ARGUS EstateMaster (Altus Group) is the development-feasibility and project cash-flow toolset for CRE developers. Where ARGUS Enterprise values a standing, income-producing asset lease by lease, EstateMaster answers the question that comes earlier in a deal's life: should we build this, and what can we pay for the land? It runs development feasibility (DF) — the residual land-value and development-margin analysis that tells a developer whether a scheme stacks up — alongside development-appraisal and project DCF models that schedule construction draws, sales or lease-up revenue, finance costs, and profit over the life of a project.
Development feasibility is its own discipline, and the bottleneck is rarely the math — it's everything that happens around the model. A development team runs a DF in EstateMaster, exports it to Excel, then retypes the residual land value and profit-on-cost into a board paper, copies the scheme into a pipeline tracker, and re-runs the model a dozen times as the cost plan, sales rates, or programme shift. Every land bid, every IC sitting, every funder update means another round of transcription from the same export. The numbers that decide whether you commit eight or nine figures to a scheme live in a workbook that nobody but the modeller can read quickly.
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Parse an exported ARGUS EstateMaster development-feasibility model — residual land value, development margin, profit-on-cost, development IRR, and the key feasibility verdict — into structured data. No connection to EstateMaster itself; the export is uploaded or watched in a folder.
The DF is what decides whether a scheme is built and what you can pay for the land. Parsing the export means the residual land value and margin reach the board paper without an analyst re-typing them.
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When a development manager finishes an EstateMaster feasibility and exports it, this workflow ingests the export, extracts the residual land value, development margin, profit-on-cost, development IRR, cost stack, revenue schedule, and programme, and drafts a feasibility one-pager plus the land-acquisition section of the Investment Committee packet. The team opens an IC packet with the feasibility verdict already populated and an AI-written narrative on whether the scheme stacks up — instead of a blank template and a workbook to transcribe before the land bid is due.
1n8n detects a new EstateMaster export in the watched folder (file-watch trigger — there is no EstateMaster webhook)
2A parsing node reads the export: residual land value, development margin, profit-on-cost, profit-on-revenue, development IRR, peak debt, and total cost and revenue
3A second pass extracts the cost stack (land, construction, fees, contingency, finance), the revenue schedule (sales/lease-up), and the programme dates
4AI node drafts the feasibility one-pager and IC narrative, and flags any assumption outside the firm's standard ranges (e.g., contingency below a configured floor, a sales rate above comparable schemes, finance cost assuming a static rate over a multi-year build)
The IC packet's feasibility section is drafted in minutes from the EstateMaster export. The team spends its time stress-testing the residual land value and the assumptions the AI flagged before the land bid — not retyping the model — and every packet is formatted identically.
Connect ARGUS EstateMaster to your workflows with powerful triggers and actions
Fires when a new ARGUS EstateMaster export (Excel or PDF) appears in a watched cloud folder (Google Drive, SharePoint, Dropbox). This is a file-watch trigger on your storage — not an EstateMaster webhook, which does not exist.
A development manager saves an EstateMaster feasibility export to the scheme's Drive folder; the watch trigger starts the feasibility-summary and IC-packet workflow automatically.
Fires when an EstateMaster export is uploaded through an intake form or portal, capturing the file along with scheme metadata (site name, scenario label, deal stage).
A regional development team uploads its feasibility export through a simple intake form; the file is routed to the right scheme record and parsed without IT touching shared folders.
Runs on a schedule (e.g., monthly) and processes any EstateMaster exports added to the development-pipeline folder since the last scan.
Each month, scan the pipeline folder and refresh the development-pipeline dashboard from every updated EstateMaster feasibility in one batch.
Read an EstateMaster export and return the headline feasibility outputs — residual land value, development margin, profit-on-cost, profit-on-revenue, and development IRR.
Pull the residual land value and margin from a DF export to populate the feasibility table in an IC land-acquisition packet.
Return the project DCF from an EstateMaster export — the period-by-period schedule of construction draws, sales or lease-up revenue, finance drawdown and interest, and peak debt over the development.
