Siemens vs Uniphore

Generative-AI assistant for industrial engineers that answers equipment-troubleshooting questions by chat, generates and debugs automation code, and supports digital-twin simulation, built with Microsoft Azure AI.

Ready-to-use AI visual quality inspection system that trains on roughly 20 good samples to detect anomalies, deviations and missing parts on a production line without machine-vision or AI expertise.

Cloud predictive-maintenance software that applies industrial AI to machine and process data to forecast asset failures, rank risk across sites and prioritise maintenance work.

Generative and agentic AI system for Siemens EDA tools that ingests and vectorises multimodal design data, exposes a natural-language interface across the design workflow and automates debugging, with customer-choice LLM support.

Edge software suite for packaging, deploying, running and monitoring AI models on the factory floor, comprising an AI SDK, AI Inference Server and AI Asset Manager running on Siemens Industrial Edge and NVIDIA-accelerated industrial PCs.

Visual drag-and-drop and notebook-based platform in the Rapidminer portfolio for building, training and explaining machine learning and generative AI models, with AutoML tooling and deployment to cloud, on-premises or edge infrastructure.

Enterprise knowledge-graph platform in the Rapidminer portfolio, built on open W3C standards (RDF, SPARQL, OWL, SHACL), that federates cross-domain data into a governed semantic layer and gives AI agents a queryable, traceable context for grounded answers.

A cloud-native enterprise communication recording application that captures voice and screen data, marketed as the capture layer that makes conversation data available to AI. It records uncompressed stereo audio with multi-channel support, includes transcription, and provides customizable policy engines for recording, retention, storage and export alongside MiFID II, Dodd-Frank, PCI DSS and GDPR compliance controls.

A generative-AI conversational intelligence application that analyses 100% of customer conversations to surface trends, sentiment and actionable insights. It automates QA scoring across all calls rather than manual sampling, and surfaces emerging call drivers beyond predefined categories.

An AI agent-assist application that gives contact centre agents in-call support: pre-call intelligence pulled from CRM and past interactions, knowledge assist that delivers contextual answers without manual search, generative conversation summaries with disposition capture, and sentiment detection. A manager dashboard provides live transcription and real-time performance alerts.

An AI recruiting application that summarises resumes and job descriptions, suggests interview questions, and provides real-time co-pilot guidance to interviewers based on candidate background and role requirements. Generative AI automates the creation of interview questions, summaries and notes.

An enterprise sales AI application that analyses the visual, verbal and tonal cues of every sales interaction to surface deal insights and automate administrative work. It provides real-time meeting assistance using emotion AI and generative AI, buyer sentiment and engagement analysis, sales methodology adherence tracking, a searchable sales knowledge base, and AI coaching.

A conversational automation application providing virtual agents across voice and digital channels. It includes emotion AI for sentiment detection and empathetic response, multilingual support with automatic language detection, a no-code conversation designer for business users, and generative-AI training that auto-generates intent phrases.

Builds and orchestrates enterprise AI agents with visual workflows, an orchestration engine and third-party agent integration.

A four-layer enterprise AI platform — data, knowledge, model and agentic layers — meant to unify what a large company already has rather than replace it.

Connects and governs enterprise data for AI without copying it.

Prepares enterprise knowledge for retrieval and model tuning.

Predicts customer behavior and automates marketing execution.

Manages model inference, fine-tuning and orchestration.