How We Built 5 Real AI Agents in Just 6 Months
Blazing a trail through the world of artificial intelligence, I’m thrilled to share how we built five real AI agents over the past six months. These aren’t just theoretical concepts or flashy demos—they’re production-ready solutions we’ve crafted for clients at our innovative agency. Each one automates complex tasks, saves time, boosts profits, and helps businesses scale like never before. I’ve been part of this journey from the ground up, witnessing firsthand how automation can transform real-world workflows. At our agency, we pioneered an “agents as a service” model, and I’m excited to dive into these unique use cases with you. From slashing manual workloads to streamlining operations, these AI agents are game-changers. If you’re curious about practical AI in action, stick with me as I unpack each one. Let’s jump right in!
We strongly recommend that you check out our guide on how to take advantage of AI in today’s passive income economy.
Table of Contents
AI Agent #1: Facebook Marketing Agent
Crafting a Solution for Kup
One of our first standout projects was for Kup, a Dutch online learning platform focused on nursing and healthcare. Kup uses interactive VR and AR simulations to let professionals and students practice in lifelike virtual settings—an incredible tool for training. But as they aimed to grow globally, they hit a wall. Tasks like creating content and managing Facebook ads were eating up too much time and demanded specialized skills they couldn’t scale. That’s where we stepped in with a team of four AI agents we call an “agency.” Picture this: a social media manager agent oversees everything, a content writer crafts compelling posts, an image generator churns out on-brand visuals, and a Facebook manager optimizes campaigns—all working in harmony.
How It Works in Action
Imagine a busy team suddenly freed from the chaos of Facebook Ads Manager. We set up a human review step using Notion, letting Kup’s staff approve ad sets before they go live. Once approved, a simple automation posts everything to Facebook. This setup cuts manual work by 80-90%. For a demo, our project manager, Nick, messaged the agent via Slack—like chatting with a coworker—asking for an ad about a free four-week VR nursing simulation. The social media manager sprang into action, prompting the content writer to whip up ideas. We picked one, refined the copy together, and the image generator offered four visuals. We chose a crisp, professional shot of a nurse in a VR headset—perfectly aligned with Kup’s brand.
Fine-Tuning and Results
Next, we detailed the ad set in Notion, reviewed it as a team, and watched the Facebook manager launch it seamlessly. After launch, we could analyze performance—think active campaigns, spend over two months, or impressions by ad set. I even asked, “What’s the average audience age per campaign, and how can we improve?” The agent delivered a detailed breakdown with actionable tips. This feedback loop is pure gold—constant chats with the agent refine ads over time. We learned that a human review step is vital early on, especially with big budgets at stake. Kup’s team once worried about a $10,000 misstep, but Notion keeps everything in check until the agent’s fully trained.
Scaling the Vision
What started as a custom fix for Kup is now evolving into a reusable, vertical AI agent. Having built similar tools for other clients, we’ve spotted patterns. Soon, we’ll productize this agent, making it scalable across businesses with a fixed price per lead. Costs? Just $12 per demo, including images. It’s a glimpse into how tailored AI agents can grow into broader solutions—a theme you’ll see across this journey.
AI Agent #2: DNS Support Agent
Solving a Sticky Problem for Ali AI
Next up is a DNS support agent we built for Ali AI, a platform that automates workflows with AI-powered tools. Their website speed optimizer feature relies on precise DNS setups—a nightmare for users prone to errors that could crash entire sites. Ali’s support team was drowning in tickets, so we created a virtual network engineer. This agent knows DNS inside out, trained on docs from GoDaddy, Namecheap, Cloudflare, and more. It doesn’t just troubleshoot—it analyzes your setup with 10 specialized tools, pinpoints mistakes, and walks you through fixes step-by-step.
Seeing It in Production
Picture a frantic user typing, “Help! My DNS is broken!” In Ali’s live setup, this agent integrates with Intercom, responding to tickets instantly. For our demo, I tested it on our SaaS platform, typing, “Solve a DNS issue with this domain.” Behind the scenes, it scanned with tools like MX Toolbox, spotting missing records. It replied with clear instructions: “Switch to Ali’s AI name servers—here’s how for GoDaddy.” I could almost feel the relief as I followed along. In production, it answers tickets via Intercom’s API, slashing support workload by over 80%.
