List of SAS Visual Text Analytics Customers
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Since 2010, our global team of researchers has been studying SAS Visual Text Analytics customers around the world, aggregating massive amounts of data points that form the basis of our forecast assumptions and perhaps the rise and fall of certain vendors and their products on a quarterly basis.
Each quarter our research team identifies companies that have purchased SAS Visual Text Analytics for Analytics and BI from public (Press Releases, Customer References, Testimonials, Case Studies and Success Stories) and proprietary sources, including the customer size, industry, location, implementation status, partner involvement, LOB Key Stakeholders and related IT decision-makers contact details.
Companies using SAS Visual Text Analytics for Analytics and BI include: Munich Re, a Germany based Insurance organisation with 43306 employees and revenues of $67.13 billion, Cisco Systems, a United States based Professional Services organisation with 90400 employees and revenues of $53.80 billion, American Red Cross, a United States based Non Profit organisation with 19000 employees and revenues of $2.91 billion and many others.
Contact us if you need a completed and verified list of companies using SAS Visual Text Analytics, including the breakdown by industry (21 Verticals), Geography (Region, Country, State, City), Company Size (Revenue, Employees, Asset) and related IT Decision Makers, Key Stakeholders, business and technology executives responsible for the software purchases.
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| Logo | Customer | Industry | Empl. | Revenue | Country | Vendor | Application | Category | When | SI | Insight |
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American Red Cross | Non Profit | 19000 | $2.9B | United States | SAS Institute | SAS Visual Text Analytics | Analytics and BI | 2018 | n/a |
In 2018, American Red Cross adopted SAS Viya and implemented SAS Visual Text Analytics within its Analytics and BI environment to analyze large volumes of unstructured text. The deployment targeted unstructured content such as case notes, incident reports, and stakeholder feedback to inform operational decision-making and improve disaster response effectiveness across the United States.
SAS Visual Text Analytics was used as the text analytics module on the SAS Viya platform, delivering natural language processing capabilities, automated entity extraction, topic detection, sentiment analysis, text classification, and model scoring as part of the Analytics and BI toolset. The public announcement from SAS lists American Red Cross as a Viya adopter, and usage of the SAS Visual Text Analytics module is inferred from that platform release.
Operational coverage centered on disaster response operations and supporting analytics teams, with models trained on internal case notes and feedback streams to surface trends and priorities for incident managers. Implementation focused on embedding text-derived intelligence into operational decision workflows and analytics processes rather than standalone reporting.
Governance aligned analytics practitioners with operational stakeholders to validate models, curate unstructured data sources, and incorporate outputs into incident management procedures. The stated objective was to improve operational decision-making and disaster response effectiveness through application of SAS Visual Text Analytics within the American Red Cross Analytics and BI portfolio.
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Cisco Systems | Professional Services | 90400 | $53.8B | United States | SAS Institute | SAS Visual Text Analytics | Analytics and BI | 2018 | n/a |
In 2018, Cisco Systems implemented SAS Visual Text Analytics as part of its adoption of SAS Viya to accelerate analytics and collaboration across teams. Cisco Systems deployed SAS Visual Text Analytics within an Analytics and BI program to extract insights from unstructured sources and to support operations and customer experience functions in North America.
The implementation centered on the SAS Visual Text Analytics module for natural language processing, including automated concept extraction, entity recognition, topic modeling, and sentiment analysis, deployed on the SAS Viya platform. Workflows emphasized model authoring and supervised classification to turn unstructured text into structured signals for downstream analytics, enabling analysts and data scientists to iterate on taxonomy and rules within the application.
Operational coverage focused on integrations with CRM systems and operational data sources to feed unstructured customer and operational content into SAS Visual Text Analytics, supporting North America operations and customer experience teams. The deployment on SAS Viya centralized text processing, enabling shared model repositories and repeatable scoring pipelines for business units that consume text-derived features.
Governance emphasized centralized model management and collaborative analytics, with rollout practices aligned to cross-team collaboration and reuse of text models and taxonomies. The stated outcome from the vendor announcement indicated the adoption was intended to accelerate analytics and collaboration across teams, with SAS Visual Text Analytics providing the core Analytics and BI text analytics capability for Cisco Systems.
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Munich Re | Insurance | 43306 | $67.1B | Germany | SAS Institute | SAS Visual Text Analytics | Analytics and BI | 2018 | n/a |
In 2018, Munich Re implemented SAS Visual Text Analytics as part of a broader SAS Viya deployment to centralize large-scale Analytics and BI for underwriting, risk assessment and fraud detection across its global insurance operations. The SAS Visual Text Analytics implementation was designed to enable natural language processing and text mining workflows to extract entities, topics and sentiment from unstructured insurance documents, claims narratives and notes to support analytical workflows.
The deployment consolidated model training and scoring, semantic indexing and NLP pipelines within the SAS Viya runtime, improving analytic collaboration and governance for data scientists and underwriters. Functional capabilities implemented included text parsing, concept and entity extraction, taxonomy management and model operationalization, which supported text-based underwriting and risk workflows and facilitated repeatable scoring and inference for fraud detection.
Operational scope covered underwriting, risk management and fraud detection teams across Munich Re's European operations, with centralized access controls and role based analytics to standardize workflows and improve cross-team collaboration. SAS named Munich Re as an early adopter of SAS Viya which included the newly announced SAS Visual Text Analytics, and Munich Re reported improved analytic collaboration and access for users across Europe.
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