Unlock the potential of Generative AI

Tribe's Generative Blueprint helps you navigate this bleeding edge technology and apply it to business functions that reduce cost and increase profit.

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The Generative Blueprint

In four weeks unlock the power of generative AI for your business.

Identify generative use cases unique to your business, explore which LLM is right for you, build a working prototype, fine-tune your model to optimize results, and get a comprehensive product roadmap and implementation plan.

1
Week 1
Discovery

We start by identifying generative use cases specific to your business and setting performance benchmarks to ensure alignment with your goals. Next we conduct stakeholder interviews to gain a deeper understanding of your organization's workflows to develop a clear success criteria for your generative product.

2
Week 2
Rapid prototyping

In week two of the Blueprint, we bring your generative use case to life. In this phase, we do rapid prototyping to build an MVP tailored to your identified use-case. Our team will test various Large Language Models (LLMs) to pinpoint the one that delivers optimal results for your specific needs.

3
Week 3
Fine-tuning

We believe in a data-driven approach, and thus, in week three we continuously evaluate and measure the performance of your product to guarantee it meets established benchmarks and success criteria. Based on the results, we'll fine-tune the models and the prompts to optimize the outputs.

4
Week 4
Implementation plan

In the final week of the engagement our team will develop a comprehensive implementation plan, outlining the necessary steps to seamlessly transition your MVP into a full-scale production solution. We consider factors such as scalability, maintainability, and integration with existing systems, ensuring a smooth and efficient deployment.

Powered by the top talent in AI
AI Researcher
Andrew C.
previously:

Worked at Google Brain, Gretel AI

OpenAI Fellow

LLMs, NLP, Transformers
AI Researcher
Jeff
previously:

AI and research at Meta,
Allen AI, and Palantir

CV, NLP, ML Engineer
Data Scientist
Michele
previously:

Worked for Nasa, Google,
Stanford, Wayfair

Text classification, Demand forecasting
Principal ML Engineer
Rahul
previously:

Director of Data Science at Appen,

Researcher at Toyota

Infrastructure, Data Science, ML Ops
ML Engineer
Timothy
previously:

ML at Google

Early engineer at Amazon Data

Data eng, NLP, Supply chain
ML Product Manager
Saguna
previously:

ML Producer at Uber and Groupon,

HCI at Stanford

Product Management, Language Interfaces, Algorithmic Pricing
Research Engineer
Seraphina
previously:

Researcher at University of Edinburgh

Product at Google

AI Fairness, Interpretability, NLP
ML engineer
Andrew
previously:

Engineering at Surge AI, Twitter

Harvard CS degree

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

Deep Learning Scientist at Ravel Biotech

Researcher at Harvard Medical School

LLMs, Genomics, Reinforcement learning
NLP Researcher
Prem
previously:

Data Scientist at IBM and AWS,

Faculty at Carnegie Mellon

Large Language Models, NLP, Infrastructure
Senior ML Engineer
Adrian
previously:

First employee at Weights & Biases,

Worked at Google

Data Science, NLP, Computer Vision
ML and Software Engineer
Jorg
previously:

Worked for Google Brain

and Facebook AI Research

Neural Networks, Computer Vision, Transformers
CTO
Oleksandr
Previously:

CTO at Togal
ML at Adblock

Deep learning, Neural networks, ML engineer
ML Engineer
Paige
Previously:

Software Engineering at Google

Linguistics at UCLA

NLP, CV, Linguistics
CTO
Doug
Previously:

VP of Eng at Carta

Head of Eng at Nova

Blockchain, Fintech, Advisor
Senior Data Scientist
Kineret
Previously:

Data at Google

Launched Apple card at Apple

Data infra, Deep learning
AI Research Scientist
Sundeep
Previously:

AI Research at Amazon

PhD Cognitive Neuroscience, Published 50+ papers

Data Science, Causal Interference, NLP
ML Engineer
Alda
Previously:

Engineer at Cityblock Health

Sr Engineer Flatiron Health

Product, Dimensional modeling, Analytics
ML Engineer
Scott
Previously:

Led ML at ClearBrain , Amplitude

Recommendations, ML infra, AWS
ML Engineer
Yada
Previously:

ML at Amazon, Microsoft,
ASAPP, Infinitus

Conversational AI, NLP, Healthcare
Full-stack Engineer
Richard
Previously:

Engineer at RBC

ML scientist at Arterys medical

Neural networks, Data eng, Recommendations
ML Engineer
Helen
Previously:

Worked at Asana, Wikimedia, CertiK

1st DS hire at Deserve

Data science, Web3, AI Ethics
ML Scientist
Catherine
Previously:

PhD from Cambridge University

Worked on NLP at Amazon Alexa

NLP, Chatbots, NLU
ML Engineer
Oana
Previously:

ML Engineer at Meta

Co-founder Habiter (YC S20)

NLP, LLM, Neural networks, Deep learning
[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.
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.
Tribe stepped into our company at a critical time to help us not only build out our machine learning, but also to act as a true advisor.
We got so much more out of this project than we thought we would. And that’s in large part to the quality of the people Tribe brought in.
It’s very rare you meet people like Tribe engineers who have the technical skills to understand your data, turn it into something actionable, and also communicate the value to us as the business guys.
How Tribe accelerates generative AI

Top AI talent

Tribe has built a network of 300+ leading AI and ML practitioners from companies like OpenAI, Google, Meta, by leveraging fractional work models and making it easy for top talent to start consulting.

Our own custom models

Sandr (our bespoke staffing LLM) and our extensive data infrastructure, enable us to staff technical dream teams in hours instead of weeks. Our process combined with our constantly growing pool of talent let us support companies as they evolve their across their AI lifecycle.

Industry expertise

Tribe members have years of experience building and deploying real-world AI solutions at scale and across industries. Our network has deep expertise in finance, healthcare, insurance, private equity, ecommerce and more.

Security

Our team has extensive experience in data privacy and security compliance, ensuring that your data remains secure and confidential. We provide secure storage of sensitive data through a combination of encryption, access control, and secure protocols.

Get started with the Generative Blueprint today

Learn more about generative AI

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Case Study

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Podcast

Stackoverflow: ML and AI consulting-as-a-service (ep. 541)

Applied AI

A Primer on Generative AI

Applied AI

Navigating the Generative AI Landscape