AI Development, From a Team That Actually Ships AI
We build AI into products for a living: agents, generative AI, LLM and RAG features, and AI wired into apps you already have. This isn't slideware. We run AI in our own SaaS, we operate our own AI agents every day, and we've delivered AI workflows for a client. When we say we can build your AI, it's because we already did.
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How to tell who can actually build your AI
AI development is on almost every homepage now, and that's a good thing. It also makes one thing genuinely hard: knowing who can actually deliver. "AI" can mean a production system real users depend on, or it can mean a demo. From the outside, they look the same.
Here's the question we'd ask in your shoes: what AI does the team actually run themselves? Not what they'll pitch for your project, but what they've already put into production and rely on every day. That one answer tells you more than any capabilities deck.
For us, it's an easy question to answer. We build AI into Formester, our own live SaaS. We run three AI agents to operate this company. And we've delivered AI workflows for a paying client. So when we say we can build your AI, it's because we already have, for ourselves and for someone else.
What we actually build
Real AI capability inside real products, built to do actual work.
AI Agents & Agentic Workflows
Agents that take real actions like generating and sending emails, scoring and analyzing data, and triggering downstream steps. Not chatbots that just talk. See AI agent development.
Generative AI Features
Text and content generation wired into your product's real workflows, with the guardrails and evaluation that keep the output usable in production.
LLM & RAG (Knowledge-Grounded)
Retrieval-augmented generation grounded in your own knowledge base, so answers are based on your data. Architected to scale as the dataset grows.
AI Chatbots That Do Real Work
Assistants that don't just answer. They look things up, take actions, and hand off cleanly when a human is needed.
AI Into Your Existing Product
You already have an app. We wire AI into it, including the features, the plumbing, and the infrastructure to run models reliably, without a rebuild.
We Build AND Fix AI
We ship AI features and we fix broken AI-built apps. If you built something with AI and it's breaking, that's AI App Rescue.
Proof, not promises
Anyone can list "AI development services." Almost no one can point to shipped AI they run themselves. We can.
Formester: AI in our own product
Formester is our live SaaS form builder, rated 4.7/5 on G2 across 13 reviews. It lets people build and edit forms with AI, and over 800 forms have been created with it. On top of that we run agentic post-submission workflows (generate emails, score and analyze submissions, custom actions) and a RAG system that grounds answers in a fed knowledge base. Real AI, in production, used by real businesses.
Our internal AI agents
We run our own company on agents we built. Freddy is our finance agent. It creates invoices, sends emails, and runs the numbers. We also run a dev agent that fixes bugs and a code-review agent that reviews code. We don't just build agents for clients. We bet our own operations on them.
PerformLine: AI delivery for a client
PerformLine builds AI solutions for compliance monitoring, flagging content that breaks the rules. We've been their engineering partner for 2+ years, growing from one engineer to eight-plus. It's our proof that we deliver AI for paying clients, not just for ourselves.
We don't sell cheaper. We sell speed and certainty.
The honest version of what AI changed for us: what used to take about four months now takes about one. We didn't get cheaper. We got faster, and the quality went up. That's because we know how to code and how to drive AI. That pairing is rare, and it's what separates a working AI feature from a fragile one.
If you're shopping purely on price, we're probably not your team. If you want AI shipped fast, correctly, and reliably, that's exactly what we do.
You might not need us if…
- A no-code or off-the-shelf AI tool already does the job. If ChatGPT, a Zapier AI step, or an existing SaaS covers your use case, use it. Don't pay us to rebuild it.
- You're bolting a single API call onto a side project. One OpenAI call in a weekend app doesn't need an engineering team. Ship it yourself.
- You can build it yourself with AI and you have the time. For some people, DIY-with-AI is genuinely enough. We'll tell you honestly when you're one of them.
We only want to work with people who genuinely need what we do. If that's not you yet, we'll say so. That candor is the whole point.
How we build AI (and keep it from breaking)
Most AI projects don't die in the demo. They die on the way to production. Our process is built around shipping, not showing.
Scope the real use case
We start by pressure-testing whether AI is even the right answer, and where it actually creates value. If a simpler solution wins, we'll tell you.
Ground it in your data
RAG, knowledge bases, and the right context so the model works from your reality, not generic internet averages.
Build
Agents, features, or plumbing, built into your product with the same engineering discipline we bring to any production system.
Eval & guardrails
We measure whether the AI actually does the job, and add the guardrails that keep it safe and predictable when real users hit it.
Ship & monitor
We get it to production and watch it there. AI behaves differently under real load, and monitoring is how you catch that early.
The line between a working AI feature and a fragile one is whether the team knows how to code as well as how to drive the AI.