We extract vehicle recalls, consumer complaints, 5-Star Safety Ratings, investigations, and Technical Service Bulletins from NHTSA. 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 Recalls objects from nhtsa.gov. All fields typed and schema-versioned.
"recall_number": "23V-123", "make": "Ford", "model": "F-150", "year": 2023, "component": "STEERING", "report_date": "2023-04-12"
| # | recall_number | campaign_id | manufacturer | make | model | year |
|---|---|---|---|---|---|---|
| 1 | ||||||
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Complete list of extractable fields for Complaints objects from nhtsa.gov. All fields typed and schema-versioned.
"odi_number": "11412345", "crash_indicator": false, "fire_indicator": false, "number_of_injuries": 0, "complaint_date": "2023-05-18", "component": "ELECTRICAL SYSTEM"
| # | odi_number | make | model | year | crash_indicator | fire_indicator |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
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Complete list of extractable fields for Investigations objects from nhtsa.gov. All fields typed and schema-versioned.
"nhtsa_action_number": "PE22-001", "status": "OPEN", "opened_date": "2022-01-15", "subject": "Phantom Braking", "component": "FORWARD COLLISION AVOIDANCE"
| # | nhtsa_action_number | make | model | year | subject | opened_date |
|---|---|---|---|---|---|---|
| 1 | ||||||
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Complete list of extractable fields for Safety Ratings objects from nhtsa.gov. All fields typed and schema-versioned.
"make": "Honda", "model": "Civic", "year": 2022, "overall_rating": 5, "frontal_crash_rating": 5, "rollover_rating": 4
| # | vehicle_id | make | model | year | overall_rating | frontal_crash_rating |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
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Complete list of extractable fields for TSBs objects from nhtsa.gov. All fields typed and schema-versioned.
"tsb_number": "TSB-21-01", "issue_date": "2021-03-10", "component": "ENGINE", "document_url": "https://static.nhtsa.gov/odi/tsbs/...", "summary": "Engine misfire under heavy load."
| # | tsb_number | manufacturer_communication_number | make | model | year | component |
|---|---|---|---|---|---|---|
| 1 | ||||||
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Our NHTSA scraper extracts safety records across decades of vehicle history. We parse complex search interfaces, decode VINs in bulk, and extract text from manufacturer PDF submissions.
Extract campaign IDs, affected populations, and remedy instructions for all vehicle, tire, and equipment recalls.
Pull millions of user submitted complaints with crash indicators, injury counts, and narrative summaries.
Track frontal, side, and rollover crash test ratings for all tested makes and models.
Scrape manufacturer communications and automatically extract text from attached PDF documents.
Monitor open and closed NHTSA investigations, including engineering analyses and preliminary evaluations.
Process millions of VINs through the vPIC API to normalise make, model, year, and plant data.
Extract aggregated manufacturer data on death and injury incidents.
Capture safety ratings and installation metrics for child restraint systems.
Paginate through decades of archived safety records without timing out or missing records.
Brief in. Clean data out.
Specify vehicle makes, years, or data types (recalls, complaints, TSBs). We map the extraction schema.
We configure Scrapy crawlers, API polling for vPIC, and PDF parsing pipelines for document extraction.
Schema validation, null-rate checks, and cross-referencing VIN decodes before full launch.
JSON / CSV / Parquet pushed to your S3 bucket, BigQuery dataset, or Snowflake stage on agreed cadence.
NHTSA provides massive public datasets, but their interfaces are prone to timeouts, rate limits, and nested document structures. Here is how we build resilience.
NHTSA APIs frequently throttle bulk requests. We implement distributed IP rotation and exponential backoff to maintain throughput without triggering blocks.
TSBs and manufacturer letters are often scanned PDFs. We deploy OCR pipelines to convert image based documents into queryable text.
Deep pagination on NHTSA databases often results in server 504 errors. Our crawlers slice date ranges into micro batches to ensure complete historical extraction.
Manufacturer naming conventions change over time. We normalise make and manufacturer fields against the vPIC database.
We track ODIs and campaign IDs to only extract new complaints and recalls, reducing load and preventing duplicate records in your warehouse.
Analyze defect trends and reliability metrics across competing manufacturers to inform product strategy.
Actuaries correlate consumer complaints and crash test ratings with claim frequencies to adjust premium pricing.
Integrate open recall status and historical complaint volume into automated vehicle valuation algorithms.
Fleet operators use TSBs and early warning reports to proactively service vehicles before catastrophic failures.
Law firms monitor defect investigations and consumer complaints to identify class action opportunities.
Aftermarket suppliers track component specific failure rates to forecast demand for replacement parts.
"NHTSA holds the definitive record of automotive safety failures in the United States, but extracting actionable signals from their legacy systems requires industrial grade pipelines."
Most teams struggle with NHTSA data because it is fragmented across APIs, HTML tables, and scanned PDFs. DataFlirt centralises this extraction, handling the rate limits, OCR, and schema normalisation so your data science team receives clean, queryable records ready for analysis.
Everything supported by our nhtsa.gov 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 direct HTML parsing for legacy search interfaces while managing rate limited requests to the vPIC API.
PDFs attached to TSBs are downloaded to S3, queued in Redis, and processed via distributed OCR workers to extract raw text.
Pipelines run on AWS Lambda (burst) and ECS (sustained). Airflow handles scheduling, dependency management, and SLA alerting.
Data delivered to where your team already works — no new tooling required.
About nhtsa.gov scraping, legality, and pipeline operations.
Ask us directly →Yes. NHTSA data is public domain government information. We strictly adhere to public access guidelines and respect API rate limits to ensure we do not disrupt government infrastructure.
Yes. Our pipeline includes automated document downloading and text extraction. We use OCR for scanned documents to ensure the technical details are fully searchable.
NHTSA records span decades. We can extract historical complaints, recalls, and investigations dating back to the 1970s, depending on the specific dataset.
Yes. We integrate with the NHTSA vPIC API to decode VINs in bulk, normalising manufacturer, make, model, year, and plant specifications.
We use distributed IP rotation, intelligent request pacing, and exponential backoff to extract data efficiently without overwhelming NHTSA servers.
No. NHTSA redacts Personally Identifiable Information (PII) from public complaint records before publishing them. We only extract the public, anonymised data.
We support daily, weekly, or monthly cadences. For critical safety monitoring, we can configure hourly incremental runs to capture new recalls or investigations.
20-minute scoping call. Pilot dataset within the week. Production within two. Whether you need a historical dump of consumer complaints or continuous monitoring for new vehicle recalls, we build and operate the pipeline. Tell us what you need.
