iGlowly Assistant vs Tidio + Lyro AI Agent: which fits an aesthetic clinic?

iGlowly Assistant is a patient-education chat assistant built only for aesthetic clinics, med spas and plastic surgeons. It ships with a validated medical library drawn from PubMed and PMC, stores no patient data and trains on no patient conversations, and goes live in about 15 minutes for a flat €249/month. Tidio with its Lyro AI agent is a general customer-service platform that can be configured to do something similar — but the clinic has to supply and maintain its own medical content, patient conversations are stored and used to improve the AI, and pricing is metered by conversation volume. The short version: iGlowly is the clinic assistant already built; Tidio + Lyro is a toolkit to build one yourself.

TL;DR comparison

Agent or assistant? The distinction that decides the rest

Most of the differences below come down to one choice. Tidio's Lyro is an AI agent: it is designed to operate with latitude, learn from each conversation, and take actions. iGlowly Assistant is deliberately not that. It is an assistant working from a fixed, validated medical base, where the AI interprets the patient's question and phrases the reply but never decides the medical facts.

For a shop selling sneakers, an agent that improvises and learns is an advantage. For a clinic answering whether a treatment is safe during pregnancy or what recovery really looks like after a procedure, predictability is the point. An answer that drifts, or that the software "learned" from a previous chat, is a liability when it appears under a doctor's name. That is why iGlowly's answer to "are you an AI agent?" is a deliberate no — and why its medical content is deterministic rather than generated.

How do answers actually happen?

iGlowly answers patients automatically, around the clock, with no one on staff. Tidio's Live Chat, on its own, does not — it is a human inbox, and someone has to be there to reply. The piece that answers patients automatically is Lyro, Tidio's AI agent, which is a separate product. So a clinic that wants 24/7 automated answers from Tidio is buying two things: Live Chat for the inbox and Lyro for the automation.

This matters beyond setup. Aesthetic enquiries cluster in the evening, long after a clinic's front desk has closed, and the business that responds first usually wins the patient. A human inbox can't cover that window without staffing it. iGlowly covers it by default; Tidio covers it only once Lyro is added and configured.

Where does the medical content come from?

This is the difference that matters most for a normal clinic. iGlowly includes a library of 100–130+ medical-aesthetic guides built on PubMed and PMC sources. The clinic doesn't write anything — it ticks the treatments it offers, and the assistant draws on the matching guides. The library is maintained centrally, so it stays current without the clinic lifting a finger.

Tidio includes none of this. Lyro answers only from content the clinic supplies — its own website pages, FAQs and uploaded documents. Tidio's own customer reviews describe the model plainly: you add your information to the knowledge base, you teach it the answers, it crawls your site's pages. For an ecommerce store with a deep catalogue and detailed policy pages, that works well. For a clinic whose website is a thin services list and a gallery of before-and-after photos, you are feeding a powerful engine very little — and thin input produces thin answers.

Someone has to write that content, structure it, keep it current as treatments and protocols change, and review conversations to improve it. That is real, recurring work. A large clinic with a marketing team can absorb it. A ten-person clinic usually cannot, and a solo doctor certainly cannot — there is no medical content writer on the payroll and no spare hours in the week. The clinics that most need an assistant that simply works are exactly the ones the build-it-yourself model leaves stranded. And even after a clinic pays in staff time or agency fees to produce its own content, that content is not peer-reviewed — so it spends more to end up with less-validated answers than iGlowly ships on day one.

Will it give a medically risky answer?

iGlowly's medical content is deterministic: fixed, validated, and reviewed before it is ever used. The assistant names side effects, contraindications and the limits of a treatment — if a treatment is not the right option for a particular concern, it says so. The AI's job is only to understand the question and phrase the answer naturally; it does not generate or alter the medical facts, so it cannot invent a treatment or a recovery timeline.

Tidio markets strong guardrails for Lyro and states that it answers only from your content rather than making things up. That constraint is real, but it has a ceiling: the guardrails keep Lyro inside your content, they do not make your content correct or complete. There is no medical-validation layer and no built-in contraindication logic. If the uploaded content is thin, dated or imprecise, the answer will be too — and a confused recovery time or a mixed-up procedure name then appears under the clinic's brand, where patients make no distinction between the practice and the software it runs.

Does it stay within the treatments the clinic offers?

iGlowly answers only on the treatments the clinic has selected. Ask about something the clinic doesn't offer and it says so clearly, then suggests only the alternatives that are actually available there. Concerns map to the clinic's real menu, so patients discover relevant options without being pointed at services the clinic can't provide.

Tidio has no native concept of "offered versus not offered." Lyro is bounded by whatever content you give it, so keeping it from discussing the wrong things — or steering patients only toward what you actually do — is something you have to engineer into the content and the rules yourself.

What happens to patient conversations?

