List of Microsoft Azure Language Understanding Intelligent Service (LUIS) Customers
Microsoft
One Microsoft Way,
Redmond, 98052-6399, WA,
United States
Redmond, 98052-6399, WA,
United States
1 425-882-8080
Professional Services
221000
$243.0B
Since 2010, our global team of researchers has been studying Microsoft Azure Language Understanding Intelligent Service (LUIS) 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 Microsoft Azure Language Understanding Intelligent Service (LUIS) for ML and Data Science Platforms 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 Microsoft Azure Language Understanding Intelligent Service (LUIS) for ML and Data Science Platforms include: Microsoft, a United States based Professional Services organisation with 221000 employees and revenues of $243.00 billion, NedBank, a South Africa based Banking and Financial Services organisation with 25954 employees and revenues of $63.59 billion, Tech Mahindra, a India based Professional Services organisation with 148000 employees and revenues of $6.40 billion, AFP Habitat, a Chile based Banking and Financial Services organisation with 1581 employees and revenues of $214.5 million, Wysdom.AI, a Canada based Professional Services organisation with 72 employees and revenues of $12.0 million and many others.
Contact us if you need a completed and verified list of companies using Microsoft Azure Language Understanding Intelligent Service (LUIS), 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 Machine Learning software purchases.
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| Logo | Customer | Industry | Empl. | Revenue | Country | Vendor | Application | Category | When | SI | Insight |
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AFP Habitat | Banking and Financial Services | 1581 | $215M | Chile | Microsoft | Microsoft Azure Language Understanding Intelligent Service (LUIS) | ML and Data Science Platforms | 2018 | n/a |
In 2018, AFP Habitat deployed Microsoft Azure Language Understanding Intelligent Service (LUIS) to power Habi, an intelligent assistant designed to provide affiliates with personalized and transparent support around the clock. The implementation is categorized under ML and Data Science Platforms and concentrated on conversational language understanding to support pension fund customer engagement.
Microsoft Azure Language Understanding Intelligent Service (LUIS) was configured to provide core capabilities including intent classification, entity extraction, utterance management, model training, and publishing workflows. Models were tuned to recognize affiliate inquiries and map natural language inputs to service actions, enabling Habi to surface account information and guide routine transactions through automated conversational flows.
The architecture used Azure-hosted LUIS runtime accessed by the Habi conversational interface across digital channels, enabling 24x7 availability for affiliates. Operational coverage targeted customer service and affiliate communications within AFP Habitat, with the assistant serving as the first line of interaction and escalating complex cases to human agents.
Governance centered on iterative model retraining and intent review cycles driven by product and support stakeholders, with rollback and update controls in the published LUIS models. The project increased the level of customer satisfaction and delivered a more personalized and transparent 24x7 service for affiliates.
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Microsoft | Professional Services | 221000 | $243.0B | United States | Microsoft | Microsoft Azure Language Understanding Intelligent Service (LUIS) | ML and Data Science Platforms | 2019 | n/a |
In 2019 Microsoft deployed Microsoft Azure Language Understanding Intelligent Service (LUIS) as a core component of an AI driven finance Chatbot designed to modernize the Procure to Pay service, the work classified within the ML and Data Science Platforms category. The initiative originated inside Core Services Engineering and Operations and Microsoft Finance Engineering, targeting an end to end user experience for procure to pay rather than a system centric set of disconnected apps.
The implementation consolidated 16 discrete services into a services oriented architecture and created an overarching End to End User Experience layer that unified presentation, master data interfaces, and orchestration. Functional capabilities implemented include conversational intent detection and context switching driven by Microsoft Azure Language Understanding Intelligent Service (LUIS), QnA Maker and Azure Cognitive Services for natural language understanding, plus text analytics for entity extraction and question answering. The solution surface was exposed through Azure Bot Service to enable interactive conversations and to perform automated actions based on search and business data.
Integrations were explicitly instrumented across telemetry and data processing layers, including Application Insights and Kusto for live site monitoring, Azure Stream Analytics and Azure Event Hubs for event ingestion, Azure Data Lake Storage and Azure Databricks for big data processing. Backend system integration used microservices deployed on Azure Service Fabric to abstract complexity and allow the bot to call discrete service APIs, while channel integrations included Cortana alongside other conversational endpoints. These integrations tied the conversational layer to finance operational systems supporting Procure to Pay workflows.
Governance and rollout were organized around a user centric design principle, shifting ownership to Finance Engineering and CSEO to manage the unified experience and to reduce manual cross application navigation. Process restructuring emphasized conversational workflows that determine intent across multiple contexts and user personas, and orchestrated automated steps to reduce friction between services. Architecture and operational design included scalability and extensibility requirements to allow future integration with vertical services and analytics pipelines.
