Text & Audio Summarisation
Overview
A single case can hold hundreds of thousands of messages, transcripts, and screens of text. Finding the ones that matter early — not months in — can change its outcome.
Rigr AI’s Text & Audio Summarisation capability securely condenses transcripts and on-screen text — across languages — into concise summaries suitable for rapid triage and evidential preparation.
When AI Invents the Answer
There are two ways a machine can summarise, and each has a hard limit.
Extraction lifts sentences straight from the source. Every word is the original, exactly as it was written or spoken — so you can trust it absolutely. The drawback: the source may never have stated, in any single passage, the precise thing you need to know.
Abstraction writes a fresh summary in its own words. It can answer your question directly, draw together threads from across a long document, and render the answer in a language other than the original. The drawback: those words are generated by an AI model, and models can hallucinate — so a fluent, confident summary may have no basis in the source material.
A Fast Answer You Can Check
The latest version of our Summariser gives you an abstract — a direct, readable answer in plain language, across languages where needed — and backs every claim with an extract from the original text.
When the abstract is right, you have a fast answer. When it draws the wrong conclusion — and any abstractive system sometimes will — the supporting extract sits right beside it, in the source’s own words. The reviewer always sees both, so a flawed conclusion can never pass as evidence unchecked.
This is summarisation built for evidential work, not just the inbox: the speed of abstraction, with the auditability of extraction.
Operational Use
- Rapid triage of long transcripts and on-screen text
- Multilingual translation and summarisation
- Identification of key statements and entities
- Every summary claim traceable to its supporting passage
Designed for sensitive and challenging content that general-purpose AI systems often reject.
Deployment and Control
- Fully containerised
- On-premise and air-gapped deployment
- No external data dependency
- Customer retains control of all data
Frequently asked questions
How does Rigr AI avoid AI hallucination in summaries?
It pairs abstraction with extraction: every claim in the readable abstract is backed by a verbatim extract from the source, so a flawed conclusion can't pass as evidence unchecked.
Can it summarise across languages?
Yes. It summarises and translates transcripts and on-screen text, rendering the answer in a language other than the original where needed.
Is it suitable for sensitive content?
Yes. It is designed for sensitive and challenging content that general-purpose AI systems often reject, and runs fully containerised on-premise or air-gapped.
Can it handle a large case?
Yes. Within VST Teams it summarises each transcript and document in a case individually, so investigators can triage item by item rather than reading everything in full — every summary backed by its source extracts.