tremblaybois.ca/
Tremblay Bois avocats, cabinet d'avocats, Québec
Not read yetPage 1 of 25
Answered today by a language model from a live web search. Search results change, so a re-run can differ.
Asked of a language model without live browsing — what the model has absorbed about this market, not a search result fetched today.
Being listed on these puts you where an assistant reads before it answers. None of them does the work you do.
Put to a live web search — the pages an assistant reads before answering. Absent from these results it cannot cite you; present, it still might not.
Le point fort du site est la sécurité (Security = 94/100), ce qui protège les données sensibles des clients. Le principal frein est l’AI‑answer‑engine readiness (AEO = 9/100), indiquant que les réponses juridiques du site ne sont pratiquement pas exploitées par les LLM. Implémenter des données structurées Produit, Offre et AggregateRating (exposer prix, disponibilité et notes) permettra d’améliorer l’AEO et le GEO, et de rendre le contenu plus exploitable par les IA.
Ask it what a customer would ask you. It answers only with what is written on the pages of tremblaybois.ca.
Hello! I’m the assistant for Tremblay Bois avocats, cabinet d'avocats, Québec. What would you like to know?
A Tadaaah demo. This is an AI assistant: it can make mistakes.
$29 CADa month, on top of PRO
This looks like an online store, but no Product schema was found. AI shopping answers and Google Shopping rely on it to understand your items.
Do: Add Product JSON-LD to product pages with name, image, description, brand, and an Offer (price + availability).
No Offer markup (price / availability) was detected. AI answers cite concrete price and in-stock facts.
Do: Include an Offer node (price, priceCurrency, availability) inside each Product.
No AggregateRating/Review markup was found. Star ratings and review counts are among the strongest signals AI shopping answers surface as social proof.
Do: Collect product reviews and expose them as AggregateRating (ratingValue + reviewCount) in Product schema.
The page links to no outside source. Pages that cite verifiable third parties are the ones generative engines treat as grounded rather than promotional.
Do: Link the things you can point at: a materials or certification standard, the maker you buy from, press that covered you, the association you belong to.
Only 2 Google review(s) detected — thin social proof for the local pack.
Do: Ask happy customers for Google reviews; a steady stream (20+) builds real local trust.
No LocalBusiness JSON-LD was found — search engines can't confidently tie this site to a physical business or place.
Do: Add a LocalBusiness (or the closest subtype) JSON-LD block with name, address, telephone, geo and openingHours. Your Schema Fix Pack can generate it.
No AggregateRating/review markup was found — star ratings drive clicks in the local pack.
Do: Surface your existing Google reviews on the page as an AggregateRating (real, verifiable counts) so search engines and AI see the proof.
Automated snapshot generated by Tadaaah from public data. Re-run the audit for the latest version.