Introducing the Arvexi Extraction Service

Today we are introducing the Arvexi Extraction Service -a standalone AI extraction engine for lease documents that delivers structured data in any target system's import format. It is designed for enterprises and accounting firms that need lease abstraction at scale, without switching their existing lease accounting software.

How it works

Upload your documents. Drop lease PDFs -agreements, amendments, subleases, invoices, estoppels, commencement memos. Any format, any length, in bulk. No templates to fill out, no preprocessing required. The system accepts the documents your team already has, in the state they are already in.

AI classifies each document. Before extraction begins, the system identifies the document type -is this a lease agreement, an amendment, a sublease, an assignment, an estoppel certificate? -and selects the right extraction template automatically. This matters because an amendment has different fields than a new agreement, and a sublease carries terms that a commencement memo does not. Classification ensures the AI knows what to look for before it reads a single clause.

Intelligent field extraction. The AI reads every page, identifying parties, dates, payment schedules, escalation structures, renewal and termination options, and custom clauses. Each extracted field gets a confidence score from 0 to 100 percent and a link to the verbatim source text and page number. For standard leases with clean formatting, a fast model handles extraction efficiently. For complex documents -multi-asset agreements, amendment chains layered over decades, unusual escalation structures tied to CPI or revenue thresholds -a stronger model is deployed automatically. The system makes this decision on its own, balancing speed and accuracy without any input from the user.

Confidence-based QA routing. Not every field needs human review. Fields above 95% confidence are auto-verified. Fields between 80% and 95% get a quick spot-check -the reviewer sees the extracted value alongside the source quote and confirms or corrects in seconds. Below 80%, full human review with the original PDF page pulled up beside the extracted data. Critical fields -lease classification inputs, discount rates, purchase option prices, termination penalty amounts -are always human-reviewed regardless of confidence score. This tiered approach means reviewers spend their time where it matters instead of re-reading values the AI already extracted correctly.

Deliver in your format. Once data is verified, it is transformed into your target system's exact import format and delivered as a downloadable file. No copy-pasting between spreadsheets. No reformatting columns. No reconciling field names between two different schemas. The data leaves Arvexi ready to be loaded directly into the system your team already uses, with every column name, date format, and data type already matching the target specification.

Confidence scoring and source verification

Every extracted field carries three pieces of information: a confidence score, a source page number, and a verbatim quote from the document. This is not a black box. When an auditor asks where a commencement date came from, the answer is immediate -page 14, paragraph 3, quoted verbatim. Verification takes seconds, not hours of flipping through a PDF.

The confidence score is not static. After initial extraction, validation checks adjust it. If a date is malformed, confidence drops. If the commencement date plus the lease term does not align with the stated expiration date, confidence drops. If the monthly base rent times twelve does not match the stated annual rent, confidence drops. If a payment escalation schedule produces amounts that conflict with the rent table on a later page, confidence drops. These cross-field checks catch errors that even experienced human abstractors miss -the kind of arithmetic inconsistencies that survive manual review because no one recalculates every number by hand.

Output in your system's format

The Extraction Service ships with eight native output adapters. CoStar ETL templates map to the Forms, Financials, and Options tab structure that CoStar users already know. LeaseQuery receives pipe-delimited files matching its bulk import specification. Oracle FBDI gets interface tables formatted for Fusion lease import. SAP RE-FX receives the contract and condition record structure SAP expects. Visual Lease, Nakisa, and NetSuite each get data shaped to their respective import schemas. Generic Excel and CSV serve teams using in-house systems or smaller platforms without a dedicated adapter.

Each adapter maps Arvexi's universal field names to the target system's specific column names, data types, date formats, and file structure. A single extraction produces data that can be exported to any supported format -useful for firms managing clients across different platforms.

Custom clause extraction

Standard extraction covers over fifty fields -the parties, dates, payment terms, escalation schedules, options, and classification inputs that ASC 842 and IFRS 16 require. But every portfolio has clauses that matter to that specific organization.

During engagement setup, you define the clauses your business needs tracked. Competition restrictions, parking space allocations, signage rights, HVAC maintenance responsibilities, snow removal obligations, co-tenancy conditions, exclusive use provisions, subletting restrictions -whatever your portfolio requires. The AI searches for these in every document alongside the standard fields. There is no additional cost per clause type and no limit on how many you define. If a clause appears in the document, the system finds it and extracts the relevant terms.

AI that learns from corrections

Every time a reviewer corrects an extracted field, the pattern is recorded -which lessor, which document type, which field, what the AI extracted versus what was correct. On future extractions from the same lessor or the same document template, the system applies these learned patterns. A correction made once propagates forward to every similar document that follows.

Accuracy compounds with every engagement. The more documents your organization processes through the Extraction Service, the better it becomes for your specific portfolio. Teams that process thousands of leases see measurably higher first-pass accuracy by the end of their first quarter than they did at the start. The system does not just extract -it improves.

Available now

The Arvexi Extraction Service is available now. It works as a standalone product -no Arvexi lease accounting subscription required. Book a demo to see extraction in action with your own lease documents.