World-leading, deep learning video privacy and analytics platform

Pimloc uses the latest machine learning and computer vision approaches to train its algorithms to recognise personal identifiable information (PII) in a wide variety of image and video scenes. They recognise the identifiers (such as faces, heads and number plates) as a human observer would, to redact / anonymise and classify the information automatically.

Pimloc’s technology can be deployed selectively, so it can remove some or all faces, and/or all vehicle registration details, or other identifying information. It has been trained to perform on low definition visual content, meaning Pimloc’s products can deal with a large diversity of CCTV and other video surveillance data.

As a result, video clips that have been anonymised with Pimloc’s technology can be used for a variety of purposes - with employees, customers, corporate insurance companies, law enforcement and lawyers, all while staying compliant with data privacy laws and regulations.

“Automated anonymisation is the only way to keep up with changing privacy legislation and to responsibly unlock the value of aggregated video data for business operations.”

Simon Randall, CEO

An hour of CCTV can contain upwards of 2 million faces. Manually redacting every image of personal data from every frame of a video is time-consuming, mundane and a difficult task that requires considerable attention to detail and can take compliance managers days or even weeks to complete for even a few minutes of video. Protecting all personal data in video by default allows businesses to stay compliant whilst sharing video content internally or with third parties.

Pimloc has created AI models that provide accurate detection and redaction in the most challenging circumstances. This means creating deep learning algorithms that have been trained to detect faces, heads and number plates across domain-specific video from CCTV, body-worn cameras and road survey video footage.

With Pimloc’s AI, the task of redaction can be completed 200x faster - enabling companies to be far more efficient and accurate when it comes to anonymising video footage, and opening up new opportunities for its use.

Responsible video management

Pimloc’s capabilities are currently being deployed across a range of sectors, including: transport, public safety, telehealth, insurance, retail, policing and local government.

Automated, selective
video redaction

Automatically blur faces, heads and number plates in video streams and batch files, at scale for incidents and data compliance.

Manage your video compliance workflow via redacted live and captured video sharing, with encrypted storage options - enabling secure collaborations with 3rd parties.

Secure video storage
and sharing

Capture high quality video metadata (people/vehicle counting in active zones, direction flows, movements and more) for wider video analytics and responsible monitoring.

Video metadata

Generate alerts from live video feeds based on video activity - react quickly and easily to potential issues and keep people and physical locations secure.

Anonymised live alerts

Run analytics on top of anonymised video meta data to understand more about behaviours and people flow (people/vehicle counting, loitering etc).

Video analytics

Secure Redact detects and anonymises over 99% of identifiable PII in security video. Our approach to PII detection is less sensitive to facial occlusion and change than normal detection systems - it performs equally well for people with facial hair, masks, glasses and other coverings.