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AI Visibility Scorecard
architech.ca · Professional Services
Somewhat visible. AI bots can read Architech, but it is missing the structured signals that push citation rate above competitors.
AI engines read this profile 3 times
Claude · Meta AI
#1,998 of 468,997 in Professional Services for AI visibility
6.6
/10
AEO Score
from our crawl and measurement
"AI-first workflow redesign and engineering firm. Architech redesigns the workflows that drive cost, speed, and growth, and engineers them into production-grade AI systems." That is how Architech of Toronto, ON introduces itself. To AI engines like ChatGPT and Perplexity it is partially visible, scoring 6.6 out of 10, readable in places, missing in others.
On the page, the fundamentals are in place: structured data on the page (Organization, ProfessionalService, WebSite), an llms.txt file for AI models, a sitemap.
AI crawlers have visited the site 3 times in our tracking, so the engines are already looking.
Higher is better · 0-10
Structured Data
10
Organization / LocalBusiness JSON-LD that AI can read.
Content Structure
10
Clear headings and answer-style content.
Entity Clarity
10
How clearly your brand identity reads to AI.
E-E-A-T Signals
Experience, Expertise, Authority, Trust
4
Experience, Expertise, Authority, Trust markers.
Technical AEO
10
robots.txt, llms.txt, and AI-bot crawl access.
AI Discoverability
8
Sitemaps and entity links AI can follow.
How the web signals your brand to AI
Backlinks
9
Inbound links from other sites.
Domain Trust
3
Established authority for your domain.
Entity Presence
0
Not in AI knowledge graphs yet.
News Mentions
0
No press coverage found yet.
Community
0
No community discussion yet.
0
No Reddit mentions found yet.
Your AEO score measures whether AI search engines - ChatGPT, Claude, Perplexity, Gemini - can actually read your site and cite it in answers. Roughly two-thirds of sites are invisible to them. At 6.6/10, Architech has a working base to build on - fixable, and the signals above are where to start.
Do I need to get all my data ready before starting?
No. The AI Foundations Sprint defines the secure access pattern in 2-3 weeks, validates it against real operational data in a controlled environment, and produces the reference architecture every subsequent workflow uses. Data readiness is part of the engagement, not a prerequisite to it.
How long does this take?
Each stage is time-boxed. AI Jumpstart: 2-3 weeks to a scored workflow shortlist and defined Proof of Value. AI Foundations: 2-3 weeks to a validated access pattern and executive go/no-go decision. Transformation Sprint: 3 weeks to a plan of record and measurement baseline. A production Proof of Value typically follows in 3-4 weeks. First proof of value in production within 5-7 weeks is the typical path.
What if we have already started AI work?
The right entry point depends on where the work has stalled. Approved roadmap with no plan to deploy → Transformation Sprint. Security, governance, or data access blocking the work → Foundations. Workflows shipped but KPIs slipping → Outcome Assurance. Licences bought without measurable ROI → Jumpstart reframes the problem around workflow outcomes, not tools.
How do you measure results?
Evaluation is tied to your business KPI, not model behaviour. A model can score high on relevance and groundedness while cost-per-resolution drifts back to baseline. Architech builds a Golden Dataset of real queries and verified expected outputs with your SMEs, tests semantic behaviour, structural integrity, and end-to-end correctness independently, runs the dataset on a defined cadence, and adds every regression back so it cannot recur. Drift is caught in engineering before it surfaces in the P&L.
Do the stages need to be sequential?
No. Foundations and Jumpstart frequently run in parallel. Some workflows move directly from Jumpstart into Transformation. Transformation Sprint and Build are sold separately, so the plan stands on its own before any commitment to deliver. Outcome Assurance runs continuously after deployment - it is a discipline, not a stage.
How is this priced?
Each engagement is structured as a fixed scope with a defined deliverable. The Transformation Sprint is success-based: acceptance criteria are confirmed in Week 1, and if outcomes are not accepted at the end, no fee is charged. Capital follows confidence.
Are Sprint and Build a single contract?
No. Sprint and Build are sold separately. Each Sprint produces a decision-ready output that stands on its own. The Build follows when the plan is approved, using the same architecture, baselines, and acceptance criteria established during the Sprint. There is no upfront commitment to the full arc.
What keeps results from drifting after launch?
Most enterprise AI projects miss their KPIs by month six. Outcome Assurance is the discipline that prevents it: continuous evaluation tied to your KPI, a Golden Dataset that grows across the engagement lifecycle, regression sets that prevent recurrence, and a dedicated team accountable for the outcome metric month-over-month. The number on the P&L holds for as long as you own the workflow.
Is this your brand?
The exact fixes for Architech
Which AI engines already crawl you
Weekly ChatGPT & Claude citation tracking
Your potential customers are asking ChatGPT, Gemini, and Claude questions about your product category. These AI models are giving answers without sending traffic to your website. You're not losing rank. You're losing visibility entirely.
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Scored by Engagemii on August 1, 2026. Methodology: engagemii.com/aeo/methodology
Source URL: https://engagemii.com/aeo/brands/architech-ca
Cite this score: Engagemii (2026). "AEO Score for Architech." Retrieved from https://engagemii.com/aeo/brands/architech-ca
Licensed under CC BY 4.0. You may reuse this data with attribution: a visible link to engagemii.com.
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