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AI Voice & Multimodal Systems.

AI beyond text: natural voice interactions, real-time audio, and systems that reason across text, images, audio, and structured data simultaneously.

Voice and multimodal AI audio visualisation
AI Voice Agents Multimodal AI Systems

Voice and multimodal AI extend AI capability beyond text, enabling natural voice interactions, real-time audio processing, and systems that reason across text, images, audio, and structured data simultaneously. DashMindsIQ builds voice and multimodal systems for customer-facing, field, and operational use cases.

Service 01

AI Voice Agents

Conversations that resolve queries and complete tasks, without a human on the line.

AI voice agents handle inbound and outbound telephone interactions autonomously, answering customer queries, collecting information, verifying identity, completing transactions, and escalating to human agents when the situation requires it. Modern AI voice agents are markedly different from the IVR systems they replace: they understand natural speech, handle interruptions and topic changes, maintain conversational context, and resolve queries that previous voice automation could not approach.

DashMindsIQ builds voice agent systems covering the full technical stack: speech-to-text, natural language understanding, dialogue management, text-to-speech, and telephony integration. We design voice agents for the specific use case, whether inbound customer service, outbound appointment confirmation, collections, or lead qualification, with the conversational flows, escalation logic, and performance monitoring that production deployments require.

What this includes
  • Speech-to-text integrationReal-time transcription using Deepgram, Google Speech-to-Text, or AWS Transcribe optimised for your audio quality and accent profile.
  • Conversational dialogue designConversation flow design that handles the full range of likely customer intents, off-topic inputs, and recovery from misunderstanding.
  • Text-to-speech with natural voiceHuman-sounding synthesis using ElevenLabs, Azure Neural TTS, or similar, tuned for your brand tone and call context.
  • Telephony integrationConnecting voice agents to your existing contact centre infrastructure (Twilio, Genesys, Avaya, Five9) or building a standalone telephony layer.
  • Intent recognition and entity extractionReal-time classification of caller intent and extraction of relevant information (account numbers, dates, preferences) from spoken input.
  • Real-time agent assistAI that provides live guidance to human agents during calls, surfacing relevant information, suggesting responses, and flagging compliance risks.
Service 02

Multimodal AI Systems

AI that reasons across text, images, audio, and data, simultaneously.

Multimodal AI systems process and generate content across multiple modalities, including text, images, audio, video, and structured data, in a single coherent system. The commercial applications range from document processing that combines text extraction and image interpretation, to quality control systems that correlate visual defect images with production sensor data, to customer service systems that handle both text messages and image attachments in the same conversation.

DashMindsIQ builds multimodal systems using the latest vision-language models (GPT-4o, Gemini 1.5, Claude 3.5) alongside specialised audio and vision models where the use case demands greater depth in a specific modality. System design accounts for the unique engineering challenges of multi-modal pipelines: coordinating asynchronous processing of different input types, managing the context window constraints of multi-modal models, and building evaluation frameworks that assess output quality across modalities.

What this includes
  • Vision-language applicationsSystems that interpret and respond to combinations of images and text, for document processing, product Q&A, and visual inspection support.
  • Audio and video understandingTranscription, summarisation, and information extraction from recorded meetings, calls, training videos, and multimedia content.
  • Multi-modal document processingExtracting structured information from documents that combine text, tables, charts, and images: invoices, technical drawings, and mixed-format reports.
  • Cross-modal searchEnabling users to search a content library using any modality: find images by text description, documents by example image, or video by transcript topic.
  • Real-time multimodal analysisSystems that process live video, audio, or image streams for monitoring, safety, and quality applications with low-latency inference.
  • Multimodal content generationGenerating content that combines text and image elements: product listings with auto-generated images, illustrated reports, and visual summaries.
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