We extract daily reports, time cards, safety checklists, and equipment logs from Raken. Delivered as clean JSON, CSV, or Parquet to S3, BigQuery, or Snowflake on your cadence.
Structured, schema-consistent data across all major object types — delivered clean, typed, and ready to query.
Complete list of extractable fields for Daily Reports objects from raken.com. All fields typed and schema-versioned.
"report_id": "REP-883921", "project_id": "PRJ-9921", "date": "2026-05-12", "status": "APPROVED", "author_name": "James Holden", "weather_summary": "Clear, 24C, Wind 5km/h", "attachment_count": 14, "created_at": "2026-05-12T17:30:00Z"
| # | report_id | project_id | date | status | author_name | author_role |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Subcontractor Logs objects from raken.com. All fields typed and schema-versioned.
"log_id": "SUB-44129", "company_name": "Apex Electrical", "trade": "Electrical", "worker_count": 6, "hours_worked": 48.5, "cost_code": "02-400", "task_description": "First floor rough-in wiring"
| # | log_id | report_id | company_name | trade | worker_count | hours_worked |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Time Cards objects from raken.com. All fields typed and schema-versioned.
"timecard_id": "TC-99281", "worker_name": "Amos Burton", "project_id": "PRJ-9921", "cost_code": "03-100", "regular_hours": 8.0, "overtime_hours": 2.5, "total_hours": 10.5, "approval_status": "PENDING"
| # | timecard_id | worker_id | worker_name | project_id | cost_code | regular_hours |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Safety Checklists objects from raken.com. All fields typed and schema-versioned.
"checklist_id": "CHK-1102", "template_name": "Weekly Site Safety Audit", "inspector_name": "Naomi Nagata", "score_pct": 92.5, "passed_items": 37, "failed_items": 3, "signature_status": "SIGNED"
| # | checklist_id | project_id | template_name | inspector_name | score_pct | passed_items |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Equipment & Materials objects from raken.com. All fields typed and schema-versioned.
"log_id": "EQ-7732", "resource_type": "Equipment", "item_name": "Excavator 320", "quantity": 2, "unit": "Days", "supplier": "Sunbelt Rentals", "delivery_status": "ON_SITE"
| # | log_id | project_id | resource_type | item_name | quantity | unit |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Our Raken scraper extracts nested project data, handles complex authentication states for client accounts, and downloads gigabytes of site photos automatically.
Capture complete daily logs including weather data, notes, and status flags across all active construction projects.
Extract worker hours, cost codes, and approval statuses. Format data for direct ingestion into payroll and ERP systems.
Log company names, worker counts, and task descriptions to audit subcontractor performance and billing.
Extract pass/fail ratios, hazard notes, and compliance signatures from custom safety templates.
Track site deliveries, equipment usage hours, and supplier information mapped to specific cost codes.
Automated downloading of high-resolution site photos and attachments, mapped to their respective reports via metadata.
Extract automated weather observations recorded in Raken to correlate environmental conditions with project delays.
Track changes to previously submitted reports and time cards. Extract only new or modified records per run.
Consolidate data across hundreds of disparate project instances into a single, queryable warehouse table.
Brief in. Clean data out.
Specify target projects, date ranges, and required data types (reports, time cards, media). We map the extraction schema.
We configure authentication flows, pagination logic, and attachment download managers for the Raken interface.
Schema validation, null-rate checks, and data reconciliation against the native Raken dashboard before full launch.
JSON, CSV, or Parquet pushed to your S3 bucket, BigQuery dataset, or Snowflake stage on agreed cadence.
Extracting construction data at scale requires managing heavy payloads and complex state. Here is how our infrastructure handles it.
Extracting private project data requires authenticated sessions. We manage client-provided credentials securely, handling session timeouts, token refreshes, and cookie persistence automatically during long extraction runs.
Construction reports contain gigabytes of photos. Our pipeline separates text data extraction from media downloading. Photos are downloaded asynchronously and streamed directly to your S3 bucket, with URLs mapped back to the structured JSON.
Raken projects can span years. We implement resilient pagination handlers that traverse thousands of daily reports without dropping records, storing cursor state to resume cleanly if interrupted.
Contractors often use custom templates and cost codes. We normalise varying report structures into a strict, predictable schema, ensuring downstream ERP and BI tools do not break.
Field workers frequently update time cards or reports days later. Our differential sync engine hashes record states to detect and push late modifications, rather than just appending new data.
Construction firms extract cost codes and material logs to sync directly with Viewpoint, Procore, or CMiC.
Finance teams pull approved time cards and overtime data to automate payroll processing without manual data entry.
Risk managers aggregate safety checklist failures across all projects to identify systemic training gaps.
Analysts correlate subcontractor hours and equipment usage with project timelines to optimise future bids.
Legal teams archive daily reports, weather logs, and site photos to defend against delay claims and disputes.
IT departments extract full historical project data to maintain independent backups or migrate to new platforms.
"Construction field data is trapped in application silos. Extracting daily reports and time cards at scale requires dedicated pipeline infrastructure, not just brittle scripts."
Most teams underestimate the complexity of extracting nested construction data: handling varied report templates, downloading gigabytes of site photos, and managing session state. DataFlirt absorbs that complexity so your data engineers can focus on analytics, not maintenance.
Everything supported by our raken.com scraper — rendered SPA elements, auth walls, rate-limit evasion and beyond.
Open-source tooling on proven cloud infra — no vendor lock-in, full observability.
Scrapy handles crawl orchestration and deduplication. Playwright manages complex authentication flows and dynamic content rendering.
Dedicated asynchronous workers handle gigabytes of photo downloads, streaming directly to cloud storage to prevent memory bottlenecks.
Pipelines run on AWS Lambda and ECS. Airflow handles scheduling, dependency management, and SLA alerting.
Data delivered to where your team already works — no new tooling required.
About raken.com scraping, legality, and pipeline operations.
Ask us directly →Yes. To extract your company's private project data, daily reports, and time cards, we require read-only credentials or session tokens. We manage these securely within our encrypted secret manager.
Yes. If contractors share public links to daily reports or photo galleries, we can extract that data without authentication.
We download all media files asynchronously. Files are named systematically and pushed directly to your S3 or GCS bucket, with the corresponding URLs included in the structured JSON/CSV output.
Yes. Our incremental sync engine hashes the state of previously extracted records. If a time card or daily report is modified retroactively, we emit the updated record in the next pipeline run.
Pipelines can be configured to run hourly, daily, or weekly depending on your sync requirements. Daily runs after shift completion are standard for construction data.
Yes. We format the output schema to match your requirements, mapping Raken cost codes and worker IDs directly to the formats required by Procore, Viewpoint, or CMiC.
20-minute scoping call. Pilot dataset within the week. Production within two. Stop manually exporting PDFs. We build and operate the infrastructure to stream Raken data directly into your warehouse.
