What We Can Do For You

Computer vision services for product and solution developers, technology providers, integrators, and OEMs building embedded vision & Edge AI products.

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Typical Problems We Solve

It works in a PoC, but not on the target device

Vision PoC vs target hardware

A computer vision or embedded vision pipeline performs well in a controlled setup, but still has to run reliably on the actual camera, module, or embedded target. The harder work begins when Edge AI has to survive real device limits, runtime behaviour, and product-level integration. This is where embedded vision deployment becomes a vision system problem, not only a vision model problem.

The platform may not fit the vision workload

Hardware fit

The team is unsure whether the chosen platform can support the full computer vision workload across sensor throughput, image processing, inference, and surrounding system load. What looked viable in isolation may break under real compute, memory, power, and thermal constraints. That is often the deciding question in Edge AI hardware assessment for computer vision projects.

The vision stack breaks under production constraints

Production constraints & embedded plumbing

Latency, thermal drift, pipeline instability, or embedded bottlenecks start showing up once the system moves beyond the demo. Machine vision and embedded vision systems often need more work around runtime fit, buffering, integration, and robustness before they are ready for field use. In practice, this is the gap between a promising machine vision prototype and a rollout-ready vision system.

The device needs stronger maintainability and resilience

Maintainability / security

The product needs clearer update paths, better lifecycle reliability, and connected-device security that can hold up after launch. For embedded vision and Edge AI products, that often means stronger updateability, better vulnerability handling, and work around CRA-related readiness. For connected vision products, security and maintainability increasingly shape whether the system remains viable after release.

Feasibility & Discovery

Early work around constraints, use-case assumptions, hardware fit, integration risk, and delivery planning.

Hardware-Fit Benchmarking

Benchmarking target platforms to see whether the vision workload fits the device, not just the demo setup.

Embedded Deployment

Getting vision workloads onto target hardware and putting the surrounding system pieces in place.

PoC Rescue

Helping teams that have something working in prototype form but are stuck before a usable deployment path emerges.

Optimization & Productionization

Improving latency, thermal behavior, power use, and robustness before field rollout.

System Validation & Field Readiness

Testing, validation, and issue resolution work that helps embedded vision and Edge AI systems behave predictably outside the demo setup.

CRA & Cyber Resilience

Readiness work for connected vision devices, including remediation planning and vulnerability-handling workflows.

Connected Device Backbone

Work around connectivity, updateability, lifecycle reliability, and long-term maintainability.

Industries We Build For

AI Camera Solutions & Vision Devices

Camera products and vision-enabled devices that need on-device inference, stable pipelines, and fit for the target platform.

Physical Security & Access Control

Biometric access terminals where latency, privacy, and device constraints all matter at once.

Drones & UAV Systems

Edge vision for unmanned platforms where weight, performance, power consumption, and response time leave little room for waste.

Agriculture Technology

Connected vision systems for monitoring and automation in greenhouses, farms, and controlled growing environments.

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Our Expertise

Embedded Vision Platforms

Practical implementations of computer and machine vision workloads for embedded vision platforms, utilizing Ambarella, Hailo, NXP, and Rockchip SoCs.

Sensor to Decision Pipeline

Low-level sensor and platform work across driver integration, calibration, ISP tuning, BSP development, as well as model porting and optimization for embedded vision systems.

On-Device Inference

Porting and optimizing ML learning models. Getting Edge AI workloads to run efficiently on constrained devices

Performance & Productionization

Optimizing behavior, quality, latency, power, and heat dissipation before the product reaches the field.

Connected Vision Security

Implementing security features and supporting certifiability for connected vision devices.

Device Integration & Maintainability

Device management: firmware updates, remote updates, configuration management, version management, life-cycle management etc.

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Engagement Models

Development and Integration

Accelerate your product development with Expert Edge AI and Embedded Systems Engineering. Shorten time-to-market, reduce development risks and scale from prototype to production with confidence.

Consulting

Consult your technical product strategy, develop roadmaps, and research technology feasibility with our team of seasoned experts. Prototype, validate, and ensure security by design from the very beginning of your project.

Talent Support

We will help you find the right talent to build your vision system. This includes executive search, as well as interview support and technical assessment.

Why Teams Start With Us

Make It Work on the Edge

Your models hit their targets on a GPU but run too slow, too big, or too inaccurate on the embedded SoC. We quantize, port, and optimize them as well as integrate the entire firmware stack from board support to application until it's production-ready.

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Make It Work on the Edge

Get There in Time

A trade show, pilot, or investor demo won't move, and your team is already stretched. Hiring and ramping up new embedded vision engineers takes months. Our senior and well-integrated engineering team can contribute to your roadmap from week one.

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Get There in Time

Get It Market Ready

Picking the wrong platform can cost a year, a failed certification delays revenue, and a prototype that works on a desk isn't a product. We help you choose the right hardware, implement your solution, and pass certification, thus turning your prototype into a robust, manufacturable device.

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Get It Market Ready

Let’s Build Something Great Together

No matter the size or complexity of your project, our team is ready to provide the right solutions for your business needs

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Our Partners

iENSO

iENSO is an Edge AI company specializing in computer vision solutions built on Ambarella. iENSO helps OEMs and product teams accelerate the deployment of AI-enabled vision systems.

Together, we bridge the gap between model development and embedded deployment, enabling customers to move from prototype to production faster, with solutions optimized for performance, power efficiency, and regulatory requirements.

www.ienso.com

Blues

Blues is a secure, cloud-connected IoT infrastructure provider that simplifies how physical products connect to the internet.

As a partner to Estigiti, Blues provides the connectivity and cloud layer that complements our embedded and Edge AI expertise. Together, we enable end-to-end IoT systems - from secure device firmware and AI at the edge to resilient cloud integration.

blues.com

Flexsolution

FlexSolution develops custom embedded hardware and software for industrial products, with experience across sensor integration, IoT platforms, cloud connectivity, and connected-device security

As Estigiti’s partner, FlexSolution strengthens the hardware and embedded engineering side of projects where vision and Edge AI are part of a broader connected product. Together, we can cover the path from device electronics and firmware to vision workloads, connectivity, and cloud integration.

flexsolution.dk

our partners