Your firm has people.
What it needs is clarity.
Most AEC firms aren't short on technology. They're short on the expertise to evaluate it, implement it, and actually get data value out of it. We help firms cut through the noise — from tool selection to AI strategy to custom-built dashboards — with the perspective of a team that's spent years at the intersection of architecture, UX research, and data engineering.
Technology should move business metrics — not just check a box.
AEC firms don't need more tools. They need a strategy that ties technology to outcomes that matter — win rate, overhead, utilization, revenue, positioning. We work backwards from the business goal.
How we work
Every engagement starts with the business — not the tool. Three phases keep technology decisions tied to outcomes.
Before any tool conversation, we name the problem in plain terms — what's broken, who's affected, and what changes if it gets fixed. The brief drives everything downstream.
Time saved, error rate, throughput, win rate — pick the numbers that prove the work. We capture the baseline up front so ROI isn't a guess at the end.
Tools, workflows, training, and change management — sequenced for your firm's reality. We build for how you deliver, not how a vendor wishes you did.
Five ways to work together
Engagements are scoped to your actual situation — not a pre-packaged software subscription.
Technology Assessment
A clear-eyed assessment of where your firm stands with AI, and where you should go next. No vendor upsell. No jargon. Just an honest written report with specific recommendations from the AEC Hub catalog.
- →90-minute discovery call — your workflows, pain points, current stack
- →Written audit report: gaps, redundancies, and 3–5 specific tool recommendations
- →Implementation priority matrix ranked by impact vs. effort
- →One async follow-up (email/Loom) within 2 weeks
- →Assessment fee credits 100% toward any deeper engagement
AEC Tech Advisory Sprint
A focused 3–4 week engagement to build a decision-ready AI or technology strategy. You leave with a documented roadmap your team can actually execute — not a slide deck full of buzzwords.
- →Current-state workflow analysis across target project phases
- →Tool selection matrix: shortlisted options evaluated against your criteria
- →AI implementation roadmap with 90-day quick wins + 12-month vision
- →Build vs. buy recommendation with rationale
- →ROI projection framework using your firm's actual numbers
- →Two live working sessions + async support throughout
Fractional Data & AI Lead
Ongoing strategic support for firms that need someone thinking about data and technology — but can't hire a full-time Chief Data Officer. Expert-level thinking without the overhead.
- →Monthly strategy sessions (2–4 hrs/month) with async availability
- →Ongoing tool vetting as new AEC products launch
- →Help translating your firm's data into actionable dashboards and reports
- →Input on RFP decisions, vendor evaluations, and procurement conversations
- →Direct access (no account manager layer) via email, Loom, or Slack
AEC Market Intelligence & Custom Dashboards
Custom data research, market analysis, or interactive dashboards built from your firm's own project and operational data. Turn the information you already have into something your leadership can actually use.
- →Custom market research: sector trends, regional AEC activity, tool adoption benchmarks
- →Internal data analysis: utilization rates, project profitability, pipeline metrics
- →Interactive dashboards your team can use without a data scientist on staff
- →AI-assisted synthesis of large document sets (RFPs, contracts, project specs)
- →Deliverable formats: Notion, Airtable, Google Data Studio, or PDF report
AEC GTM Intelligence & Market Research
Purpose-built go-to-market research for AEC technology companies and investors. We map the full distribution landscape — conferences, communities, influencers, trade associations, directories, and AEC-specific VCs — so your team can focus on outreach, not list-building.
- →Conference calendar: AEC events, dates, ICPs, and attendance profiles
- →Community map: LinkedIn groups, Facebook groups, Discord, Reddit, WhatsApp — segmented by role and tool
- →Influencer directory: podcasts, YouTube channels, blogs, and newsletters (Bricks & Bytes, aec+tech, AI in AEC, and more)
- →Trade association index: AIA, SMACNA, ASHRAE, MECA, and 30+ others mapped to ICP and decision authority
- →Directory & list intelligence: ENR Top 400, BD+C Giants, and other key industry rankings
- →AEC + ConTech VC landscape: active investors, portfolio focus, and deal stage preferences
- →Segmented outreach lists by role, firm type, and geography — ready to import into your CRM
What this looks like in practice
Examples from recent projects — across custom AI tooling, data research, and implementation strategy.
