List of Inbenta Enterprise Semantic Search Customers
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Since 2010, our global team of researchers has been studying Inbenta Enterprise Semantic Search 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 Inbenta Enterprise Semantic Search for Application, Web and Enterprise Search 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 Inbenta Enterprise Semantic Search for Application, Web and Enterprise Search include: GOL Linhas Aéreas, a Brazil based Transportation organisation with 14048 employees and revenues of $3.01 billion, Opplus Spain, a Spain based Professional Services organisation with 2762 employees and revenues of $127.0 million, Travel Club Spain, a Spain based Leisure and Hospitality organisation with 120 employees and revenues of $35.0 million and many others.
Contact us if you need a completed and verified list of companies using Inbenta Enterprise Semantic Search, 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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GOL Linhas Aéreas | Transportation | 14048 | $3.0B | Brazil | Inbenta Technologies | Inbenta Enterprise Semantic Search | Application, Web and Enterprise Search | 2016 | n/a |
In 2016, GOL Linhas Aéreas deployed Inbenta Enterprise Semantic Search to power its GAL virtual assistant and WhatsApp self-service for passenger support. GOL Linhas Aéreas implemented Inbenta Enterprise Semantic Search in the Application, Web and Enterprise Search category to centralize semantic knowledge and automate conversational workflows for passenger interactions across Brazil.
The implementation configured Inbenta Enterprise Semantic Search to provide semantic search and knowledge management capabilities that feed natural language understanding and response generation for the GAL chatbot and WhatsApp channel. Functional capabilities included conversational intent resolution, knowledge base indexing for help center content, and automated check in flows routed through the chat interfaces.
Integrations were concentrated on the GAL virtual assistant, WhatsApp self-service, and the airline help center to create an omnichannel passenger support surface, with operational coverage focused on passenger support and contact center workloads in Brazil. Governance emphasized iterative knowledge tuning and conversational rule updates driven by contact center interactions, and the rollout produced explicit outcomes cited by the vendor, including millions of queries deflected and approximately 35% of check ins completed via WhatsApp, which reduced pressure on contact centers.
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Opplus Spain | Professional Services | 2762 | $127M | Spain | Inbenta Technologies | Inbenta Enterprise Semantic Search | Application, Web and Enterprise Search | 2022 | n/a |
In 2022, Opplus Spain implemented Inbenta Enterprise Semantic Search as part of a broader Inbenta AI platform deployment that included Chat, Knowledge and Assist. The initiative targeted Opplus's BPO operations serving BBVA and aimed to shift service handling to a self-service model while reducing escalations across its banking office network. The implementation explicitly lists the Knowledge product as the knowledge management and semantic search component of the platform.
Configuration focused on semantic search and knowledge management capabilities provided by Inbenta Enterprise Semantic Search, integrated with conversational Chat and agent Assist functionality. Functional modules implemented included semantic indexing of knowledge assets, natural language search, conversational intent handling for self-service interactions, and agent assist context delivery to reduce manual escalations. These modules were configured to support automated resolution flows and to surface ranked knowledge responses to both customers and agents.
Operational coverage extended across Opplus's banking office network and contact center operations that support BBVA customer interactions, impacting customer service and branch support functions. The deployment is categorized under Application, Web and Enterprise Search and serves both external customer-facing channels and internal agent lookup workflows. The source case study does not enumerate external system integrations by name.
Governance and process changes accompanied the technical rollout, with Opplus centralizing knowledge ownership and redefining escalation workflows to favor automated self-service first and agent assist second. Rollout cadence and tuning occurred within a 12 month window, implying staged knowledge base population, conversational model refinement, and agent onboarding to Assist-driven workflows. Ownership models were adjusted to maintain knowledge currency and to manage escalation thresholds.
The vendor case study reports that the combined Inbenta platform, including Inbenta Enterprise Semantic Search, Chat and Assist, produced an 84% reduction in escalations and very high automation metrics within 12 months. Opplus implemented Inbenta Enterprise Semantic Search in 2022 to embed knowledge management and semantic search into its customer service and agent assist stack, aligning the Application, Web and Enterprise Search capability with frontline banking operations.
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Travel Club Spain | Leisure and Hospitality | 120 | $35M | Spain | Inbenta Technologies | Inbenta Enterprise Semantic Search | Application, Web and Enterprise Search | 2012 | n/a |
In 2012, Travel Club Spain implemented Inbenta Enterprise Semantic Search to strengthen member self-service and automate routine loyalty and CRM inquiries. The deployment used Inbenta Enterprise Semantic Search as an Application, Web and Enterprise Search solution to power the Laura virtual assistant and the online help center, linking search-driven knowledge retrieval to conversational AI.
Functionally the implementation combined semantic search, knowledge base indexing, and conversational AI workflows so the Laura virtual assistant could resolve FAQ requests and surface loyalty program information. The configuration implied use of search relevance tuning, intent recognition, and knowledge article management to feed chatbot responses and the public FAQ, extending across customer service and loyalty operations in Spain. Governance centered on content curation and taxonomy management to keep the knowledge base aligned to loyalty and CRM workflows, with an operational emphasis on continuous knowledge updates to maintain answer accuracy. The project improved member self-service and automated routine loyalty and CRM queries, with the Inbenta solution serving both chat and web help channels.
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