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RE:MARK · Active Development Platform

An edge AI system for
automated visual inspection —
running on real hardware,
on real parts.

RE:MARK Inspector is one of the platforms we develop and operate. PatchCore anomaly detection on NVIDIA Jetson, industrial camera, edge-to-cloud telemetry — built and maintained as a working system, not a prototype or a demo.

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Technical questions welcome.
RE:MARK inspector
99.8%
Anomaly detection accuracy
on discrete manufactured components(*)
6 hrs
Operational installation
on existing conveyor
0
Line or process modifications
required
How it works

The architecture below is what runs in production. Every component — edge device, model pipeline, dashboard — has been selected, integrated, and tested on real parts. What follows is the system as built and validated.

01 · EDGE

Camera and AI module

A compact frame — industrial camera, LED lighting, edge device — mounts alongside the existing conveyor. No production downtime during installation.

02 · MODEL

Trains on your own parts

The model learns from 200 images of conforming parts. No defect labelling. No dataset to build. Operational within days of installation.

03 · DASHBOARD

Real-time analytics

Every inspected part generates a record. The cloud dashboard shows defect rate by shift, anomaly map, SPC trends and full traceability for audits.

Frequently asked questions
Our visual inspection requires an NDT Level 2 certified operator. How does the system integrate?
In contexts with NDT Level 2 regulation, RE:MARK Inspector operates as an instrumental support tool for the certified operator — not as a replacement.
The operator examines 100% of parts, as required by the regulation.

The final decision on every part remains with the certified operator, but human error is significantly reduced.

RE:MARK Inspector detects 99.8% of visual anomalies, regardless of fatigue or operating conditions. Combined with certified operator review, it reduces the probability of a defect escaping the overall inspection process by approximately 20x — whatever the operator's baseline detection rate. In a sector where a single escape can have catastrophic consequences, this delta has concrete economic and safety value.
Additionally, every inspection — including conforming parts — is archived with the original image and anomaly map. In the event of a dispute or incident, it is possible to demonstrate the quality status of each individual part at the moment it left the line.
We have no NDT regulation, but production volume makes manual visual inspection unsustainable. Are we a use case?
Yes — this is the second scenario the system is designed for.
On high-volume lines under ISO 9001 or IATF 16949, the requirement is documented 100% production coverage. Manual inspection of every part becomes physically impossible beyond a certain pace, and inspection quality degrades rapidly with operator fatigue.
RE:MARK Inspector inspects every part automatically. The operator intervenes on flagged parts — typically 3–5% of production — with full attention and visual context.
The result is documented 100% coverage with a sustainable operational load, and a complete audit trail for every batch.
Our process uses AQL sampling inspection. Does the system replace it? Do we need to recertify?
No — and this is an important distinction to clarify before any conversation with your certification body.

ISO 9001 and IATF 16949 do not prescribe AQL as a mandatory method: they require that control methods are defined and documented in the Control Plan. The Control Plan is a living document, updatable within normal QMS management — it does not require an extraordinary audit or recertification.

The typical path with RE:MARK Inspector has three phases:

Phase 1 — Pre-inspection addition. RE:MARK is inserted before your existing sampling. The AQL process remains unchanged. Nothing needs updating in the Control Plan: it is an additional step, not a replacement. Sample results improve immediately because they are drawn from an already pre-filtered batch.

Phase 2 — Historical documentation. After 3–6 months you have objective data on system performance: detection rate, temporal distribution of anomalies, correlation with process parameters. This is the documentary basis for any subsequent decision.

Phase 3 — Control Plan update (optional). With data in hand, the quality manager can choose to update the Control Plan to reduce manual sampling frequency, documenting automated inspection as the primary method with periodic sample validation. This is a normal continuous improvement process provided for by the standard — reviewed in the annual surveillance cycle, not with a separate audit.
Our line already has a specific configuration. Do we need to modify it?
No. The aluminium profile frame mounts alongside the existing conveyor — no mechanical modifications, no disruption to the flow. The only precondition is that parts arrive already singulated with predictable orientation, a condition typically already met at CNC exit, after washing, or at the pre-packaging stage.
What does it cost and how quickly does the investment pay back?
The cost depends on the specific configuration — hardware, cloud dashboard subscription, and support. In a free 30-minute assessment we calculate together the expected return based on your production volume, current defect rate, and cost of parts that currently escape inspection. Typically break-even is reached in 3–9 months.

(*) MVTec AD benchmark, single component category, model retrained with augmentation — capability demonstration, not a production statistic.

Technical questions about
machine vision, anomaly detection, or edge AI?

Whether you are assessing a target, evaluating a portfolio company's technology, or facing a regulatory evidence question on a vision-based medical device — a 30-minute call to see if there is a useful conversation to be had.

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Giulio PianaFounder and Principal · RE:MARK giulio.piana@brandcraft.it

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