Everyone is telling you to add AI. We’ll tell you if you should — and where.
You’ve built a product. It works. It has users. Now your investors have questions, your competitors are shipping “AI-powered” features, and your team is fielding requests to add things nobody has fully defined yet.
Before you commit engineering time to a direction, it’s worth finding out what AI actually means for your specific product — not in general, not as a trend, but for what you’ve built and who uses it.
Most startups don’t have an AI problem. They have a clarity problem. The question isn’t whether to use AI — it’s whether it fits, where it fits, and what it would take to get there from where you actually are today.
Two steps. You decide how far to go.
AI Reality Check · Entry point
An honest assessment of where AI fits in your product.
We look at what you’ve built — your architecture, your data, your workflows, your users — and give you a clear picture of where AI genuinely adds value and where it doesn’t. Not a hype-driven roadmap. Not a vendor recommendation. A practitioner’s view of what’s realistic, what’s worth pursuing, and what you can probably skip.
The output is a written assessment you can share with your team and your investors. Fixed scope, fixed fee. No retainer required — this step stands alone if that’s all you need.
Build
We help you build what the assessment identifies.
If the Reality Check surfaces a clear opportunity — a feature, an integration, a change to how your product handles data — we can stay on and help build it. Hands-on, embedded, shaped entirely by what we found in step one. No predetermined solution, no preferred stack. We build what fits.
What we actually look at
Your data. AI is only as useful as the data it runs on. We look at what you have, how it’s structured, and whether it’s in a shape that makes AI features feasible — or what it would take to get there.
Your workflows. Where does your product make decisions today? Where do users get stuck, make mistakes, or ask for help? Those are often the places where AI earns its keep — and where it’s hardest to bolt on after the fact.
Your architecture. Some products are one integration away from something genuinely useful. Others have structural constraints that make AI features expensive to ship correctly. We’ll tell you which camp you’re in.
Your team. An AI feature your team can’t maintain is a liability. We factor in what you have — engineering capacity, existing tooling, operational maturity — so the assessment is actionable, not aspirational.
What you won’t get
We don’t have a preferred AI vendor. We don’t benefit from recommending one model provider over another, one vector database over another, one framework over another. The assessment reflects what fits your situation — not what someone is paying us to recommend.
We also won’t tell you AI is the answer if it isn’t. Some products genuinely benefit from LLMs and agents. Some are better served by deterministic logic, better structured data, or just a cleaner API. You’ll get a straight answer either way.
Start with the Reality Check.
Tell us what you’ve built, what you’re being asked to do with AI, and what’s making you uncertain. A paragraph is enough.
info@shippingbytes.com · subject: "AI Reality Check — [one line about your product]"
We respond personally. No forms, no account managers.