The implementation was explicitly positioned to simplify employee experience and reduce manual handoffs by enabling fluid, context aware conversations and by automating certain process tasks where appropriate. The Finance Digital Assistant architecture was designed with scalability in mind and to integrate with multiple analytics and service layers, leveraging Microsoft Azure Language Understanding Intelligent Service (LUIS) as the primary natural language component within the ML and Data Science Platforms stack.
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NedBank | Banking and Financial Services | 25954 | $63.6B | South Africa | Microsoft | Microsoft Azure Language Understanding Intelligent Service (LUIS) | ML and Data Science Platforms | 2017 | NML |
In 2017, NedBank deployed Microsoft Azure Language Understanding Intelligent Service (LUIS) as the NLU core for its Electronic Virtual Assistant, positioning the implementation within the ML and Data Science Platforms category. The project targeted Nedgroup Investments call center interactions and aimed to move client engagement from voice channels to messaging and web channels, with implementation and advisory support from NML and Microsoft Digital Advisory Services.
The implementation configured Microsoft Azure Language Understanding Intelligent Service (LUIS) for intent classification, entity extraction, and localized language models, complemented by dialog management and response tone control. Capabilities implemented included conversational intent recognition, form prepopulation using existing client data, escalation rules for live agent takeover, and iterative linguistic tuning, reflecting standard natural language understanding and dialog orchestration workflows for bot services.
Operational integration aligned LUIS with the Microsoft Bot Framework and Azure AI Bot Service to run conversational flows, and the solution was provisioned for front end channels beginning on the Nedgroup Investments website with planned expansion to messaging platforms such as WhatsApp, Facebook Messenger, and Slack. Live agent handoff was instrumented so agents could take over sessions and also use the virtual assistant as an internal knowledge retrieval and content delivery tool, improving answer consistency across channels.
Governance and rollout followed an iterative, multidisciplinary process, engaging linguistic experts and marketing to localize intents and responses, and establishing content management and escalation workflows for compliance and customer experience consistency. The development cadence was rapid, with a prototype delivered in three months and a fuller production release less than four months later, under implementation services provided by NML and advisory input from Microsoft Digital Advisory Services.
EVA went live in February 2017 and, as reported by NedBank, handled 80 percent of the programmed inquiries at 10 percent of the cost of live agents, freeing live agents for exception handling and serving as a support tool for agent research. The deployment demonstrates an enterprise pattern of embedding Microsoft Azure Language Understanding Intelligent Service (LUIS) within conversational automation to scale customer service while retaining human escalation points.
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Professional Services | 148000 | $6.4B | India | Microsoft | Microsoft Azure Language Understanding Intelligent Service (LUIS) | ML and Data Science Platforms | 2018 | n/a |
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Professional Services | 72 | $12M | Canada | Microsoft | Microsoft Azure Language Understanding Intelligent Service (LUIS) | ML and Data Science Platforms | 2018 | n/a |
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Buyer Intent: Companies Evaluating Microsoft Azure Language Understanding Intelligent Service (LUIS)
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FAQ - APPS RUN THE WORLD Microsoft Azure Language Understanding Intelligent Service (LUIS) Coverage
Microsoft Azure Language Understanding Intelligent Service (LUIS) is a ML and Data Science Platforms solution from Microsoft.
Companies worldwide use Microsoft Azure Language Understanding Intelligent Service (LUIS), from small firms to large enterprises across 21+ industries.
Organizations such as Microsoft, NedBank, Tech Mahindra, AFP Habitat and Wysdom.AI are recorded users of
Microsoft Azure Language Understanding Intelligent Service (LUIS) for ML and Data Science Platforms.
Companies using Microsoft Azure Language Understanding Intelligent Service (LUIS) are most concentrated in Professional Services and Banking and Financial Services, with adoption spanning over 21 industries.
Companies using Microsoft Azure Language Understanding Intelligent Service (LUIS) are most concentrated in United States, South Africa and India, with adoption tracked across 195 countries worldwide. This global distribution highlights the popularity of Microsoft Azure Language Understanding Intelligent Service (LUIS) across Americas, EMEA, and APAC.
Companies using Microsoft Azure Language Understanding Intelligent Service (LUIS) range from small businesses with 0-100 employees - 20%, to mid-sized firms with 101-1,000 employees - 0%, large organizations with 1,001-10,000 employees - 20%, and global enterprises with 10,000+ employees - 60%.
Customers of Microsoft Azure Language Understanding Intelligent Service (LUIS) include firms across all revenue levels — from $0-100M, to $101M-$1B, $1B-$10B, and $10B+ global corporations.
Contact APPS RUN THE WORLD to access the full verified Microsoft Azure Language Understanding Intelligent Service (LUIS) customer database with detailed Firmographics such as industry, geography, revenue, and employee breakdowns as well as key decision makers in charge of ML and Data Science Platforms.