Embedded AI & Computer Vision for Real-World Devices

We build and deploy end-to-end embedded Computer Vision and Edge AI, combining hardware design, firmware development and optimized AI models running on production devices.

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No sales pitch. Just a technical call.

Trusted by edge ecosystems

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Our key
to success

1

Feasibility study in 3 weeks

We validate your idea. with a detailed report.

2

End-to-end delivery

From hardware architecture and firmware development to optimized AI deployment on production devices.

3

Real-time on edge

We extract full potential of the hardware.

4

One roof

Our hardware, firmware and AI teams collaborate closely to deliver fully integrated production-ready systems.

1

MVP in 3 weeks

We ship a working edge MVP in 3 weeks - unless your device is truly cursed. Then we ship it anyway.

2

End-to-end delivery

We cover whole process from hardware design, firmware development, and model deployment.

3

Real-time on edge

We build models that extract full potential of your hardware.

4

One roof

Our hardware, firmware and AI teams, work together hand in hand. No handoffs. No vendor juggling.

Our key to success

1

MVP in 3 weeks

We ship a working edge MVP in 3 weeks - unless your device is truly cursed. Then we ship it anyway.

2

End-to-end delivery

We cover whole process from hardware design, firmware development, and model deployment.

3

Real-time on edge

We build models that extract full potential of your hardware.

4

One roof

Our hardware, firmware and AI teams, work together hand in hand. No handoffs. No vendor juggling.

WHAT WE DO

We deploy Embedded AI. Not demos.

Embedded Computer Vision

Real-time detection, tracking, and segmentation on edge devices

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Embedded Computer Vision

Real-time detection, tracking, and segmentation on edge devices

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End-to-End Deployment

Hardware + firmware + AI. One team. One delivery

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End-to-End Deployment

Hardware + firmware + AI. One team. One delivery

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On-device LLMs

Run language models on edge devices - locally for privacy and offline workflows.

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On-device LLMs

Run language models on edge devices - locally for privacy and offline workflows.

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Industries we serve

Robotics

Edge perception for robots that move in unpredictable environments.

Retail & Smart Stores

Vision for checkout, shelves, and store ops - on-device.

Industrial / Manufacturing

Quality, safety and automation that runs on the edge.

Automotive

Real-time perception and driver monitoring - built for embedded.

Smart Cities & Security

Tracking and analytics without cloud dependency.

Logistics / Warehousing

Sort, track and monitor goods at the edge.

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TECHNOLOGY / PRODUCTS (READY TO DEPLOY)

Built faster with NeuralSpike Products

We use our Toolbox and Frameworks to ship faster and better products.

Model optimization toolbox: quantization / pruning / compression.

Deployment-ready approach (edge constraints first).

Explore products

Proof, not promises.

Real-time segmentation on edge - faster, smaller, more precise.
Robotic vision that doesn’t break in real-world conditions.
Checkout without barcodes. Shelf insights without delay.

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Feasibility study in 3 weeks

We validate your edge AI on your target device - with measurable performance.



What you get:

Benchmark sheet (FPS / latency / memory)

Demo running on-device

Integration plan (firmware + deployment)

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Get a benchmark estimate

Got a device. Got constraints. Let’s ship it.

Got a device. Got constraints. Let’s ship it.

Talk to an Engineer

Request Feasibility Review