Technical breakdowns, decision frameworks, and honest context. Evaluate this clearly before committing to anything.
A plain-language breakdown of how automation layers map to the actual workflows CRE firms run: deal flow, operations, reporting, and compliance. Not a product pitch. A reference you'll actually use.
Request the blueprintTechnical breakdowns of what each workflow does, what it connects to, and where the complexity lives. Not marketing copy.
Automated monitoring of public records, MLS data, and off-market signals. The system surfaces properties matching your buy-box before a broker calls. Configured per firm: asset class, geography, unit count range, vintage, and distress indicators. Sources are checked on a schedule and routed into your CRM when criteria match.
Inbound OM triage. Attachments are parsed on receipt, structured into a consistent format, and scored against your firm's specific criteria. The output is a kill-or-advance decision with written reasoning. Not a score alone. Analysts receive only deals that pass the first filter. The system adapts to deal type: MF, industrial, retail, office.
Pre-populates your underwriting model with data extracted from OMs, T12s, rent rolls, and market comp pulls. Does not replace underwriting judgment. Removes the data-entry layer under it. Key metrics (NOI, cap rate, DSCR) surfaced with flagged discrepancies. Integrates with Excel, Argus, or any spreadsheet-based model your firm already uses.
Converts raw lease PDFs into structured data. Extracts: commencement/expiration, options, rent escalations, CAM provisions, HVAC responsibility, co-tenancy clauses, and any custom fields your team tracks. Output is consistent and populates directly into your property management system. Existing backlog can be cleared in bulk; new leases process same-day.
Automates quarterly or monthly reporting to limited partners. Pulls data from operator portals, property management software, and accounting. Reconciles, formats into your branded template, and stages for GP review. One-click approval triggers distribution with per-LP personalized views. Supports fund-of-funds structures and waterfall reporting.
Tracks and manages the document collection process for acquisitions. Generates a checklist from deal parameters, assigns items to vendors and attorneys, monitors what's been received vs outstanding, and flags gaps before closing. Connects to your data room (Dropbox, Google Drive, Firmroom) and updates status automatically as documents are uploaded.
This is where most vendors stop being useful. We'd rather you know before you book a call.
Most of the hesitation we hear is based on assumptions that don't hold. Here's what's actually true.
The systems we build are maintained by us, not by you. You own the output. You don't operate a stack. When something breaks or the source data format changes, we fix it. That's what the 30-day support window covers. Ongoing maintenance is available as an add-on.
None of these systems make the decision. A deal screener produces a recommendation. An underwriting support tool pre-fills a model. The GP approves the LP report before it sends. Automation removes mechanical labor. It doesn't replace the person making the call.
We've never found a portfolio where the data was too messy to work with. The scope of the build accounts for the format of your data. OMs come in dozens of formats. Leases vary wildly. That's what document parsing and normalization are designed for. Messy inputs are the baseline, not the exception.
Most CRE software handles data storage. Not workflow automation. AppFolio stores your leases. It doesn't abstract them. CoStar shows you deals. It doesn't screen them against your buy-box. What we build is the layer that runs between your data and your people. The part the software vendors don't build.
A $5,000 deal screening system saves 4 hours per deal. At 30 deals a month, that's 120 analyst hours recovered. Before any improvement in deal quality. The math closes in the first month for most firms at any reasonable volume. The guarantee removes the financial risk.
The firms that implement early compound the advantage. An 8-person team running with the throughput of a 20-person team doesn't grow slower. It grows faster. Waiting until you're big enough to feel the pain means carrying the drag while you scale, not eliminating it before you scale.
We use these terms with specific meanings. Worth defining before a scoping call.
A system that executes a repeating multi-step task without manual involvement. Not a chatbot. Not a dashboard. A process that runs on a trigger (an email arrives, a file is uploaded, a date passes) and produces a structured output.
Extracting structured data from unstructured documents (PDFs, OMs, leases). The hard part is variability. Every broker formats their OM differently. Parsing systems are trained to handle that variation, not assume a fixed format.
The specific criteria a firm uses to evaluate whether a deal is worth pursuing. Asset class, geography, unit count, cap rate range, vintage, distress indicators. We encode this as logic, not a checklist. It runs against every deal automatically.
A numerical measure of how certain the system is about an extracted value. Low confidence flags are surfaced for human review. The system doesn't silently guess. Critical for high-stakes extractions like option windows and rent escalations.
The connections between your automation and your existing software (CRM, PM system, data room, accounting). Most of the scoping work happens here: matching data models, authentication, field mapping, error handling.
A build delivered at a fixed price against a defined scope. Not time-and-materials. Not an ongoing retainer. You know what you're getting, what it costs, and when it's done before you commit to anything.
If there's a fit, you'll know the scope and price before you commit. If there's no fit, we'll tell you that too, and point you at something that makes more sense.
Satisfaction guaranteed · Fixed price · You own everything