How One Deal With a Law Firm Made $35,000 — Using a Private LLM

Not long ago, I came across a Reddit post that went viral — over 2.3 million views across Reddit and X. It was about a developer who closed a $35,000 deal with a law firm, not by building a fancy SaaS product or chasing hype, but by creating a private large language model (LLM).

Sounds crazy, right? Let me break it down.

Why Law Firms Needed This

For industries like law, healthcare, banking, or military, privacy isn’t optional. Client data, legal records, financial information — none of this can leave the walls of the company. That means tools like ChatGPT, which run in the cloud, are often off the table.

But what if you could give them a ChatGPT-like system, completely private, running on their own servers, 100% compliant with regulations, and customized to their workflows?

That’s exactly what this guy did.

The Secret: Outcome-Driven Selling

When he first reached out to law firms, he wasn’t trying to sell “chatbots.” Law firms didn’t care about another chatbot. What they cared about was efficiency:

Replacing their receptionist with a 24/7 AI-powered system

Integrating all inbound calls and emails into a smart assistant

Keeping everything private and secure

He focused on outcomes: “Here’s how much money you’ll save. Here’s how much faster your processes will run.”

That’s why they signed.

How the $35,000 Deal Happened

Instead of a one-off build, he packaged the solution as a recurring subscription model:

Imagine a law firm with 1,000 employees

Charge $8 per employee per month

That’s $8,000 in monthly recurring revenue

And because law firms make millions, this pricing feels cheap compared to the value they’re getting.

The result? $35,000 upfront, with potential for much more in recurring deals.

The Tech Behind Private LLMs

Here’s the best part — all the tech is already available, and it’s open-source:

LLMs: LLaMA 70B, Mistral, or other open models can be deployed privately.

Deployment: A $7/month virtual machine or GPU rentals from platforms like RunPod are enough to get started.

Workflows: Tools like n8n handle automation and integration with CRMs, marketing systems, and communication channels.

This means any developer or AI agency can replicate this. You don’t need millions in funding.

Why This Is a Massive Opportunity

Think beyond law firms. This opportunity applies anywhere privacy matters:

🏥 Healthcare — patient data compliance

🏦 Banking & Finance — secure transactions and records

🪖 Military & Government — confidential intelligence systems

📊 Enterprise Companies — internal AI tools without data risk

The demand for private AI will only grow, and companies will happily pay big for solutions they can trust.

Final Thoughts

This story isn’t just about one $35,000 deal. It’s about a blueprint for the future of AI services:

👉 Sell outcomes, not features. 👉 Focus on privacy, compliance, and efficiency. 👉 Use open-source LLMs and automation tools.

For developers and AI entrepreneurs, this is one of the biggest untapped opportunities right now. If you can master private LLM deployments and position them as outcome-driven solutions, you could be closing deals like this too.

🔥 What do you think? Would you pay for a private ChatGPT system inside your company? Or do you see other industries where this model would explode?