Workflow Orchestration for Commercial Real Estate

What This Category's Data Looks Like

Commercial real estate due diligence data mainly comes from real estate registration authorities, regional property trading platforms, on-site surveying and mapping reports, tenant lease contracts, property payment records, and surrounding supporting facility survey data. Update frequency: Ownership-related information is updated quarterly. Transaction and rent data is synchronized in real time but requires pulling via third-party platform APIs. Tenant contracts and property records are updated as needed. Document structure: A single due diligence report includes modules such as basic parcel information, building area details, rent ledger, ownership certificate scans, and surrounding business district data. Fields and units: Includes internal floor area (unit: ㎡), average monthly rent (unit: yuan/㎡/month), vacancy period (unit: days), and ownership certificate number. Some cross-regional data requires unit conversion.

Constraints Imposed on Workflow Orchestration by These Characteristics

Dispersed data sources and varying update rhythms require splitting the workflow into multiple data pulling nodes. These nodes must separately support scheduled pulling of static ownership data and real-time synchronization of dynamic rent data. Long single-document length requires setting shard parsing nodes to avoid single-processing timeouts. Inconsistent field units require adding unit conversion nodes to calibrate numerical formats across data sources. Cross-validation of multi-module data requires setting data verification nodes in the workflow. These nodes ensure consistency of parcel area and rent values from different sources. Some documents contain mixed scanned text and image content. An OCR recognition node must be configured for preprocessing to avoid missing text extraction.

Configuration Settings

Configuration Item	Recommended Value	Rationale
`PARSE_FILE_TIMEOUT_SECONDS`	`900 seconds`	Commercial real estate due diligence single documents often exceed 50 pages, with long parsing times, requiring sufficient time reserved
`maxContext`	`8000–12000 characters`	Context information of multiple ownership documents and rent ledgers must be retained to avoid truncation of key fields
`UPLOAD_FILE_MAX_SIZE`	`2000 MB`	Supports uploading complete due diligence packages including aerial images and surveying and mapping reports
`chunk_size`	`1500 characters`	Adapted to long paragraphs of property descriptions and rent details in commercial real estate documents, avoiding semantic fragmentation
`retrieval_top_k`	`Top 8 entries`	Meets recall requirements for multiple key fields including parcel information, surrounding supporting facilities, and tenant data
`rerank_top_k`	`Top 3 entries`	Focuses on highly relevant core data, avoiding redundant information interfering with due diligence conclusion generation

The parameter values provided on this page are common recommendations used as a starting point for configuration. Actual values are affected by material format, data volume, and business rules. Specific issues require targeted analysis, and it is recommended to test on your own samples before finalizing.

Three Common Configuration Errors

Phenomenon: Tenant rent fields display empty after workflow runs. Cause: Context synchronization is not triggered after the variable update node, so subsequent nodes cannot read the newly assigned variable values.
Phenomenon: 503 Service Unavailable error occurs after multiple workflow triggers. Cause: Multi-node load balancing is not configured, and the single-node concurrent processing peak exceeds the carrying limit.
Phenomenon: Generated due diligence reports lack supplementary data on surrounding supporting facilities. Cause: AI reply content is mistakenly passed as context to subsequent nodes, and the two outputs of new context and AI reply content are not correctly separated.

How to Verify Successful Configuration

Upload a single commercial real estate due diligence document with more than 50 pages. Verify that the parsing duration matches the configured PARSE_FILE_TIMEOUT_SECONDS value.
Manually trigger a workflow. Check the output logs in the variable panel to confirm that core field values match the source file.
Call the workflow API interface. Confirm that the returned results include preset core due diligence fields, with no abnormal formatting or unit errors.
Configure a concurrency test. Confirm that triggered requests do not return 503 errors, meeting business carrying requirements.

Question material comes from public community discussions. Configuration values are common starting points and should be measured against your own samples. Verified on 2026-09-14.