AI Companies for Data management

Explore AI vendor companies offering data management solutions, including applications in data auditing, knowledge management, data collection, and more.

Ignite Technologies

Description: Ignite Technologies provides business applications and tools to make the workforce of their clients more capable and more committed. In October 2017, Ignite Technologies acquired Infer, a Mountain View-based machine learning company focused on marketing optimization.


Description: Lexalytics helps to solve the problem of text analytics and natural language processing. Use cases span from social listening to survey analysis. Products: AI Assembler Salience Semantria API Semantria for Excel Storage & Visualization

Nuance Communications

Description: Nuance Communications is a technology company with products in voice, natural language understanding, reasoning and systems integration. Nuance is best known for their audio and voice recognition technologies, but the company has offerings in telephone call steering systems, automated telephone directory services, medical transcription software and systems, optical character recognition software, and more. Nuance powers flagship devices and solutions from the likes of Samsung,, Ford, and Domino’s. Products: Nuance's products break down into the following categories: Healthcare Omni-channel customer engagement Print, capture & PDF Mobile & Automotive Dragon & document productivity


Description: Retention Science, the global leader in Retention Marketing, is the best way to understand, engage, and retain your customers. Retention Science’s AI marketing technology predicts customer behavior and helps you create one-to-one campaigns via email, mobile, and web.

Semantic Machines, Inc.

Description: Semantic Machines is a new startup founded by a team of proven entrepreneurs and researchers from the fields of speech recognition and synthesis, natural language processing, and artificial intelligence. We are developing a new kind of mobile experience that will let people accomplish things in an amazing new way. Products: Conversation Engine: The Semantic Machines Conversation Engine is a revolutionary approach for modeling human discourse fluidly across speech and text. The engine extracts semantic intent from natural input (voice or text), and then spawns a self-updating learning framework for managing dialog state, context, salience, and end user goals. The Conversation Engine's natural language generation (NLG) technology actively formulates communication with the user based on dialog context. Deep Learning: Semantic Machines is developing state-of-the-art neural network systems for use across a range of critical functions from semantic analysis to dialog state to acoustic and language models, NLG and speech synthesis. Speech Recognition: The speech team at Semantic Machines previously led ASR development for Dragon Systems, VoiceSignal, Nuance and Siri at Apple. Now we are building a new speech platform to overcome the limitations of these previous systems. Our ASR technology represents an exciting new advancement providing unique capabilities and performance needed for true conversational computing. Speech Synthesis: Speech synthesis is critical for conversational computing. The computer’s voice takes the place of a display providing information users need. Existing speech synthesis technology, particularly the prosodic models, are not sufficient to enable effective conversational computing. Leveraging our extensive NLP and machine learning expertise we are developing a proprietary synthesis technology that will enable conversational computing for the first time. Reinforcement Learning: Reinforcement learning is a core component of our platform. Our novel learning technology enables the system to absorb knowledge from users to continually expand its capabilities in real-time. This learning feedback loop allows the system to improve its understanding of semantics and learn new domains at an ever-increasing rate. Language Independent: The conversational AI technology we are developing is based on a language independent architecture. Our speech and language understanding technology is initially being developed in English, but supports others, including tonal languages like Mandarin. Developer Tools: To enhance and customize the capabilities of our conversational AI we are creating a suite of tools to be used internally and by our partners. Using these tools, developers will be able to adapt our conversational AI technology to their own application space, as well as teach new skills within existing domains.


Description: Skymind is an open-source, enterprise deep-learning provider based in San Francisco, California. We help large corporate teams build deep-learning applications for media, images and sound and time series data for finance, healthcare, telecommunications and the Internet of Things.


Description: Making technology disappear. This is what Snips sets to achieve by embedding an Artificial Intelligence (AI) in every connected device. Whether it is a smartphone, a smartwatch, a connected car or a home appliance, they will one day be able to anticipate their owner’s intentions, and act preemptively to save time and reduce friction. Products: Context Awareness: The user’s personal data is turned into a highly contextualized timeline of activity they did during the day. This includes turning location traces into places visited, parsing chat messages to extract people and places, mining emails for hotel and restaurant reservations, and much more! This runs fully on-device, with no user data being sent to our servers, ensuring privacy by design. Personal Knowledge Graph: The user’s activity timeline and all other contextual data are linked to create his Personal Knowledge Graph. Similarly to how the human brain does, our assistants use this as their memory, enabling contextual disambiguation in natural language interactions. This also runs fully on-device, keeping the user’s data safe. Intent & Entity Recognition: Understanding Natural Language requires two key technologies: detecting the intention of the user, and extracting entities – “things” – they are talking about. Our algorithms leverage both classical NLP methods and Deep Neural Networks, offering a good tradeoff between precision and performance. And since we also wanted to do that on device, we optimized our models so that they could fit on a smartphone with no impact on battery! Deep Natural Language Queries: Deep Natural Language Queries (which involves solving multiple sub-queries) are binded to the user’s Personal Knowledge Graph, enabling arbitrarily complex queries that require contextual understanding. Thanks to our technology, assistants can now answer queries like “show me pictures of the food I ate at that french place I went to for dinner last Thursday in New York”. And yes, this ALSO runs 100% on device, making Snips the first end-to-end private AI assistant.

Tamr Inc.

Description: For Data Officers and Business Counterparts in the Global 2000 whose previous analytic investments are proving inadequate, Tamr delivers the clean, unified data critical for optimizing key decisions. Tamr’s unique machine-driven plus human-guided solution automates the mastering and organizing of a company’s enterprise-wide data (suppliers, customers, products, transactions …) that enables previously unattainable cost and revenue analytics. Business leaders know the analytics they need and their teams have great analytical tools. But they’re forced to compromise on getting data “good enough” - which often leaves them with analytics supplied by only one or few data sources. The reality is that every global company has hundreds or thousands of highly siloed systems and the rich and valuable data sources can’t be used because the means to do so simply aren’t there. The next level of insight will come from the unsexy and hard work of systematically making new data sources analytics-ready. For these business leaders, Tamr is an Enterprise Data Prep Engine for integrating many new data sets. Tamr’s machine-driven, expert-guided approach to mastering empowers teams to take advantage of enterprise-wide data, rather than relying on siloed metrics, to make better decisions and see the bigger picture. The end result is a critical muscle of making data usable and more effective and agile teams.

Data management

Explore AI vendor companies offering data management solutions, including applications in data auditing, knowledge management, data collection, and more.