FehrWatch

FehrWatch

Fehr Algorithmus
MindSafe

MindSafe

Atlantix Global
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+

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About

FehrWatch (Fehr Algorithmus) is a specialized B2B workflow and analysis system built for used IT infrastructure, ITAD operations, and electronics refurbishers. It focuses on the operational intake process — stabilizing, automating, and accelerating device check‑ins, valuation, and pricing decisions at the bench. Core capabilities include automated residual value calculation from Excel batch lists, camera‑based label and serial capture, risk and compliance checks, auditable data‑erasure verification signals, and full stock and batch management. Designed as a high‑performance intake engine, FehrWatch eliminates slow manual data entry, reduces pricing errors, and delivers ultra‑fast processing speeds for warehouse and refurbish environments.

About

When it’s time to retire your IT hardware there’s an entirely new risk to your data. Don’t overlook this critically important step in any IT project. We safeguard your data with our leading-edge erasure and destruction services that meet the most rigorous industry standards. Atlantix employs the industry’s largest team of technical engineers to handle your data security needs. With expertise across all major platforms and manufacturers (Dell EMC, NetApp, HPE, IBM, Cisco, and more), we deploy a compliant sanitization protocol without degrading the value of your IT assets. Atlantix evaluates your assets and determines the best course of action, data erasure, degaussing or shredding. Our process includes a full audit and tracking through serial number capturing to ensure your products are secure. MindSafe erasure services are performed when your products are in good condition and considered as equipment for reuse, redeployment, or remarketing.

Platforms Supported

Windows Supported
Mac Supported
Linux Supported
Cloud Supported
On-Premises Supported
iPhone Not Supported
iPad Not Supported
Android Not Supported
Chromebook Supported

Platforms Supported

Windows Not Supported
Mac Not Supported
Linux Not Supported
Cloud Supported
On-Premises Not Supported
iPhone Not Supported
iPad Not Supported
Android Not Supported
Chromebook Not Supported

Audience

ITAD companies, IT infrastructure refurbishers, re-commerce businesses, circular economy enterprises, and B2B used-hardware procurement teams.

Audience

Enterprises, professionals and anyone seeking a solution for keeping their data secure and protected

Support

Phone Support Supported
24/7 Live Support Supported
Online Supported

Support

Phone Support Supported
24/7 Live Support Supported
Online Supported

API

Offers API Not Supported

API

Offers API Not Supported

Screenshots and Videos

Screenshots and Videos

Pricing

$1499/month
€1499/month 1500requests
€4999/month 6000requests
€4999/monath OCR-camera
enterprise on Request
Free Version Not Supported
Free Trial Supported

Pricing

No information available.
Free Version Not Supported
Free Trial Not Supported

Reviews/Ratings

Overall 0.0 / 5
ease 0.0 / 5
features 0.0 / 5
design 0.0 / 5
support 0.0 / 5

This software hasn't been reviewed yet. Be the first to provide a review:

Review this Software

Reviews/Ratings

Overall 0.0 / 5
ease 0.0 / 5
features 0.0 / 5
design 0.0 / 5
support 0.0 / 5

This software hasn't been reviewed yet. Be the first to provide a review:

Review this Software

Training

Documentation Supported
Webinars Not Supported
Live Online Not Supported
In Person Supported

Training

Documentation Supported
Webinars Supported
Live Online Not Supported
In Person Supported

Company Information

Fehr Algorithmus
Founded: 2026
Germany
www.fehrwatch.de

Company Information

Atlantix Global
United States
www.atlantixglobal.com/data-security/mindsafe-data-security/

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Categories

Categories

Data Security Supported

Integrations

Azure NetApp Files Not Supported
Cisco ACI Not Supported
Dell EMC Avamar Not Supported
HPE Cloud Volumes Not Supported
IBM Cloud Not Supported

Integrations

Azure NetApp Files Supported
Cisco ACI Supported
Dell EMC Avamar Supported
HPE Cloud Volumes Supported
IBM Cloud Supported
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