What AI Projects Should Cost — And Why Yours Are Overpriced

Following up on my recent posts on small language models, I wanted to delve again into how they are revolutionizing business. 

AI has entered the enterprise — but not always in the way it should. Too many companies are spending too much money on “AI transformations” that deliver too little value. 

Bloated roadmaps. Months of discovery. Proofs of concept that never become production. And somewhere along the way, half a million dollars vanishes without a single process getting faster. 

Let’s be clear: most enterprise AI is overpriced, overbuilt, and under-delivered. 

Here’s what it should cost — and why our model delivers better outcomes at a fraction of the price. 

What You’re Being Sold (and Why It’s Broken) 

The typical AI pitch goes like this: 

• Spend $100K–$500K to explore “opportunities” 

• Build a proof of concept 

• Expand the team 

• Try to scale something six months later 

• Never reach ROI 

Why? Because most firms: 

• Start with LLMs trained on public data (hallucination risk) 

• Focus on experiments, not delivery 

• Treat every problem like a custom software build 

• Want to embed long-term consultants, not solve and exit 

The result? Beautiful slide decks. No working product. 

What AI Should Actually Cost 

Let’s use some actual numbers. A properly scoped, business-facing AI project should cost: 

• $5K–$25K for a fixed-scope engagement 

• Deliver a working tool (not a pilot) 

• Be completed in 2–4 weeks 

• Run securely on your data 

• Require no ongoing support contract 

That’s how our SLM-based solutions work. We build them fast, make them yours, and move on. 

Real Projects, Real Prices 

Here’s what some of our clients have paid — and what they got: 

Use Case	Timeline	Cost/Outcome
Matching 1000s of invoices	3 weeks	$5K/140 hrs/mo saved
CFO dashboard	2 weeks	$5K/20 CFO hrs saved

These aren’t toys. These are tools — shipped, working, and owned by the client on Day 1. 

Why the Pricing Model Matters 

We don’t want to “partner.”  We don’t want to “explore use cases.”  We want to solve the problem you already know you have. Then we’re out. 

That’s why our pricing model is transparent and fixed-scope. We don’t grow by inflating hours. We grow by finishing jobs and earning the next one. 

Bottom Line 

If your AI vendor can’t show you a working tool in the first week and a fixed price for the result, they’re not selling delivery — they’re selling dependency. 

We’re different.  We scope tight, build fast, and hand you the keys.  No fluff. No hallucinations. No consultants hanging around forever. 

That’s what AI should cost — and that’s exactly what we deliver.