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Thematic

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Wit

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Thematic vs Wit: What are the differences?

Thematic: Customer Feedback Analysis via NLP. The fastest and most reliable way for finding deep insights in NPS, CSAT, user research surveys and chat logs; Wit: Natural Language for the Internet of Things. Turn speech into actionable data. Wit enables developers to add a modern natural language interface to their app or device with minimal effort. Precisely, Wit turns sentences into structured information that the app can use. Developers don’t need to worry about Natural Language Processing algorithms, configuration data, performance and tuning. Wit encapsulates all this and lets you focus on the core features of your apps and devices.

Thematic and Wit belong to "NLP / Sentiment Analysis" category of the tech stack.

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What is Thematic?

The fastest and most reliable way for finding deep insights in NPS, CSAT, user research surveys and chat logs.

What is Wit?

Wit enables developers to add a modern natural language interface to their app or device with minimal effort. Precisely, Wit turns sentences into structured information that the app can use. Developers don’t need to worry about Natural Language Processing algorithms, configuration data, performance and tuning. Wit encapsulates all this and lets you focus on the core features of your apps and devices.

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Jobs that mention Thematic and Wit as a desired skillset
CBRE
Australia New South Wales Sydney
CBRE
United Kingdom of Great Britain and Northern Ireland England Farnborough
CBRE
United Kingdom of Great Britain and Northern Ireland England London
CBRE
India Telangana Hyderabad
CBRE
Australia New South Wales Sydney
What companies use Thematic?
What companies use Wit?
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    What tools integrate with Thematic?
    What tools integrate with Wit?
    What are some alternatives to Thematic and Wit?
    SpaCy
    It is a library for advanced Natural Language Processing in Python and Cython. It's built on the very latest research, and was designed from day one to be used in real products. It comes with pre-trained statistical models and word vectors, and currently supports tokenization for 49+ languages.
    rasa NLU
    rasa NLU (Natural Language Understanding) is a tool for intent classification and entity extraction. You can think of rasa NLU as a set of high level APIs for building your own language parser using existing NLP and ML libraries.
    Gensim
    It is a Python library for topic modelling, document indexing and similarity retrieval with large corpora. Target audience is the natural language processing (NLP) and information retrieval (IR) community.
    Transformers
    It provides general-purpose architectures (BERT, GPT-2, RoBERTa, XLM, DistilBert, XLNet…) for Natural Language Understanding (NLU) and Natural Language Generation (NLG) with over 32+ pretrained models in 100+ languages and deep interoperability between TensorFlow 2.0 and PyTorch.
    Amazon Comprehend
    Amazon Comprehend is a natural language processing (NLP) service that uses machine learning to discover insights from text. Amazon Comprehend provides Keyphrase Extraction, Sentiment Analysis, Entity Recognition, Topic Modeling, and Language Detection APIs so you can easily integrate natural language processing into your applications.
    See all alternatives