Reduce digital evidence backlogs without compromising information control.
Rigr AI helps police and regulated investigative teams triage extracted evidence from phones, laptops, chat logs, images, video and audio at scale — across on-premise, air-gapped, private sovereign AI, secure private cloud and government cloud deployments.
A sector-wide capacity problem, not a local failure
Phones, laptops and media-rich cases now produce more material than human-only teams can manually review on operational timelines. That pressure shows up as safeguarding decisions, charging timelines, bail decisions and case progression all waiting on a review queue — not as a single team falling behind.
The House of Lords Science and Technology Committee has highlighted that digital forensics backlogs continue to undermine timely justice, and pointed to trusted AI and digital tools as part of the response. Rigr AI is built for exactly that role: a secure triage layer that sits after acquisition and before deep manual review, directing scarce specialist time to the material most likely to matter.
Where Rigr fits
| Stage | What happens | Rigr’s role |
|---|---|---|
| 1. Acquisition / export | Existing forensic tools acquire, extract or export device data. | Rigr does not replace acquisition, unlocking or forensic collection tools. |
| 2. Rigr triage and enrichment | Rigr ingests extracted media, chats, transcripts, images, video and audio, then structures them for search, review and prioritisation. | This is the secure AI triage layer. |
| 3. Human review | Investigators, analysts and digital forensic investigators review priority material, validate outputs and build evidential narratives. | Rigr supports, but does not replace, human judgement. |
| 4. Case progression | Teams export findings, reports and references into downstream case or evidence workflows. | The outcome is earlier leads and better prioritisation, not black-box decisions. |
The capabilities behind stage 2
The triage layer is built from capabilities that can run together inside VST Teams or independently as APIs:
- CSAM detection and severity classification — grades seized imagery so the queue is ordered by severity rather than filename
- Evidence transcription, translation and summarisation — makes interviews, calls and multilingual text searchable, with every summary tied back to its source passage
- AI image geolocation — surfaces the strongest geographic leads across a large image set
- Age estimation — flags apparent minors with calibrated uncertainty for prioritised review
What this means for commanders and forensic leads
Digital evidence queues are not just an analyst problem. Rigr gives teams a faster first-pass map of large evidence sets — prioritising devices, folders, people, locations, dates, faces, entities, transcripts and media — so scarce specialist time can be directed to what’s most likely to matter. This helps improve time-to-first-lead and time-to-evidence while preserving information control: data, outputs and review decisions remain under your organisation’s control throughout.
Final investigative, evidential and legal decisions remain with authorised humans. Rigr’s role is to help trained teams decide what to review first — not to decide evidential relevance or legal status on their behalf.
To see stage 2 and stage 3 in practice, take the Media Classification review tour — a click-through of the real screens showing how a team works down a seized device by severity rather than by filename, and where the analyst’s judgement enters. It runs on sample data; nothing is processed.
See VST Teams for the operational workspace this triage layer feeds into, and Deployment, sovereignty & information control for how it runs inside your environment.
Frequently asked questions
How can AI reduce a digital forensics backlog?
By triaging extracted material before deep manual review rather than replacing that review. Rigr structures media, chats, transcripts, images, video and audio for search and prioritisation, so scarce specialist time goes to the material most likely to matter first — improving time-to-first-lead rather than the total volume held.
Does Rigr replace our forensic acquisition tools?
No. Acquisition, unlocking and forensic collection stay with the tools you already use. Rigr sits at the next stage, ingesting what those tools extract and preparing it for review.
Where does the triage layer sit in the workflow?
After acquisition and export, before deep manual review. Existing tools acquire the data; Rigr structures and prioritises it; investigators review the priority material and build the evidential narrative; findings then export into your downstream case workflow.
Can evidence triage run without sending data to the cloud?
Yes. Rigr deploys on-premise, air-gapped, as private sovereign AI, or in a secure private or government cloud. Data, outputs and review decisions remain under your organisation's control throughout.
Does the AI decide what is evidentially relevant?
No. Final investigative, evidential and legal decisions remain with authorised humans. Rigr helps trained teams decide what to review first; it does not determine evidential relevance or legal status.
What kinds of material can it triage?
Material extracted from phones, laptops and media-rich cases — images, video, audio, chat logs, transcripts and documents — prioritised across devices, folders, people, locations, dates, faces and entities.