Pull the draw profile and peak debt from an export to size the funding ask and feed the pipeline cash-flow view.
Return the development cost stack — land, construction, professional fees, statutory/contribution costs, contingency, and finance — as a structured breakdown, including contingency as a percentage of build cost.
Flag a scheme whose contingency has been cut below the firm's standard floor between two feasibility runs.
Return the development programme from an EstateMaster model — acquisition, planning/entitlement, construction start and completion, and the sales or lease-up window — as structured timeline data.
Surface each scheme's stage and completion date on the development-pipeline dashboard from the model's own programme.
Read a set of EstateMaster scenario exports for one site and return a normalized comparison of residual land value, margin, IRR, peak debt, and programme across the options.
Produce a build-option comparison table showing the for-sale, BTR, and higher-density scenarios side by side for a land decision.
Diff two exports of the same scheme and return the assumption-level and output-level changes, with the cost or revenue lines that drove the move in residual land value and margin.
Produce a feasibility change-log entry showing how the model moved between first appraisal and land commitment.
Use the extracted feasibility data to populate a downstream document or system — feasibility one-pager, IC land-acquisition packet, scenario comparison table, or pipeline dashboard row.
Auto-fill the feasibility section of an IC packet template from a freshly ingested EstateMaster export.
Get started in approximately 1-2 hours for the first export-to-feasibility-summary pipeline; a half-day for the full IC packet + scenario comparison + pipeline-dashboard suite, depending on export consistency
Decide which export is your source of truth — the EstateMaster Excel feasibility/cash-flow workbook is the most parse-friendly; the PDF report is the fallback when that's all you receive. Agree on a folder structure (one folder per scheme, with scenarios tagged or sub-foldered) and a naming convention that encodes the site identifier and scenario label, so the automation can route each export to the right record.
Have the team always export the same EstateMaster template. Consistent sheet/tab names make the parsing dramatically more reliable than ad-hoc exports — and scenario labels in the filename make the comparison workflow trivial.
In n8n, add a trigger on your cloud storage that fires when a new file lands in the watched EstateMaster folder. Because EstateMaster exposes no webhook or event API, this storage watch (or a scheduled folder scan) is how the pipeline starts. Confirm it fires by dropping a test export into the folder.
Use a dedicated 'inbox' subfolder for fresh exports and move processed files to an 'archive' subfolder at the end of the run, so the watch never re-processes the same export.
Add the parsing step that reads the export and emits a structured object: residual land value, margin, profit-on-cost, development IRR, the cost stack, the revenue and draw schedule, and the programme. Validate it against several real EstateMaster exports from your own schemes — different asset types and tenures (for-sale, BTR, mixed) — and confirm the extracted numbers match the model exactly. Everything downstream trusts this step.
Build a reconciliation check that re-derives profit (total revenue minus total cost) and compares it to the export's own stated profit. If they don't tie, the parse failed — halt the run rather than push a wrong residual land value into a land bid.
Point the structured output at its destination: an IC land-acquisition template that gets populated, a scenario comparison table that gets rendered, or a development-pipeline dashboard row that gets written. Map each extracted field to its target explicitly and keep the mapping in one reusable sub-workflow so the IC packet, the comparison table, and the dashboard all share the same field definitions.
For the comparison workflow, key everything off the scenario label in the filename so adding a fifth build option later is a drop-in, not a re-wire.
Add an AI node that summarizes the feasibility verdict and flags assumptions outside your firm's standard ranges (thin contingency, optimistic sales rate, static finance cost over a long programme), then route a notification (Slack or email) to the development lead with a link to the artifact and the flagged items. Monitor the first several runs and tune the thresholds to your go/no-go criteria.
Log a one-line result for every run ('Scheme X parsed: RLV £8.2M, margin 19.4%, profit-on-cost 22%, 1 assumption flagged'). It makes it obvious when a parse silently degrades after an EstateMaster export-format change.
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