Efficiency is the research problem
Power, memory, and latency are design constraints, not a later optimization pass.
UPDATE Initial MVP runs entirely on CPU
UPDATE TRL 5 reached for MSHI and T-SUVI
UPDATE Presenting at SLM Workshop 2026 · NeurIPS Satellite, Paris
UPDATE Initial MVP runs entirely on CPU
UPDATE TRL 5 reached for MSHI and T-SUVI
UPDATE Presenting at SLM Workshop 2026 · NeurIPS Satellite, Paris
Heysuvi Labs
Heysuvi GreenAI
Energy-efficient edge AI and on-prem multimodal AI for private infrastructure and local CPU inference, measured against power, latency, and operating constraints. GreenVision for industrial edge vision. GreenAI for multimodal AI without a discrete GPU.
FocusEnergy-efficient inference
SurfacesEdge · ARM CPU · On-prem
ProductsGreenVision MVP 2.1.0
GreenAI MVP 2.1.0
GreenAI MVP 2.1.0
StatusTRL 5
CPU-only path on Raspberry Pi 5 with M.2 storage.
Deployment is the evaluation
Models are judged on constrained devices and private infrastructure.
Architecture first
GreenVision and GreenAI are designed around constrained hardware from the first decision.
Open where it should be
GreenAI is intended for broad release beyond large compute budgets.
Heysuvi GreenAI
Product line
| Product | Primary Role | Use Cases | Deployment | Properties |
|---|---|---|---|---|
| GreenVisionEmbedded edge vision · TRL 5 | Object recognition where latency, power, and hardware limits define the product | Factories · warehouses · field devices · cameras · robots · OEM | ARM Cortex CPU · industrial edge · no discrete GPU | Fast class updates · deterministic |
| GreenAIMultimodal AI · TRL 5 | Efficient multimodal AI for private workflows on practical hardware | Streaming chat · private enterprise AI · air-gapped multimodal · local inference | On-prem · CPU-only · public release planned | Energy-efficient multimodal · CPU-only |
Operating principles
Built around the constraints of the machine.
Hardware limits, local updates, private inference, and predictable behavior are the specification.
GreenVision for environments where latency, power, and hardware constraints define the deployment.
Cameras, robots, warehouses, industrial nodes, and OEM devices. Local inference on efficient hardware.
Fast updates without full retraining
New classes enrolled locally instead of restarting the training cycle.
Deterministic and traceable inference
Operational control and auditability as product requirements.
GreenAI for local and air-gapped workflows
Private multimodal without external cloud APIs for every request.
Efficient hardware over oversized assumptions
Useful inference on practical systems and constrained hardware.
Broader access to efficient multimodal AI
Public release so GreenAI reaches more teams and real deployments.
Deployment surface
Where the systems are meant to run.
Local inference, hardware efficiency, and operational control from the first design decision.
On-prem enterprise AI
Banks, hospitals, governments: sensitive workflows that cannot leave controlled infrastructure.
Industrial & warehouse
Edge vision where latency, auditability, and constrained hardware are the reality.
Edge & field devices
Cameras, robots, drones, sensors, and OEM systems at the edge.
Low-infrastructure
Affordable local AI for low-infrastructure environments.
FAQ
Frequently asked questions
What is Heysuvi Labs?
A research lab building energy-efficient AI for edge, private infrastructure, and local inference. Our product family is Heysuvi GreenAI.
What is Heysuvi GreenAI?
The Heysuvi product family for sustainable, deployment-first AI: GreenVision for edge vision and GreenAI for multimodal AI.
What is GreenVision?
Edge vision for factories, warehouses, service teams, field devices, cameras, robots, and OEM hardware.
Can GreenVision run without a GPU?
Yes. Designed for ARM Cortex CPU cores, with no discrete GPU in the deployment path.
What is GreenAI?
An energy-efficient multimodal AI model that runs entirely on CPU for private workflows, streaming chat, and local inference.
How can I collaborate?
Use Collaborate on this page to open our partner form. US operations in Orlando, Florida.
Collaborations
Bring a deployment constraint. We will tell you which of our models fits best. Tailored model only for your device.
Enterprises, OEMs, and research groups working on edge vision or private multimodal inference.