FAQs / VIDIZMO AI Hub

VIDIZMO AI Hub

What are AI solutions for library services?

AI solutions for library services refer to the use of artificial intelligence tools like chatbots and intelligent search to automate routine tasks, personalize patron support, and improve resource discoverability.

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How does multimodal AI work?

Multimodal AI runs different AI models on different content types in a coordinated pipeline. Computer vision models analyze video frames; speech recognition models transcribe audio; OCR and NLP extract meaning from documents. A unified indexing layer connects all outputs so a single query retrieves relevant results from any format. In VIDIZMO AI Hub, this entire pipeline runs inside your own infrastructure, no content is sent to external servers for processing.

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How does self-hosted AI differ from cloud AI?

Cloud AI sends your data to a vendor's servers for processing, your content leaves your network. Self-hosted AI processes data inside your own environment using models you control. For law enforcement, healthcare, and government organizations, self-hosted AI is required or strongly preferred because it satisfies data sovereignty requirements, meets CJIS Security Policy mandates, and eliminates the risk of sensitive data being processed in third-party cloud environments. In VIDIZMO AI Hub, AI models run locally via Ollama or VLLM, nothing is sent externally unless your policy specifically permits it.

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What are some examples of responsible AI in government?

Examples of responsible AI in government include Georgia’s Department of Labor using sentiment-aware chatbots, the Department of Transportation using video analytics for traffic management, and the Attorney General’s Office implementing secure digital evidence redaction. 

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What kind of use cases does VIDIZMO support?

VIDIZMO supports a wide range of use cases: redaction of PII, transcription and translation, chatbots, digital evidence management, content moderation, anomaly detection, enterprise-wide video search, and many more.

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How does an evidence chatbot compare to keyword search?

Traditional keyword search only matches text strings in metadata or manually entered tags. An AI chatbot combines transcript search, object detection, visual analysis, and metadata queries into a single natural-language interface. This means officers can find relevant moments even when they do not know the exact words spoken or tags applied.

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What is agentic RAG and how does VIDIZMO implement it?

Agentic RAG combines large language models with retrieval from your data, adding stateful multi-step workflows, multi-agent hierarchies, conditional branching, and human-in-the-loop checkpoints. Unlike basic chatbots, it reasons across multiple steps and retrieves from five content modalities simultaneously.

What types of evidence can an AI chatbot search?

AI chatbots built for digital evidence management can search across video, audio, images, and documents. VIDIZMO DEMS supports 255+ file formats and applies AI processing including transcription, object detection, OCR, and summarization across all ingested evidence. Officers can query body cam footage, dash cam video, interview recordings, surveillance clips, and scanned documents from a single interface.

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How do large language models transform customer service operations?

Large language models transform customer service operations by powering intelligent chatbots and virtual assistants capable of understanding customer queries across different formats. They enhance responsiveness, personalize interactions, and reduce the workload on human support teams. 

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What content can it analyse?

Documents, audio, video, images, and structured data from the systems you already run. Content is transcribed, translated, classified, and made searchable, with transcription across 82 languages.

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How does agentic RAG differ from traditional search in BI tools?

Traditional search relies on keyword matching. Agentic RAG uses AI agents to understand intent, retrieve information across multiple data formats, and generate synthesized answers complete with source citations.

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What AI models does VIDIZMO AI Hub support?

VIDIZMO AI Hub supports both cloud AI models and self-hosted AI models in the same platform. Cloud: OpenAI GPT series, Anthropic Claude, Google Gemini. Self-hosted: Ollama and VLLM, running any compatible open-source model inside your network. Administrators configure which model runs for which workflow, self-hosted for sensitive data, cloud models for non-sensitive analysis where policy permits. Organizations with strict data residency requirements can run entirely on self-hosted models.

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How can agencies measure the ROI of a chatbot for government?

Agencies can measure the ROI of a chatbot for government by tracking reductions in manual support hours, lower wait times, increased citizen satisfaction, and improved operational efficiency. Analytics and usage trends provide clear evidence of value.

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How can AI enhance community engagement in libraries?

AI enhances community engagement by automating patron support and improving how easily people find relevant content. Chatbots and intelligent search help libraries foster stronger connections with patrons by making services faster and more accessible.

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Can different steps in a workflow use different AI models?

Yes. Each AI node can use a different LLM -- GPT-4o for summarization, Claude for analysis, a self-hosted model for classification -- within the same workflow. This multi-model approach optimizes each task for cost, accuracy, and speed without committing to a single provider.

Can VIDIZMO AI Hub replace our current document processing pipeline?

Intelligence Hub combines OCR, layout detection, classification, data extraction, and PII detection into a single automated pipeline. Organizations processing large document volumes -- intake forms, invoices, contracts, regulatory filings -- can consolidate fragmented tools into one governed platform.

What types of documents can Intelligence Hub process?

VIDIZMO AI Hub  processes a wide range of document types with layout detection handling complex structures including tables, multi-column formats, and embedded images.

  • PDFs
  • Word documents
  • Spreadsheets
  • Presentations
  • Images
  • Scanned documents (via OCR)
  • Handwritten text (via ICR)
  • Documents in Perso-Arabic scripts

Does VIDIZMO train AI models on customer data?

No. VIDIZMO's Responsible AI Policy states that customer data is not used for model training without explicit consent. Data stays within the customer's environment, and self-hosted embedding and LLM options ensure no content flows to external AI providers.

How does VIDIZMO AI Hub power CaseBot in the Digital Evidence Management System?

Intelligence Hub's agentic RAG engine is the foundation of CaseBot. It indexes evidence transcripts, detected objects, metadata, and locations, then enables prosecutors and investigators to search across entire case libraries with natural language queries and source citations.

Can VIDIZMO AI Hub enhance EnterpriseTube's video search?

Yes. The  AI Hub  Video Platform solution combines EnterpriseTube and Intelligence Hub for AI-enhanced search across transcripts, OCR text, detected objects, metadata, and visual descriptions simultaneously. Employees find specific moments across thousands of videos in seconds.

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