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Trained on billions of lines of public code, GitHub Copilot puts the knowledge you need at your fingertips, saving you time and helping you stay focused.
Callout uses AI to perform first-pass construction drawing reviews against building codes and standards. Upload your PDF drawing sets, select from 33+ supported codes across 7 engineering disciplines (mechanical, structural, architectural, electrical, plumbing, energy, fire protection), and receive a structured list of findings in seconds.
Each finding includes a severity rating (Critical, Major, Minor, Advisory), confidence level (High, Medium, Low), exact code section citation, and a suggested resolution. Licensed PEs review each finding and accept, reject, or edit it. Over time, Callout learns from those decisions and adapts future reviews to match each engineer's judgment, without any model fine-tuning.
Key features:
-Multi-discipline single-pass review: check drawings against codes from all 7 disciplines in one run -Firm standards library: add plain-English firm-specific requirements that get checked alongside model codes -Jurisdiction amendments: upload local or state code amendments and cross-reference them against base codes -Confidence ratings: each finding signals how reliable the citation is, helping PEs triage efficiently -Export and sharing: CSV, Excel, and PDF export, plus read-only shareable report links for team collaboration -Organization support: shared credit pools, role-based access, firm-level calibration, and audit logging
Pay-per-use pricing with no subscription. Credits never expire. 50 free credits on signup, no credit card required. Built by a licensed Mechanical PE.
GitHub Copilot
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Callout.app's answer:
Callout learns from each engineer's decisions. When a PE accepts, rejects, or edits a finding, that feedback shapes future reviews to match their judgment. Over time, each engineer gets a personalized review profile without any model training. Combined with firm-specific standards, jurisdiction amendments, and multi-discipline single-pass review across 33+ codes, no other tool offers this combination.
Callout.app's answer:
Most tools in this space are either digital markup tools (Bluebeam, PlanGrid) that don't analyze drawings, or code lookup tools (UpCodes) that don't review uploaded plans. Callout is the only tool that takes a PDF drawing set, reviews it against building codes from all 7 engineering disciplines in one pass, and returns structured findings with exact code citations and severity ratings. It's also pay-per-use with no subscription, so you only pay when you use it.
Callout.app's answer:
Licensed Professional Engineers and MEP firms who review construction drawings for code compliance. The typical user is a PE at a small to mid-size engineering firm who reviews mechanical, structural, electrical, plumbing, or fire protection drawings and wants a faster first pass before stamping.
Callout.app's answer:
Built by a licensed Mechanical PE who spent too many hours doing manual code compliance reviews. The idea was simple: AI is good at cross-referencing documents, and building code review is fundamentally a cross-referencing task. Callout started as a tool to speed up the founder's own review workflow and grew into a product for the broader engineering community.
Callout.app's answer:
Next.js, Anthropic Claude API, Supabase (PostgreSQL), Stripe, and Vercel.
It definitely increases my productivity.
Based on our record, GitHub Copilot seems to be more popular. It has been mentiond 387 times since March 2021. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.
Where llms.txt genuinely gets read is a different layer: coding and agent tooling โ Cursor, Claude Code, GitHub Copilot, Windsurf โ pulling a documentation site's pages with less token waste, plus emerging agent protocols like OpenAI's Agents SDK. That's real, and it's growing fast. - Source: dev.to / 8 days ago
You need an active GitHub Copilot subscription. Plans are available at individual, business, and enterprise tiers at github.com/features/copilot. Once active, all tools use your GitHub account credentials. - Source: dev.to / about 1 month ago
For over a decade PhpStorm (starting in my WordPress era) and later WebStorm have been my main IDEs for web development. So when GitHub Copilot launched, it was a natural choice to try it out in WebStorm. It was one of the first AI coding tools I used, and it had a big impact on how I thought about AI-assisted coding. - Source: dev.to / about 1 month ago
Before we get into it, there are some things about AI usage worth addressing. I've had my fair share of scepticism in the past, but recent model releases have made it increasingly difficult to argue that AI isn't a viable tool for the majority of workstreams, including building user interfaces. Most large language models are trained on public data scraped from the internet, which means your internal design system... - Source: dev.to / about 1 month ago
Most developers still treat GitHub Copilot like a very good autocomplete engine. That's useful, but it's not the real unlock. - Source: dev.to / about 1 month ago
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