Opportunities › Agent-driven Building Information Modeling software › Proposed app
Beamnote
Review and approve AI agent edits to building models before they merge
- Score
- 36
- confidence 41
- Evidence
- 2
- items on the page
- Rivals
- 2
- named in sources
- First version
- 55 d
- estimate
- Type
- Desktop app
- PWA: runs in the browser, installs on Mac and Windows
- Market since
- 2000
- Mature market · AI estimate
ScreensConcept
Desktop app: Architects and engineers review complex model diffs and make approval decisions at a desk, relying on detailed technical comparisons and audit trails. Sample screens on a computer, in the proposed brand. Their numbers are sample data.
Review queue
2 need you today7 pending
About this appAI proposal
Beamnote is a review desk for building models. Your AI agents, scripts or open-source BIM tools send proposed changes to an IFC model through an API. Beamnote shows each change as a clear diff, runs your checks, and lets a person approve, reject or comment before anything is merged.
It is for architects, engineers and construction technology teams who want to automate repetitive modeling work but cannot let an agent edit a shared model unseen. Reviewers work in the browser or on a phone instead of opening a heavy desktop tool to inspect every edit.
Beamnote does not replace your modeling tool. It sits between agents and the model, keeps a full history, and exports standard IFC, so you are not tied to one vendor's file format.
- Tagline
- Let agents draft. Let people decide.
- Voice
- PlainCarefulPractical
- Why this name
- A beam carries load and a note records a decision. Together they say: structural work, with a clear human sign-off.
In the first version
Members say which features they would use. It tells PWAS what people want; it changes no score.
Change proposals from any agent
Agents and scripts post edits through a simple API. Each arrives as a named change set with a reason, not a silent overwrite.
No member yet
Readable model diffs
See what was added, moved, resized or deleted, grouped by level and element type, with a simple 3D view that highlights each change.
No member yet
Rule checks before review
Set checks such as minimum door width or missing fire rating. Failing proposals are flagged before a person looks at them.
No member yet
Approve, reject, comment
Reviewers decide per change or per set. Comments stay attached to the element, so agent runs and the team see the same notes.
No member yet
Brand identityAI proposal
Check the name against trademark registers before using it.
Palette
#17505ADeep Teal · primary#F4F1EADrafting Paper · surface#1F2A2EInk · text#E07A2FSafety Orange · accent#6B8F71Sage · data, passed
Typography
Aa
Beamnote
ABCDEFGHIJKLMNOPQRSTUVWXYZ 0123456789
Let agents draft. Let people decide.
PricingAI proposal
The material gives no competitor prices. These tiers are a starting point to test, not based on market data.
Solo
Free
- 1 project
- 1 reviewer
- Import and export IFC
- 30-day history
Team
$49 a month
- 10 projects
- 5 reviewers
- Custom rule checks
- Full history and rollback
- Email alerts
Firm
$199 a month
- Unlimited projects
- 25 reviewers
- Audit export
- Priority support
Would you pay Team · $49 a month?
Your answer tells PWAS which prices people accept. It changes no score.
No answers yet.
What it could be worthEstimate
What a software business making this much sells for today, from real deals. Pick a monthly revenue.
If it makes
Worth about
$190,000
Sale range $132,000 to $263,000
$120,000 a year in revenue
From 87 software businesses listed and sold on Empire Flippers in the last year, revenue vetted by the broker: they sell for about 19× their monthly revenue, most between 13× and 26×.
Measured on profit, the middle deal is 32× monthly net profit: about 2.7 years of profit.
An estimate, not an offer or financial advice. A real price depends on profit, growth, churn, how much of the work is the owner's, and the buyer.
How it would growAI proposal
How the product would reach new customers through its own use, and how the first ones would be found. A plan to test, not a result.
- Built-in loop
- Shared outputs. Reviewers share a change-set link with consultants, clients or contractors, who can view the diff and comment without an account. Exported review reports carry a small Beamnote mark.
- Do they become customers?
- Outside viewers could become paying users if they run their own agents, but most will only see a link once. Test whether guest reviewers create accounts in the first month.
- First customers
- Small architecture and engineering practices of 5 to 30 people with a BIM lead who already scripts model tasks and is trying AI agents.
- Where to reach them
- Open-source BIM communities: Offer a free review API to developers building agent tools on open BIM projects, and ask for feedback in their repositories.
- BIM manager forums and groups: Post short demos of reviewing an agent's door renumbering and ask managers for a pilot.
- Direct outreach to BIM leads: Contact leads at small practices with a sample model reviewed in Beamnote, and offer a free setup call.
- First milestone
- Five firms each review at least 20 real agent change sets in a month, and two agree to pay for the Team tier.
Why people already pay for this
- VerifiedGitHub repository gained 828 stars in 17 days
- Public claimBIMCraft is an open-source BIM tool built in Rust, designed to replicate and improve upon Revit's workflow while adding agent-driven automation capabilities.
Tech stack
Every proposal builds on the same PWA base, installable from the browser on any phone or computer. Dashed boxes are what this app adds.
- AppNext.js and TypeScript
- PWAManifest and service worker
- UITailwind CSS
- Data and authSupabase Postgres
- PaymentsStripe
- EmailResend
- HostingVercel
- This app · IFC processingOpen-source IFC parser compiled to WebAssemblyReads, compares and writes IFC files in the browser and on the server without a desktop BIM tool.
- This app · File storageS3-compatible object storageModel files and versions are large and do not belong in Postgres rows.
RisksAI inference
- TechnicalDiffing large IFC models and rendering them on a phone is hard. Files may be slow or lose detail on round trip, which would break trust.
- CommercialFirms may prefer approvals inside their own modeling tool or an open-source platform, leaving a separate review desk with little reason to be paid for.
- AIAgent output quality is uneven. Reviewers may be flooded with poor proposals, and rule checks may give false confidence.
- PlatformVendors of dominant BIM tools may restrict file exchange or change their formats, limiting how far models can be read and written.
- DataBuilding models can be confidential client assets. Firms may refuse cloud storage without strong access control and regional hosting.
Everything marked AI proposal or AI inference was written by a model from the evidence on the opportunity page. The proposed name must be checked against trademark registers before it is used.