Use Cases

What teams use a private LLM for.

Honest, day-one use cases people are getting value from with Palm Valley AI today, the work an LLM grounded in your own data does well, no autonomous-agent fairy dust required.

Ask anything across your knowledge

Connect your docs, PDFs, slides, and runbooks. Anyone on the team can ask plain-English questions and get cited answers, no more digging through Drive or asking the same Slack question for the fifth time.

Best for: CS teams, ops, anyone who answers internal questions repeatedly.

Draft in your team's voice

Feed in your style guide, brand voice, and recent customer-facing writing. The LLM drafts emails, blog posts, support replies, and announcements that sound like you wrote them, not like a generic AI.

Best for: Marketing, customer success, founders writing investor updates.

Analyze docs securely

Drop in contracts, spreadsheets, transcripts, board materials. Ask follow-ups. Your data never leaves the secure boundary, you can put materials in front of the LLM you'd never paste into ChatGPT.

Best for: Legal, finance, ops, anyone handling sensitive documents.

Onboard new hires faster

Point new joiners at the workspace on day one. They learn your business through the LLM, asking dumb questions without bothering anyone, with citations so they can dig deeper into the real docs.

Best for: People ops, engineering managers, anyone scaling a team fast.

Brainstorm with full company context

Think out loud with an assistant that knows your products, your customers, your recent decisions, and your strategy docs. Better than a public LLM that knows none of it, and won't leak your thinking to anyone.

Best for: Founders, PMs, anyone doing strategic work.

Code with internal patterns

Connect your repos, internal style guides, and ADRs. The LLM writes and reviews code that matches your team's conventions, not the random generic patterns it picked up from the open web.

Best for: Engineering teams with strong house style or proprietary frameworks.
// HONESTY NOTE

What this isn't, yet.

Today, Palm Valley AI is a private LLM platform with your data, and a small set of services around it. It is not an autonomous-agent platform that takes action across your tools. That capability is on our roadmap, but we'd rather under-promise and ship the stuff that works than sell you a demo. If you want a custom workflow built on top of the platform today, our Atlas tier covers that as a professional service.

Common contexts

Where these fit best.

Categories where teams tend to get the most value out of a private LLM with their own data.

PROFESSIONAL SERVICES

Knowledge work, accelerated

Research, drafting, project notes, work that lives in documents your team needs to reason over.

FINANCIAL SERVICES

Sensitive analysis

Contracts, reports, policy docs reviewed with an LLM your compliance team will sign off on.

HEALTHCARE

Internal Q&A

Staff Q&A and document analysis with HIPAA-eligible deployment options on Atlas.

LEGAL

Document review

Synthesize across precedent and contracts in a workspace where nothing leaves the boundary.

B2B SAAS

Internal knowledge

Self-serve answers for support, engineering, and ops, grounded in your own runbooks.

EARLY-STAGE STARTUPS

The team's second brain

One assistant that holds the whole company context, for everyone, on web and iOS.

Pick a use case. Try it on your data.

Tell us what your team would actually use this for. We'll show you what's possible, on your docs, with your stack.