Our work - Proven solutions for real-world problems.

We believe in efficiency and maximizing our resources to provide the best value to our clients. The primary way we do that is by re-using the same five projects we’ve been developing for the past decade.

Case studies

VC diligence

AI and LLM Integration

VC diligence

This product does diligence on privately held startups. We structure public data to make it simpler for investors to evaluate privately held startups. Customers can also give private data to LLG and we will structure that. Note that LLG keeps the data private.

LLG did an amazing job building out our private AI document query system. Their solution ensures our data remains secure while providing powerful AI capabilities. Highly recommend their services for any privacy-focused AI projects.

Emily Selman, Head of Engineering at Confidant

FamilyFund

Charlie's Checklist

Inspired by Charlie Munger's writings, Charlie's Checklist is an app that allows investors to memorialize their investment checklist and offload research to an AI agent.

LLG developed an innovative AI-powered system that helps investors systematically address qualitative questions that traditional tools like Bloomberg overlook.

Charlie's Checklist empowers users to delve into critical qualitative factors, combining both quantitative and qualitative insights for better-informed decision-making.

Investors can pose crucial qualitative questions such as "Does X have regulatory risk?" or "Is there any evidence of labor disputes?" and receive AI-powered insights.

The AI agent can be trained by investors, ensuring that the responses align with their preferences and requirements, similar to mentoring a human researcher.

Working with Studio, we felt more like a partner than a customer. They really resonated with our mission to change the way people convince their parents to cash out their pensions.

Debra Fiscal, CEO of FamilyFund

Confidant

AI and LLM Integration

Private AI Document Query

Confidant is a private app that allows AI and LLM users to query their private documents via regular chat, ensuring full privacy and security.

The documents and information remain completely private and never touch any foundational models like OpenAI, Anthropic, etc. This is perfect for customers who cannot risk leaking any data.

Confidant can query private notes, PDFs, Excel files, and more, providing the latest AI capabilities controlled entirely by the user.

LLG did an amazing job building out our private AI document query system. Their solution ensures our data remains secure while providing powerful AI capabilities. Highly recommend their services for any privacy-focused AI projects.

Emily Selman, Head of Engineering at Confidant

You’re in good company

  • Phobia
  • Family Fund
  • Unseal
  • Mail Smirk
  • Home Work
  • Green Life
  • Bright Path
  • North Adventures

Reach out!

Our offices

  • San Francisco
    3465 Broderick Street
    Unit 201
    San Francisco, CA 94123