VIDIZMO integration brief · Azure AI Services · vidizmo.ai/integrations/catalog/azure-ai-services

Integrations / Azure AI Services

Azure AI Services

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Azure AI Services provides speech, translation, vision and language models as managed APIs.

It backs transcription, translation and analysis, and where it runs decides where media is processed.

Speech, Translation and OCR Inside Your Azure Subscription

Open as a two-page brief

Azure AI Services provides speech, translation, vision and language models as managed APIs, in your Azure subscription or as containers on your own servers. Connected to the platform, it backs transcription, translation of transcripts and OCR: a recording becomes a timed transcript, the transcript becomes readable in another language, and a scanned page or on-screen text becomes searchable. The results land against each item in Nexus, where AI Intelligence Hub answers questions over them. Where the service runs decides where media is processed.

Nexus your video, audio, images and documents, indexed under your access rules content the asking user may see AI Intelligence Hub agents, chat, workflows, retrieval with citations; model chosen per agent prompts and embeddings over API Azure AI Services model endpoint, hosted by the provider or on your own servers answers Users chat, search, workflow output Azure AI Services VIDIZMO

How it connects

AI processing runs on one of two provider paths, and the choice is a deployment decision with a data-residency consequence. On the VIDIZMO Indexer path, processing happens on your own infrastructure and content does not leave it. On the Azure AI Services path, you supply your own Azure subscription, the platform calls the services over their REST APIs, and media is processed in that subscription's region.

The same services also run containerized inside your own infrastructure, so capabilities that would otherwise call a cloud service operate without egress.

Media goes out for processing and results come back as timed data. The transcript is aligned to the timeline so every word is a jump point. The translation is made from that transcript. Text is recognized in video frames, images and scanned documents. All of it is indexed and searchable against the item. Transcription language mode is set per job, and language coverage differs by capability and is published per capability.

What you can do together

  • Search a recording by what was said in Digital Evidence Management (DEMS), with every word a jump point and the transcript editable afterwards.
  • Read an interview recorded in one language in another, with the translation made from the transcript, so an investigator searches in English across the case.
  • Make scanned statements and on-screen text searchable through OCR, with a result opening at the page in a document or the timestamp in a video.
  • Transcribe and translate town halls and training recordings in EnterpriseTube so a workforce reads them in its own languages.
  • Ask AI Intelligence Hub a question across transcripts, translations and OCR text and get an answer cited to the moment or the page.

A scenario

  1. SetupIT connects the department's Azure subscription and selects Azure AI Services as the processing provider for transcription, translation and OCR.
  2. 15:10A detective uploads a Spanish-language witness interview and the scanned statement forms for case 24-0331 into Digital Evidence Management (DEMS). The audio goes to the speech service in the department's Azure region and a timed transcript comes back. The English translation follows from the transcript, and OCR reads the scanned forms.
  3. 15:40She searches "blue sedan" across the case. One result opens the interview at the moment the phrase was spoken; another opens a statement at the page.
  4. 16:00She asks AI Intelligence Hub, "Where do the witness statements in 24-0331 disagree about the time?" The answer cites the translated transcript and two OCR pages.
  5. ThroughoutThe media was processed in the department's Azure region. The transcript, translation and OCR text sit with the recording in Nexus under retention and audited access.

What stays where

Azure AI Services stays in your subscription, or in your containers

The resource, the region and the billing are yours, and the containerized form runs on your own infrastructure.

The platform reads timed data

Media goes out for processing; a transcript, a translation and recognized text come back and are indexed against the item. Search, questions and evidence handling happen on the platform.

Nothing is replaced

The VIDIZMO Indexer path remains available, and on it content never leaves your environment. The provider is a deployment decision, not a rebuild.

Where processing runs

In the Azure region your subscription is bound to, or on your own infrastructure in containers. A disconnected deployment uses the VIDIZMO Indexer path, where transcription, translation and OCR run on local models.

Products and solutions

Next step

See it on your own Azure AI Services instance. We will show the connection made, the data moving and the output, then size it for your deployment.

Request a demonstration  or write to sales@vidizmo.ai

sales@vidizmo.ai  ·  vidizmo.ai/integrations/catalog/azure-ai-services

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