Stella Reads Your Website So Your Visitors Don't Have To

Most websites are quietly failing a simple test. A visitor arrives with one question - how much does this cost, do you serve my town, where do I file this permit - and instead of an answer, they get a search bar, a menu, and eventually a phone number. Stella's founder looked at that gap and decided the answer was already on the page. The site just needed someone to read it out loud.

Stella is an AI assistant that installs on a website with a single line of code and answers visitor questions around the clock. It learns from a site's own public content - the FAQ nobody scrolls to, the policy page buried three clicks deep - and turns that material into a conversation. The company is backed by Y Combinator (S22) and run by Ryan Endacott, who before this built mission-control software at Loon, the Google X project that beamed internet down from stratospheric balloons.

Stella is more than a chatbot. It's an instant, intelligent companion ready to engage your website visitors the moment they arrive.Stella company site

01 / What it actually doesAn answer engine, not a maze

The pitch is narrow on purpose. Stella does not promise to run your business or replace your staff. It reads what you already publish and answers questions about it, in plain language, in multiple languages, styled to match your brand's colors, logo, and voice. When a question is too complex - a specific case, a hand-off, a lead worth a human - it routes to the right person or department instead of guessing.

That restraint is the strategy. A small business does not need artificial general intelligence to handle the same five questions forty times a day. It needs a good librarian who never clocks out. Stella's bet is that retrieval, done politely and reliably, is worth more than cleverness.

The mechanics are ordinary in the way good tools tend to be. You paste a snippet into your site. Stella crawls your public pages, builds an understanding of them, and starts answering. There's a dashboard where you can watch conversations, correct a bad answer, or add knowledge the site doesn't cover. Integrations push conversations and leads into tools a team already uses, like Slack and HubSpot, so the AI isn't a silo bolted to the corner of the page. None of that is exotic. The discipline is in leaving out everything else.

02 / The proofA New York town let an AI answer the phone

The most useful thing about Stella is that you don't have to imagine how it performs. The Town of Carmel, NY deployed it on the town website, and the numbers are specific. Residents held more than 1,590 conversations. Stella answered over 2,417 questions. Nearly three-quarters resolved automatically, with no staff involved. The town estimates it saved more than 200 hours of employee time - hours that used to go to repeating where the permit form lives.

Integrating Stella into our existing systems was surprisingly straightforward. We were up and running quickly, with minimal disruption to our daily operations.Kevin Kernan, Town of Carmel

It's a telling flagship customer. Governments are cautious buyers, answerable to voters, and slow to trust software with their public face. That a town clerk describes the rollout as painless says as much about the product as any benchmark. Town Supervisor Michael Cazzari put it plainly: Stella is "making town resources easier to find."

03 / Who it's forSmall shops, SaaS apps, and town halls

Stella wears three hats. For small businesses, it's the support desk they could never afford to staff overnight. For SaaS companies, it helps prospects understand a product on their own terms - and, quietly, shows the team exactly what those prospects are confused about. For local governments, it fields the permit-and-service questions that clog the phone lines. Named customers include the Town of Carmel, the Association of Towns of the State of New York, Springbrook, and Book't.

The three audiences look different but share a shape: each has more questions coming in than people to answer them, and each already has the answers written down somewhere. A dentist's office and a town clerk's desk are not obviously the same market. Under the hood, they're the same problem. That's why one product can serve all three without forking into three products - a rare piece of leverage for a team this small.

04 / The modelFree to start, priced not to sting

Stella is subscription software, tiered by how many answers you need each month. It starts free, which matters: the biggest obstacle to adopting an AI tool is rarely the price, it's the effort of trying. A free tier and a one-line install remove both. From there it scales up to custom enterprise contracts with unlimited chatbots and dedicated support.

Pricing as published on chatwithstella.com. Subject to change.

05 / The differenceKnowing less, on purpose

The crowded field around Stella splits in two. On the government side sit specialists like Citibot, Polimorphic, and GovBot. On the business side sit general website chat tools - Intercom's Fin, Ada, and a growing pile of do-it-yourself widgets. Stella's edge is that it straddles both with the same product and one deliberate constraint: it learns only from a website's public content.

In a moment when AI products compete to ingest as much data as possible, choosing to know less reads as a feature. For a town answerable to residents, it's the difference between a tool they can defend and one they can't. Trust, here, is the moat.

The timing raises the stakes. In early 2026, municipal AI chatbots drew a wave of press scrutiny, with reporters testing city assistants and finding some deployed by governments that couldn't quite explain what they'd bought or how it spoke for them. That's the environment Stella is selling into. Its answer - stay narrow, learn only what's public, route the hard cases to humans - is less a marketing line than a survival trait. A chatbot that invents policy is a liability. One that reliably points to the policy already written is an asset.

We're thrilled to support Carmel as they use Stella to make local government more accessible.Ryan Endacott, Founder & CEO

06 / The founderFrom balloons to the browser

Endacott's route here is unusual. He studied computer science at the University of Missouri, co-founded a hackathon that still runs, then spent years at Google X on Loon, building the systems that kept internet balloons flying. His YC S22 company began as a crypto-payments product for Discord before the work turned toward AI and, eventually, Stella. The through-line is a builder drawn to the same question in different forms: how do you get useful information to the person who needs it, wherever they are?

That background shows up in how the product is scoped. Loon was an exercise in reliability under uncomfortable conditions - keep a fragile thing working when a person can't reach it to fix it. A chatbot on a town homepage has a milder version of the same demand: it has to behave when nobody's watching, at 2 a.m., for a resident who will judge the whole town by the answer. Building for that constraint tends to make you conservative about what you promise. It's a useful instinct to bring to a category full of tools that promise everything.

07 / Where it fitsThe unglamorous, profitable middle

There's a familiar startup instinct to chase enterprise logos and ignore the dentists, town halls, and two-person SaaS shops that would pay today. Stella went the other way. Its reference customer is a town, its entry price is a coffee-a-week, and its ambition is narrow enough to actually deliver. Whether it stays a tidy niche or grows into something larger will depend on how many organizations decide the answers on their website deserve a voice. For now, at least one town would tell you it was worth a line of code.