About Snipget

We're the utility toolbox AI agents reach for; built by developers tired of writing the same helpers into every new app.

We've been here before

Between us, we have decades of experience building data pipelines, healthcare platforms, and automation systems. And in every single project — without exception — we ended up building the same things: address parsers, phone normalizers, entity matchers, credential validators, jurisdiction resolvers. Not because it was interesting work. Because it had to be done, and we knew better than to skip it.

Then AI agents arrived. And suddenly the plumbing got harder, not easier. Now we were building those same utilities and  wrapping them in agent-discoverable APIs so the LLM could actually use them reliably. Project after project. The same detour, every time.

We got tired of it. So we built it once, properly, and opened the door.

The problem nobody warns you about

Large language models are remarkable. They're also confidently wrong about things code can compute exactly. Ask an LLM to normalize a phone number, validate an identifier, or resolve a jurisdiction and you'll get a plausible answer — one that looks right, passes a quick glance, and silently fails when it hits the real world. You won't always know which answers are wrong. That's the problem.

Builders with thirty years of scar tissue know to put a defensive layer between AI output and anything that matters. They've been burned enough times to wire it in early. But developers who are newer to the craft — or building on no-code and low-code platforms — often don't know that layer needs to exist. They find out the hard way, and the bugs are subtle enough that they don't always know why.

Snipget is that defensive layer, pre-built. Whether you've been doing this for thirty years or thirty days.

What we believe

• Programmatic over generative. When a thing can be computed, compute it. Utilities should never call LLMs.
• Every utility included. No feature tiers. Pricing scales on usage, not capability.
• Consistency is the product. Every endpoint returns the same envelope. Every error is the same format. Agents shouldn't have to special-case us.
• Tiny utilities matter. A huge catalog of small, fast helpers is a feature, not filler. Agents discover what they need.
• New builders deserve guardrails. The mistakes that come from trusting LLMs with routine data tasks are predictable and preventable. We want to prevent them.

The company

Snipget is built and operated by Snipget Inc. — a small team of developers and data engineers who have spent decades building the things AI agents get wrong. We ship carefully, stay close to our users, and genuinely believe the toolbox we wished existed is worth building for everyone.