: Jam events per zone incl. timestamp & snapshot
- Integration: REST, MQTT, OPC UA, Modbus TCP, digital I/Os
- Benefit: fewer downtimes, faster response, transparency
Built from practice, not slides
Built from practice, not slides.
Practical Roots
Founded by a trained craftsman — we understand real workflows, machines and constraints.
Grounded in Germany
Founded in Siegburg, Germany — reliable delivery and long-term thinking.
Enterprise DNA
Enterprise DNA — engineered for regulated environments and resilient production systems.
Technology Partners




Our Team
The neural network behind the innovation.

Jens Schneider
Founder & Managing Owner

Chantal Schneider-Reifert
Sales Manager

Krishna Sharma
AI Product Manager

Neeraj S J
Senior ML Engineer

Gireesh B M
Senior Tester

Prashanth D
Senior Dev-ops Engineer

Rakshith N
Senior ML Engineer

Latest Insights
Updates from the Bluepolicy team.
2. Januar 2026
Meru: Revolutionizing Electric Vehicle Charging for Corporate Fleets
Transform your fleet management with Meru, the app that streamlines EV charging, automates reimbursements, and simplifies tax reporting.
Estimated reading time: 6 minutes
As the transition towards electric vehicles accelerates, companies are seeking efficient solutions to manage their fleets effectively. Meru, a Germany-based EV charging application, emerges as a game-changer, offering a streamlined approach to charging for company cars. By automating the compliance process with Germany's new reimbursement regulations, Meru simplifies the complexities of charging management and empowers both employees and employers with precise documentation and ease of use.
The Need for Streamlined EV Charging Solutions
In a rapidly evolving automotive landscape, electric vehicles (EVs) are becoming a staple in corporate fleets. However, this shift presents challenges, particularly in managing the operational costs associated with charging. Company car users often find themselves dealing with the hassle of reimbursement for charging costs, which can become a tedious manual process. This is where Meru steps in, providing a robust solution that not only simplifies charging but also ensures compliance with regulatory requirements.
Automatic Cost Tracking and Compliance
Meru's core functionality lies in its ability to track wallbox charging sessions automatically. By integrating with MID-certified meters and leveraging vehicle-integrated displays, the app ensures that every kilowatt hour (kWh) consumed is accurately documented. This level of precision is crucial for calculating actual electricity costs based on individual tariff rates. With the increasing complexity of electricity pricing, especially as dynamic tariffs gain traction, Meru's capacity to manage receipt documentation seamlessly is invaluable.
Comprehensive Reporting for Employees and Employers
One of the standout features of Meru is its capability to generate tax-compliant monthly reports. For employees, this eliminates the need for lengthy calculations and paperwork when submitting expenses. For employers, it provides a centralized fleet management resource that integrates seamlessly with payroll systems. This feature not only saves time but reduces the administrative burden, allowing HR and finance departments to focus on strategic initiatives instead of mundane data entry tasks.
Supporting Dynamic Electricity Pricing
As dynamic electricity prices become more common, Meru accommodates these shifts by managing receipts effortlessly. Users receive real-time updates on the cost of charging based on current rates, ensuring that the expenses reported are reflective of actual consumption costs. This adaptability makes Meru a forward-thinking choice for forward-thinking companies looking to enhance their EV charging strategies.
Real-World Impact of Meru
Consider a medium-sized enterprise in Germany with a significant fleet of electric vehicles. Without a solution like Meru, employees might face difficulties in documenting their charging sessions and reconciling costs for reimbursement. By implementing Meru, the company can streamline its operations, reduce inaccuracies in expense reporting, and improve employee satisfaction. This results in a more efficient fleet management system that aligns with corporate sustainability goals.
Conclusion
Organizations that embrace solutions like Meru are not just adhering to compliance; they are positioning themselves at the forefront of the EV revolution. As the infrastructure for electric vehicles continues to develop, Meru reflects a commitment to innovation, efficiency, and sustainability in fleet management. Companies implemented Meru can expect not only simplified processes but also empowered employees who can focus on delivering value rather than navigating bureaucratic hurdles.
Tags: Electric Vehicle Management, Fleet Management, Corporate Sustainability, EV Charging Solutions, Compliance Automation
29. Dezember 2025
Edge AI – Intelligence at the Camera
In a world demanding real-time responses and data sovereignty, Edge AI is becoming essential. Moving intelligence directly to the data source – the camera – is revolutionizing industrial applications.
Edge AI by the Numbers
<10ms latency vs. 100-500ms cloud | 100% local data processing | 90% reduced bandwidth
Why Edge AI?
- Real-time Processing: Milliseconds instead of seconds response time
- Data Privacy: Sensitive data never leaves the premises
- Cost Efficiency: No cloud fees, minimal bandwidth requirements
- Reliability: Works offline – no internet dependency
Leading Edge AI Platforms 2025
NVIDIA Jetson Family
Jetson AGX Orin: Up to 275 TOPS, 15-60W power
Jetson AGX Thor: 2,070 FP4 teraflops, 128GB memory
Best for: Multi-camera systems, robotics, industrial automation
Google Coral
Edge TPU: 4 TOPS at only 2W power consumption
Best for: Low-power IoT, battery-operated devices
Intel OpenVINO + NCS2
Myriad X VPU: Flexible model optimization
Best for: Retrofitting existing x86-based infrastructure
Edge AI at bluepolicy
Our edge solutions deliver the best of both worlds:
- Hybrid Architecture: Real-time inference locally, complex analytics in the cloud
- Over-the-Air Updates: Update models remotely without on-site visits
- Model Optimization: Quantization and pruning for maximum performance
- Industrial Housing: IP67-rated enclosures for harsh environments
Typical Savings with Edge AI
90% less bandwidth | 60% lower cloud costs | 95% faster response
Edge AI for Your Project
We help you select optimal hardware and develop custom edge solutions.
29. Dezember 2025
Vision Language Models – When Computers See AND Understand
The boundaries between Computer Vision and Natural Language Processing are dissolving. Vision Language Models (VLMs) mark a paradigm shift: from simple object detection to genuine image understanding.
The Difference
Classic CV: "Object detected: screw"
VLM: "M8 stainless steel screw with damaged threading on the third turn, likely caused by over-torquing."
What Makes VLMs Different
VLMs combine three core components to handle visual tasks through natural language:
- Visual Encoder: Processes images into meaningful representations
- Language Model: Understands queries and generates human-readable responses
- Fusion Layer: Bridges visual and textual understanding
Leading VLMs in 2025
GPT-4.1 / GPT-4o
Improved analysis of charts, diagrams, and visual mathematics
Best for: Real-time multimodal analysis, enterprise applications
Claude 3.5 Sonnet
Exceptional precision in visual descriptions
Best for: Technical documentation, detailed inspections
Gemini 2.0
Native video understanding and temporal reasoning
Best for: Video analysis, motion detection, process monitoring
LLaVA-NeXT / Qwen2-VL
Open-source models for on-premise deployment
Best for: Data-sensitive applications, air-gapped environments
Industrial Applications
At bluepolicy, we integrate VLMs for:
Quality Control
Clear descriptions: "Surface scratch (12mm length, 0.3mm depth), upper right quadrant. Severity: Medium. Recommendation: Re-polish."
Safety Monitoring
Context-aware analysis: "Person entering restricted zone. No safety vest detected. Warning triggered."
Discover VLM Capabilities
See how Vision Language Models can transform your image analysis.