Custom AI Customer Service Agent for a Local Woodworking Studio
A San Francisco woodworking shop was evaluating off-the-shelf customer service chatbots running $79–$165/month — tools that weren't purpose-built for their business and required ongoing SaaS subscriptions. Our team designed and built a custom AI agent integrated with their website and Gmail, using the Anthropic API with a FastAPI backend. The agent handles customer inquiries, appointment context from their scheduling system, and common questions about services and lead times — all trained on the shop's actual voice and offerings. The result: a purpose-built solution for roughly $5–20/month in API costs, with full ownership of the tool and no vendor dependency.
Aané — AI-Powered Architectural Detail & Material Search
Partnered with Aané (aane.io), an early-stage AEC software company building an AI-powered architectural detail and material search platform. The core problem: architecture firms were losing institutional knowledge when project teams turned over, and spending hours re-researching details and materials they'd already solved. We contributed to product strategy and ICP positioning — helping the team articulate why 'reduce research time by 80%' is the right lead metric, and how to sequence onboarding to demonstrate value before asking for firm-wide adoption. The platform now serves architects, interior designers, and engineering firms as a searchable knowledge repository with AI-enabled design intelligence.
Visit aane.io →AEC Hub Data Intelligence Platform
Built and maintain 7 live data dashboards pulling from BLS, FRED, Census Bureau, FHWA, and USAspending.gov — covering construction employment, material prices, building permits, bridge conditions, federal infrastructure spending, site risk, and AEC salaries across 44 occupations and 393 metro areas. Each dashboard is validated against source data, updated automatically, and built to serve real decisions — not just display numbers. The platform now attracts AEC professionals, researchers, and firms using it as a primary reference for market intelligence.
Simple process, clear output
No lengthy discovery questionnaires. No six-week onboarding. Here's what working together actually looks like.
We diagnose where technology or data is moving the needle — and where it isn't. Honest take on whether we're the right fit.
Simple scope document: engagement, timeline, deliverables, price. No bloated SOWs.
Focused collaboration with regular check-ins. Deliverables on schedule. Scope changes flagged early.
You walk away with something actionable — a report, roadmap, dashboard, or working tool. Retainer available for ongoing support.
The perspective behind the platform
AEC Hub started as an independent tool directory — we kept hearing the same question from firms: "great, but which one is right for us, and how do we actually use it?" Advisory was the answer. We bring architecture practice, AI product strategy, and data engineering to firms making real technology decisions.
Common questions from firms reaching out
How do I choose the right AI tools for my AEC firm?
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Start with a Technology Assessment. We evaluate your current workflows, identify gaps and redundancies, and recommend 3-5 specific tools from our catalog of 249+ AEC tools, ranked by impact vs. effort. The audit costs $750 and includes a written report, implementation matrix, and follow-up support. Most firms find this is enough to make a confident decision without spending months on internal research.
Can a small architecture firm afford AI consulting?
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Yes. Our Technology Assessment starts at $750 flat, and the fee credits 100% toward any deeper engagement. We designed our services specifically for firms that need expert guidance without enterprise consulting budgets. A 5-person studio and a 500-person firm both get the same quality of analysis.
What does a Fractional Data & AI Lead do for an AEC firm?
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Think of it as having a Chief Data Officer without the full-time hire. For $3,500/month, you get monthly strategy sessions, ongoing tool vetting as new AEC products launch, help translating your firm's data into dashboards and reports, and input on RFP decisions and vendor evaluations. You get direct access via email, Loom, or Slack — no account manager layer.
Does AEC Hub work with AEC technology companies, not just firms?
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Yes. Our GTM Intelligence service (from $1,500) is built specifically for AEC tech startups, established vendors, and investors. We map the full distribution landscape: conferences, communities, influencers, trade associations, directories, and AEC-focused VCs. We also help with ICP positioning and go-to-market strategy for the AEC buyer.
What kind of data dashboards can AEC Hub build?
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We build custom dashboards from your firm's own data (utilization rates, project profitability, pipeline metrics) or from public data sources. Our own platform runs 7 live dashboards covering AEC salaries, material prices, construction employment, building permits, federal infrastructure spending, bridge conditions, and site risk — all validated against federal source data. We deliver in Notion, Airtable, Google Data Studio, or as a standalone web application.
Ready to stop guessing and start deciding?
Whether you're evaluating your first AI tool, building a GTM motion for an AEC product, or trying to get more value from data you already have — the first call is free.