Key Lessons and Costs
The magic here is blending knowledge with action. This agent doesn’t just parrot docs—it tailors advice to your exact setup. At 8 cents per request, it’s a steal compared to hours of human troubleshooting. We learned that combining analysis with guidance beats either alone, delivering results that feel almost human. It’s a lifeline for Ali’s team and users alike, proving AI agents can tackle niche, high-stakes tasks with precision.
AI Agent #3: Questionnaire Agent
Tackling Complexity for Sustainability
Then there’s our questionnaire agent, built for a UK- and France-based sustainability consultancy with 25 years in the game. They help big European firms track carbon emissions, but their process was brutal—130-question forms and 300-page scoring rubrics took employees three days to finish. We built an AI agent to parse Word files, match questions, and apply scoring—all in one swoop. What once took days now wraps up in 20 minutes. Imagine the relief of ditching that grind!
A Peek at the Process
I opened our app, uploaded an Excel template and Word file, and told the agent to start. It broke the massive questionnaire into chapters, scoring each one as I watched the progress bar tick in Gradio. Thirteen minutes later, a fully scored Excel file popped up—tabs brimming with tables, some with hundreds of rows. It’s a beast of a workbook, complex enough to make your head spin, yet the agent handled it flawlessly. These form-filling AI agents are gold for businesses like e-commerce stores needing fast, accurate automation.
Savings and Insights
Cost-wise, it’s a no-brainer. Three days of employee time—over $300—drops to $1-$2 and 13 minutes. The savings are so massive that model choice barely matters. We learned that AI agents can obliterate manual costs in repetitive, data-heavy tasks, making them must-haves for industries buried in paperwork.
AI Agent #4: Jack – Home Repair Agent
Simplifying Home Fixes
Jack, our fourth agent, is a vertical AI startup focused on home maintenance. It streamlines repair estimates—a process once bogged down by manual data collection and shifting costs across the U.S. Through a chat interface, Jack asks homeowners the right questions, then uses the 01 Mini reasoning model to pull pricing from a Vector database on Firestore. Administrative overhead? Down 90%. Picture a company shifting focus from spreadsheets to actual repairs—game-changing stuff.
Chatting with Jack
I typed, “My dishwasher’s leaking—how much to fix?” Jack didn’t guess—it asked for details: “Is it a seal issue or a hose? Where are you located?” After I answered, it crunched data from similar cases, landing on $170. It’s like having a savvy contractor in your pocket. Integrated with Sendbird, it chats via WhatsApp or SMS in production, but our local demo showed its finesse. At 10 cents per estimate, it’s a bargain for such precision.
Takeaway for Success
The trick? Gather all info before acting. Rushing to answers kills accuracy, but Jack’s methodical approach boosts trust and results. It’s a lesson in patience paying off—applicable to any AI agent aiming to impress.
AI Agent #5: COO Reporter Agency
Streamlining Data for Ali AI
Finally, our COO Reporter Agency, also for Ali AI, tackles data chaos. Users struggled to pull metrics from Google Analytics and other sources—slow and error-prone. We built a team of AI agents: a COO leading three interconnected helpers. Reports that took hours now take minutes, with fewer mistakes. It’s a symphony of collaboration, powered by our unique framework.
Generating Insights
I opened Gradio and requested data from November 2-29, 2024. The COO tapped the data integration agent, processing 5,000 rows from Analytics and Search Console. I asked, “What’s the traffic trend?” The team delivered users, sessions, and revenue stats. Then I pushed further: “Chart new vs. total users.” The report builder agent whipped up a graph—imagine a clean line spiking upward, vivid in blue and green. I requested PDF and Excel exports, and soon, Google Drive held two files: a technical spreadsheet and a sleek report with charts and insights.
Adaptability Is Key
At 12 cents per report, it’s a steal. The big lesson? Adaptability trumps rigid tools. Users tweak reports via chat, making them far more useful. It’s not just automation—it’s collaboration with AI agents that evolve.
Conclusion
These five AI agents—Facebook marketing, DNS support, questionnaire, Jack, and COO reporter—showcase tailored brilliance. Most started as custom fixes, or horizontal agents, built for specific needs. But as patterns emerged, like with the Facebook agent, we’re turning them into scalable, vertical solutions. Starting with horizontal AI agents gives you insights to productize later—a strategy that’s paid off for us. Costs stay low, results soar, and clients thrive. If you’re intrigued, we’re hiring—reach out via our site. This journey’s just beginning, and I’m excited to see where these AI agents take us next!
We strongly recommend that you check out our guide on how to take advantage of AI in today’s passive income economy.
