Short answer: Hire an AI agency based on shipped production work, senior engineers you'll actually talk to, and clear ownership of code and IP — not on flashy demos or the lowest hourly rate. The biggest red flags are vague scoping, no real deployments, and reluctance to put pricing or IP terms in writing.

AI is the easiest thing in the world to demo and one of the hardest to ship reliably. That gap is exactly where projects go wrong. Here's how to choose an AI development agency that actually delivers — and the warning signs to walk away from.

What to look for in an AI agency

1. Production work, not just demos

Anyone can wire up a chatbot in an afternoon. Ask to see systems running in production with real users — handling errors, scale, and edge cases. Ask "what broke, and how did you fix it?" Real builders have war stories; demo-makers don't.

2. Senior engineers you'll actually work with

In many agencies, a senior closes the sale and juniors do the work. Confirm who writes your code and that you'll have direct access to them. Founder-led and senior-led teams ship faster with fewer surprises.

3. Clear scoping

A good agency turns "we want AI" into a specific, scoped first deliverable with a timeline and a number. If they can't explain what they'd build first and why, they'll discover the scope on your budget.

4. They start with the simplest thing that works

Good engineers reach for the cheapest effective solution — usually RAG before fine-tuning, managed APIs before custom infra. Beware anyone who proposes training a custom model on day one; it's rarely necessary and always expensive.

Red flags to avoid

  • Vague pricing. If they won't give a range or put it in writing, your budget is the variable.
  • No deployments to show. Slideware and Figma mockups are not shipped software.
  • They won't give you the code. You should own 100% of source and IP. Get it in the contract.
  • "AI for everything." If every answer is "add an LLM," they're selling hype, not solutions.
  • No talk of evals, monitoring, or guardrails. Production AI needs all three. Silence here means a demo, not a product.
  • Account-manager wall. If you can't talk to the engineer, communication will be slow and lossy.

Questions to ask before you sign

  1. Who exactly will write the code, and can I talk to them?
  2. Can you show me a similar system running in production?
  3. What's the simplest first version you'd ship, and what does it cost?
  4. Who owns the code and IP when we're done?
  5. How do you handle reliability — evals, monitoring, fallbacks?
  6. What are the ongoing monthly costs after launch?

How Kortex Labs works

We're founder-led and senior by default — you work directly with the engineer building your product, with no account-manager layer. We scope a sharp first deliverable, quote a fixed range, and hand over 100% of the code and IP. We've shipped LLM platforms, real-time event systems, and data pipelines in production, so you're hiring delivery, not a pitch.

Evaluating agencies for an AI build? Send us your project and we'll give you an honest scope and a free quote within 24 hours — even if we're not the right fit, you'll leave with a clearer plan.

Once you know what to look for, the next question is budget — see how much it costs to build an AI app.