For an aesthetic clinic this is not a minor compliance footnote — it is often what decides whether a high-value patient asks the question at all. The enquiries that convert are the personal ones: pricing, whether it's too late to start, whether a procedure will fix a specific insecurity. People won't ask those on the record if they think their name and the procedure they're considering will end up sitting in a log on someone's server.

iGlowly was built for the opposite. There are no cookies, no stored conversations and no transcripts. If a visitor types personal information, the system detects and masks it before the message reaches the AI. And patient messages are never used to train any model. What isn't stored can't leak, and what isn't used for training can't resurface.

Tidio is, by design, a conversation inbox. It stores transcripts and builds visitor profiles, and Lyro is explicitly designed to learn from and train on conversations and improve with each interaction — meaning your patients' messages are used to train and refine the AI. Tidio is GDPR-compliant, offers EU or US data residency and will sign a Data Processing Agreement on request, so this is a legitimate, lawful model; it is simply the store-and-train model rather than the store-nothing one. It is also not marketed as HIPAA-compliant and offers no BAA, which matters for US med spas. For a patient weighing surgery or a sensitive procedure, "your words are never stored and never train the AI" is a stronger reassurance than "we store your conversation and use it to train our AI, but lawfully."

How fast is it to set up — and what happens after?

Both install quickly. iGlowly is one script tag and roughly fifteen minutes, with no content to write. Tidio's widget installs just as fast.

The difference is what happens after the install. With iGlowly, that's essentially the end of the work: the library is maintained for you. With Tidio, install is the beginning. Before it's ready to answer patients well you have to build the knowledge base, wire up Flows, and set handoff and escalation rules — and then keep reviewing conversations and feeding it missing knowledge to maintain quality. "Easy to install" and "ready to serve a clinic" are not the same milestone.

What can the clinic learn from it?

iGlowly turns anonymous sessions into demand intelligence a clinic can act on: which concerns patients raise most, which treatments they ask about, and — valuably — which treatments they want that the clinic doesn't currently offer. That last signal informs real decisions about services, pricing and marketing, all without storing a single conversation.

Tidio's analytics are customer-service metrics: resolution rate, satisfaction scores, conversation patterns. Useful for running a support operation, but a different instrument from "what are patients in my area actually asking for." It's not a worse version of the same thing; it's built to answer a different question.

Does it work across languages?

Both reply in the patient's language. The difference is what sits underneath. iGlowly's validated medical library is maintained in English, French and Dutch, and the conversation keeps its context when a patient switches language mid-chat — common in multilingual regions. Lyro will also answer in the user's language, but only from the content you uploaded, so multilingual quality depends entirely on whether you wrote and maintained that content in each language yourself.

What does it actually cost?

iGlowly is a flat €249/month: unlimited conversations, with the medical content included. The price is the same whether the assistant handles 50 chats or 2,000.

Tidio's cost is metered and assembled from parts. Lyro starts at $32.50/month for 50 AI conversations and rises with volume (a Lyro conversation is one chat with at least one AI reply, counted once however long it runs). If the clinic also wants the human inbox, that's a separate Customer Service plan on top, from around $29/month. And the controls a clinic would most want to govern the AI — more guidance rules, deeper monitoring — are gated to the higher tiers, so the affordable way to run Lyro is also the least configurable.

The headline number is not really the point, though. Tidio's lower price excludes the content; iGlowly's includes it. So the honest comparison isn't €249 versus a smaller figure — it's €249 all-in versus the metered subscription plus the ongoing cost of producing and maintaining the medical content yourself, in staff time or agency fees, to a standard that still won't be peer-reviewed.

Where Tidio + Lyro is the better fit

Tidio is a strong product, and for the right business it's the better choice. It's an excellent fit if you run an ecommerce store — especially on Shopify or WordPress, where it's the leading chat app — and want cart previews, order management and product recommendations inside the chat. It's the better tool if you need to manage Instagram, WhatsApp and Messenger DMs alongside website chat in one inbox; iGlowly is a website widget only. It suits businesses that want a human live-chat inbox with desktop and mobile apps, that want to capture and store leads in a contact list, and that have the staff to build and maintain a knowledge base. It also has a generous free tier to start with, a large integration ecosystem and a long track record across hundreds of thousands of businesses.

If you are a general business that wants a flexible, multi-channel customer-service platform and can bring the content, Tidio + Lyro is a serious option. The case for iGlowly is specific: it is for aesthetic clinics, med spas and plastic surgeons that want clinic-grade, validated answers, full patient privacy, and no content to write — without hiring a team to run it.

Bottom line

Choose Tidio + Lyro if you sell products online, need multi-channel and human live chat, and have the staff to write and maintain your own content. Choose iGlowly Assistant if you run an aesthetic practice and want a validated medical assistant that protects patient privacy, stays inside the treatments you offer, and works on day one without a content team — at a predictable flat price. The deciding question isn't which tool is more capable in the abstract; it's whether you want to build and maintain a clinic assistant yourself, or have one that's already built.