NLP | Tribe AI

NLP

Unlock the potential of NLP

What is natural language processing (NLP)?

Natural Language Processing (NLP) is a form of machine learning technology that enables computers to understand, interpret, and generate human language. By leveraging NLP, businesses can automate customer support, analyze customer feedback, and optimize communication, resulting in increased efficiency and a better customer experience.

Tribe helps companies identify use cases for NLP, select the right models, prepare data, develop custom solutions, and provide ongoing support.

How 3 companies automated manual processes using NLP

Learn how Natural Language Processing (NLP) is being used across industries – it's not just chatbots.

Recent NLP projects

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Accelerated time to market for OpenAI-backed startup

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Built automation roadmap for publishing startup using GPT

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Increased accuracy of core NLP model for compliance startup

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Automated categorization of transactions for fintech co

How Tribe can help

Text classification

NLP algorithms can be used to classify large amounts of text data into specific categories, such as customer inquiries or support tickets. This can help businesses manage their workflow and prioritize tasks more efficiently.

Text mining

Streamline your claims processing with machine learning automation. Quickly identify and handle claims with machine learning algorithms, which detect fraud more efficiently, reducing costs and improving profits.

Chatbots and virtual assistants

Deliver personalized products and services to improve customer satisfaction and retention rates. With machine learning, insurance companies can tailor policy recommendations to each customer, resulting in higher profits.

Named entity recognition

Identify and extract named entities, such as people, places, and organizations, from text data to analyze large amounts of unstructured data in industries such as finance and legal.

Work with the best talent in AI

AI Researcher

Jessy

PREVIOUSLY:

Research at Berkeley and MIT

PhD at Berkeley

AI Researcher

Andrew C.

PREVIOUSLY:

Worked at Google Brain, Gretel AI

OpenAI Fellow

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AI Researcher

Jeff

PREVIOUSLY:

AI and research at Meta,
‍Allen AI, and Palantir

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ML Engineer

Paige

PREVIOUSLY:

Software Engineering at Google‍

Linguistics at UCLA

Data Scientist

Michele

PREVIOUSLY:

Worked for Nasa, Google,
Stanford, Wayfair

AI Research Scientist

Sundeep

PREVIOUSLY:

AI Research at Amazon‍

PhD Cognitive Neuroscience, Published 50+ papers

ML Engineer

Timothy

PREVIOUSLY:

ML at Google

Early engineer at Amazon Data

Research Engineer

Seraphina

PREVIOUSLY:

Researcher at University of Edinburgh

Product at Google

ML engineer

Andrew

PREVIOUSLY:

Engineering at Surge AI, Twitter

Harvard CS degree

ML Engineer

Yada

PREVIOUSLY:

ML at Amazon, Microsoft,
ASAPP, Infinitus

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NLP Researcher

Prem

PREVIOUSLY:

Data Scientist at IBM and AWS,

Faculty at Carnegie Mellon

ML Scientist

Catherine

PREVIOUSLY:

PhD from Cambridge University

Worked on NLP at Amazon Alexa

Senior ML Engineer

Adrian

PREVIOUSLY:

First employee at Weights & Biases,

Worked at Google

ML Engineer

Oana

PREVIOUSLY:

ML Engineer at Meta

Co-founder Habiter (YC S20)

My head was spinning during the entire handoff presentation. We now have our multi-year product roadmap, based on this 8-week project – which is incredible.

Co-founder & CEO

Wingspan

Our Tribe consultant has become an indispensable member of our team. I trust her completely and even included her as part of our leadership team in our fundraising materials.

Co-founder & CEO

Rita Health

After Tribe joined, we went from 0 to 100 in terms for time to market. This work was a jet propulsion for our team

Data Science Leader

Public Medical Device Company

[Our Tribe advisor] grounded us in understanding the different models and training structures to think about. Every week was a new unlock to a deeper understanding of how to use this new technology.

CEO

Nota