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AI-driven supplier intelligence and discovery platform. Matchory aggregates customs records and web-crawled company data to maintain a database of millions of global manufacturers and suppliers. It resolves scattered supplier lists (ERP exports, spreadsheets) into a clean, de-duplicated company base (one MatchoryID per supplier), enriches thin records with verified capabilities, certifications and risk signals, and enables portfolio intelligence and company matching so procurement, R&D and risk teams can search their own base and the whole market as one.

Anthropic's Claude foundational large language model family used by third-party applications under contractual zero-data-retention agreements. No specific Docsum Claude version is publicly documented; Docsum cites "foundational model providers like OpenAI and Anthropic" on its security page.

Retorio is an AI-powered coaching and training platform for enterprise sales, service, and leadership teams, founded at the Technical University of Munich on research from TUM, MIT, and the University of Tokyo. It replaces passive e-learning with lifelike AI role-play in which users practice client conversations with AI personas (photorealistic avatars or phone-based virtual twins) on video or phone. After each session, its multimodal behavioral model analyzes verbal content, voice characteristics, and visual signals (facial expressions, body language, eye contact, posture) and delivers feedback across dimensions including Applied Knowledge, Active Listening, Empathy, Confidence, and Persona-Oriented Communication. Intended users include sales academies, sales and service enablement teams, L&D professionals, heads of sales, contact center teams, and emerging leaders at enterprises (typically 1,000+ employees, min. 300 customer-facing). Evidenced use cases: sales/objection-handling/negotiation coaching, onboarding and qualification, product enablement, contact center enablement, retail performance, emerging-leader journeys, and regulated-industry training in pharma (Merck, Amgen, MLR-review compliant), insurance (Nuerenberger, AXA), telco (Vodafone/VOIS), automotive (Daimler Truck) and FMCG. The platform is EU-hosted (GCP and Azure, both within the EU), GDPR and EU AI Act compliant, ISO 27001 certified, and available in 14 languages with auto-translation.

Ameba is an AI workforce platform for supply chain administration, built by Ameba Systems Ltd. It automates the manual administrative work around purchase orders: quoting customers, chasing suppliers for status updates, reading and summarizing email/WhatsApp/ERP/Excel/PDF/PLM data, and keeping the ERP up to date. Teams teach their processes once in plain English (what to watch for, what to do, when to involve a human), and Ameba's AI workforce runs them 24/7 on every order. Intended users are supply chain, operations and procurement teams at manufacturers, brands and retailers. Vendor-reported outcomes: on-time delivery up 10%, up to 80% less manual data entry, average delay cut in half; operating 50,000+ orders, 80,000 line items, 580,000 emails, 30,000 files processed. It connects to existing ERP/PLM, email, WhatsApp and Excel with no rip-and-replace, and is SOC 2 Type II and GDPR compliant (vendor-reported). Evidenced customer: Anglotex, a Portuguese garment manufacturer reporting raw-material arrivals ~10% faster. Also supports the EU Digital Product Passport by chasing suppliers for certificates and traceability data (fibre composition, recycled content, environmental footprint).

The Databricks Data + AI Platform is a cloud platform on which a company keeps its data and builds analytics, machine learning models and AI agents on top of it. Data engineers, data scientists and analysts use it; business users can ask questions through the built-in assistant Genie. Agent Bricks lets teams build and evaluate agents with a model of their choice, and Unity Catalog governs access to data and models.

The OpenAI API is the developer platform through which companies call OpenAI's models from their own software. It offers text generation, embeddings for search and retrieval, image and audio models, built-in tools, agents, fine-tuning and batch processing. Developers and product teams use it. OpenAI says data sent to the API is not used to train its models unless the customer opts in.