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.

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

Recent NLP projects


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

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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

Research at Berkeley and MIT

PhD at Berkeley

Large Language Models, NLP, Human-In-The-Loop
AI Researcher
Andrew C.

Worked at Google Brain, Gretel AI

OpenAI Fellow

LLMs, NLP, Transformers
AI Researcher

AI and research at Meta,
Allen AI, and Palantir

CV, NLP, ML Engineer
ML Engineer

Software Engineering at Google

Linguistics at UCLA

NLP, CV, Linguistics
Data Scientist

Worked for Nasa, Google,
Stanford, Wayfair

Text classification, Demand forecasting
AI Research Scientist

AI Research at Amazon

PhD Cognitive Neuroscience, Published 50+ papers

Data Science, Causal Interference, NLP
ML Engineer

ML at Google

Early engineer at Amazon Data

Data eng, NLP, Supply chain
Research Engineer

Researcher at University of Edinburgh

Product at Google

AI Fairness, Interpretability, NLP
ML engineer

Engineering at Surge AI, Twitter

Harvard CS degree

Large Language Models, NLP, Humans-In-The-Loop
ML Engineer

ML at Amazon, Microsoft,
ASAPP, Infinitus

Conversational AI, NLP, Healthcare
NLP Researcher

Data Scientist at IBM and AWS,

Faculty at Carnegie Mellon

Large Language Models, NLP, Infrastructure
ML Scientist

PhD from Cambridge University

Worked on NLP at Amazon Alexa

NLP, Chatbots, NLU
Senior ML Engineer

First employee at Weights & Biases,

Worked at Google

Data Science, NLP, Computer Vision
ML Engineer

ML Engineer at Meta

Co-founder Habiter (YC S20)

NLP, LLM, Neural networks, Deep learning
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.
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.
After Tribe joined, we went from 0 to 100 in terms for time to market. This work was a jet propulsion for our team
[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.

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