“How Entrepreneurs Are Making Real Money with AI Agents: 3 Case Studies You Should Know”
If you’re someone who’s been paying attention to the rise of AI and especially if you’ve ever thought about starting your own business around it then you’ve probably wondered:
“Is anyone actually making serious money with AI agents?”
The answer is yes.
In fact, several startups and entrepreneurs have already scaled AI agent-based businesses into six-figure or even seven-figure monthly revenues.
And what’s more exciting is that many of these businesses started small, iterated quickly, and found smart ways to scale up—without necessarily needing huge technical teams.
Today, I want to share three real-world examples of companies using AI agents to generate serious income.
We’ll look at what they built, how they scaled, and what marketing strategies helped them grow.
If you’re curious about how AI can be turned into an actual business, this is for you.
1. Cal AI: The AI calorie tracker built by teenagers
Let’s start with Cal AI, a company that’s gotten a lot of attention recently.
Cal AI was launched in 2022 by two teenage founders who wanted to simplify calorie tracking.
Instead of manually logging every meal, their app lets users simply snap a photo of their food, and the AI agent estimates the calories automatically.
Within a few months of launching, Cal AI had crossed over 5 million downloads and was reportedly generating over $800,000 in monthly recurring revenue.
So how did they scale so fast?
1)Viral marketing through social media:
Their users shared screenshots and videos of the app on TikTok, Instagram, and Reddit, leading to organic virality.
2)A freemium model with paid upgrades:
The core features were free, but premium features—like personalized diet plans and unlimited scans were offered through a paid subscription.
3)A hyper-focused product:
Rather than trying to be a full fitness app, they focused on solving one specific pain point really well: making calorie counting effortless.
Their story shows that AI agents don’t need to be complicated to be valuable—if they automate a task people do every day, users will flock to it.
2. Decidr: An AI agent for smarter business decisions
Decidr is an Australian startup that built an AI agent to assist businesses in making faster, data-driven decisions.
Founded in 2018, Decidr started by offering AI-powered tools for recruitment, helping companies screen and shortlist candidates more efficiently.
But their big breakthrough came when they expanded their AI agent’s capabilities into other sectors like e-commerce, skincare, and marketing.
For example, they partnered with the skincare brand Edible Beauty to integrate an AI agent on their website that guided customers through personalized product recommendations.
The result? A 50% increase in online sales.
Their scaling strategies included:
Industry-specific solutions:
Instead of creating one generic AI agent, Decidr customized its agent’s behavior and workflows for different industries, increasing perceived value.
Partnerships with bigger platforms:
They collaborated with AWS and other cloud providers to reach enterprise clients.
Marketing focused on ROI:
Their messaging always included concrete numbers: “8x faster hiring,” “50% more sales,” “3x customer engagement.”
This results-driven approach helped them close deals with skeptical clients.
Decidr’s success highlights how AI agents that directly impact revenue or save significant time are easier to monetize in B2B settings.
3.Relevance: Building AI agents for non-coders
Relevance, also based in Australia, took a different angle.
Instead of building AI agents for one industry, they created a platform that lets non-developers build their own AI agents without coding.
Think of it like the “Canva for AI agents.”
Relevance recently raised $37 million in Series B funding and counts companies like SafetyCulture and Activision as clients.
How did they scale so quickly?
1) No-code, user-friendly interface:
By removing the need for programming knowledge, they opened up AI agent creation to a much larger audience such as marketers, educators, operations managers.
2) A focus on collaboration:
Their platform made it easy for teams to co-build AI agents for internal workflows, automating tasks like onboarding, FAQs, and project tracking.
3) Expanding use cases beyond one niche:
Instead of limiting their product to just customer service or marketing, they encouraged experimentation across industries.
Their marketing leaned heavily into “empowering non-technical users”—positioning AI as an accessible tool rather than an intimidating technology.
What can we learn from these AI agent businesses?
These three companies show that building a business around AI agents doesn’t require inventing entirely new AI models or hiring huge engineering teams.
Sometimes it’s about applying existing AI in a focused, useful way.
Sometimes it’s about creating tools that let others build their own solutions.
And often, success comes from solving one painful problem really well, then expanding once traction builds.
In all three cases, their marketing leaned toward results, usability, and virality.
They didn’t focus on technical jargon or algorithms they focused on showing how their AI agents made people’s lives easier, businesses more profitable, or work more efficient.
Thinking about building your own AI agent business?
If you’ve ever wondered how you could turn AI into a profitable venture, these examples show that it’s not only possible. It’s already happening.
You don’t necessarily have to build the next ChatGPT.
You could:
Create a niche-specific AI agent for a local industry.
Build templates or workflows for a no-code AI platform.
Offer AI agent integration services for small businesses.
The opportunities are wide open, and the market is still early.
Sometimes the most valuable ideas come from simply asking:
“What’s a repetitive task that AI could handle for someone?”
Solve that, package it well, and you might find your AI-powered side hustle or even your next full-time business.