We turn sensor data
into decisions.
GFuse designs and ships applied AI — computer vision, sensor fusion, and edge deployment — for teams who need working systems, not slide decks. 10+ years, 40+ engagements, from prototype to production.
Three ways we get you to a working system.
No fixed-scope guesswork — every engagement starts by understanding your data and infrastructure, then builds outward.
Consulting & Development
Custom AI applications built around your data — from a SaaS-hosted model to one running natively on edge hardware. We scope for what your infrastructure can actually support.
Robustness & Deployment
CI/CD pipelines built for continuous delivery, not one-off handoffs. Your model ships, gets monitored, and keeps shipping as data drifts.
Product & Interface Design
The algorithm is half the product. We design and build the application layer around it, so the intelligence is actually usable by the people who need it.
License the engine, not just our time.
Alongside custom engagements, GFuse packages its core sensor-fusion algorithm as a licensable SDK — a drop-in component for teams that don't need a full consulting build.
Sensor Fusion SDK
AvailableReal-time multi-sensor fusion (IMU + camera + LiDAR) for embedded and edge targets. EKF/UKF core with an optional learned correction layer, C++ core with Python bindings.
- ARM / Jetson-class edge deployment, no cloud round-trip required
- Modular sensor inputs — drop in or remove a sensor without a rewrite
- Reference integration + documentation included with every license
Six things we don't compromise on.
Agile delivery
We adapt scope as your data and requirements evolve — not locked into a spec written before we'd seen your problem.
Client-centric
Regular check-ins and honest status reports. You always know exactly where the build stands.
Cross-domain
Sensor fusion, autonomous systems, motion capture, RAG — patterns from one domain regularly solve problems in another.
Applied innovation
New techniques earn their place only once they measurably improve your outcome, not because they're novel.
Quality bar
Every deliverable is held to production standard — tested, documented, and built to hand off cleanly.
Security by default
Edge and cloud deployments are built with data protection and access control considered from day one, not bolted on after.
Technologies we reach for.
Six stages, one continuous line.
Each stage feeds the next — we don't hand off and disappear between them.
Research
Explore your infrastructure and data sources, assess whether there's enough signal to start R&D, and define the metrics that will define success.
Data-flow design
Map how information moves through the system before writing a model — the architecture that determines whether it'll scale.
Development
Build the model and the application around it in parallel, so neither is designed in isolation from the other.
Testing
Verify the system does what it's meant to, under the conditions it'll actually see — not just on a clean validation set.
Deployment
Move from a controlled environment into production — on your cloud, your edge devices, or both.
Support
Ongoing technical support as data drifts and requirements change — the system keeps working after we ship it.
What it's like to work with us.
Led by Majid Geravand — AI & Computer Vision Engineer
M.Sc. Artificial Intelligence & Robotics, Sapienza University of Rome. 10+ years across research, sensor fusion, and applied AI delivery.