GET/v1/vehicle/{registration}
POST/v1/vehicle/bulk
POST/v1/vehicle/bulk/async

Full history.
One registration.

Raw DVLA and DVSA data is public. We ingest 137M vehicle records, classify every defect description, compute fleet benchmarks, detect odometer fraud, and return a scored, ready-to-use response — not a data dump.

Data sourced from DVLA and DVSA under the Open Government Licence v3.0.

Key signals

Six key signals shown below — 80+ in every response. No tiers, no add-ons. View the full signal reference →

signals.odometerTrend string | null

Odometer Trend

consistent, high_mileage, low_mileage, possible_clocking, or insufficient_data. Derived from all recorded MOT readings chronologically.

signals.ulezCompliant boolean | null

ULEZ Compliant

Derived from DVLA euro emission standard and fuel type. One field, no calculation required.

signals.motPassRate number | null

MOT Pass Rate

0.0–1.0 pass rate across all recorded MOT tests. Null only when there's no MOT history at all.

signals.motStatus string | null

MOT Status

Live MOT status from DVLA: valid, expired, no_mot, or no_details.

signals.euroEmissionStandard string | null

Euro Emission Standard

The underlying emission classification (EURO 1–6) from DVLA. Drives ULEZ compliance, insurance pricing, and resale value.

summary.buyRecommendation string | null

Buy Recommendation

good, consider, caution, or avoid — derived from MOT risk score, odometer integrity, condition score, and recall status.

The intelligence layer

The raw government data is public. Here's what sits on top of it.

Pattern detection

Defect clustering across MOT history

Every DVSA defect description — failures and advisories — is classified into one of nine categories: brakes, suspension, tyres, lights, steering, bodywork, exhaust, electrical, wipers. Recurring categories across separate tests are surfaced as failureClusters and advisoryClusters.

Fraud detection

Odometer integrity analysis

All recorded readings are checked chronologically across the full MOT history. Same-day retests are ordered failed-before-passed to eliminate false positives. Any reading lower than the previous triggers possible_clocking.

Fleet benchmarking

Performance vs identical models

Per-test failure and advisory rates are maintained for every make/model/year combination across our full dataset. maintenanceScore and the fleet profiles show where this vehicle sits relative to the same model at the same mileage.

Composite scoring

Three distinct risk dimensions

motRiskScore accounts for last result, lifetime pass rate, advisory trajectory, odometer integrity, dangerous defect history, recall status, and imminent expiry. conditionScore answers "is it safe to buy?" — maintenanceScore answers "has it been looked after?"

Buy signal

buyRecommendation — one field, fully derived

good, consider, caution, or avoid — computed from vehicleRiskLevel, odometer trend, dangerous defect history, recall status, and last MOT result. No manual signal interpretation required.

Compliance & tax

ULEZ status and VED cost computed

ulezCompliant is derived from euroEmissionStandard + fuelType per current TfL rules. vedAnnualCostGbp is the actual annual cost from current DVLA rate bands — updated after each Spring Statement.

Fraud detection

DVLA vs DVSA colour discrepancy

When the colour on the current V5C (DVLA) differs from the colour recorded at the last MOT (DVSA), the response flags colourChangeIndicated. A common indicator of a post-accident respray or identity fraud — returned automatically in every enriched response.

Safety intelligence

Euro NCAP rating — no lookup required

Overall safety star rating plus four sub-scores (adult occupant, child occupant, vulnerable road users, safety assist) derived from Euro NCAP open data. Returned inline with every vehicle response. Low ratings (0–2 stars) elevate vehicleRiskLevel automatically.

Off-road detection

offRoadLikelihoodScore — continuous SORN signal

0.0–1.0 continuous score based on time since last MOT test. Linear: 3 years = 0.30 (caution), 7 years = 0.70 (avoid). Vehicles with no recent test are almost certainly SORN'd, scrapped, or non-runners — the score makes the likelihood explicit so you can apply your own threshold without interpreting a boolean.

Drivetrain stress

Usage pattern and DPF risk — derived automatically

drivetrainStressProfile infers likely driving pattern (short_urban, mixed, long_distance) from typical annual mileage. For diesel vehicles, dpfRisk flags elevated or high DPF clogging risk when annual mileage is too low for passive regeneration — a common hidden fault that doesn't show on an MOT until it fails.

Fleet benchmarking

Above-average advisories and MMY fleet averages

aboveAverageAdvisories is a single boolean comparing this vehicle's per-test advisory rate to the fleet average for the same make/model/year. avgAdvisoriesPerTestForMMY and avgFailuresPerTestForMMY surface the raw benchmark figures so you can show users exactly where they stand: "This vehicle averages 2.1 advisories per test vs 1.4 for its model."

Expiry intelligence

MOT and tax expiry — days remaining, not just a date

motDaysRemaining and taxDaysRemaining give exact days remaining for each — ready to display without date arithmetic. imminentMot flags vehicles within 30 days of MOT expiry. Negative values mean the vehicle is currently unlicensed or untested.

Common use cases

From used car platforms to insurance underwriting. See all vehicle use cases →

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Used car risk

MOT history, odometer trend, and clocking detection before a vehicle goes to market or is taken in trade.

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Insurance risk scoring

Every signal a motor underwriter needs: fuel type, CO2, euro standard, MOT history, ULEZ status.

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Fleet management

Check MOT expiry, tax status, and ULEZ compliance across your whole fleet programmatically.

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Finance & HP risk

Assess the collateral before the deal closes. MOT history and odometer trend from DVSA directly.

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Marketplace trust

Show buyers the full MOT history, clocking flag, and ULEZ status on every listing.

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Claims verification

Pull the full vehicle record in a claims flow. Spot discrepancies between the claim and the vehicle's actual history.

Data sources

DVLA Vehicle Enquiry ServiceDVSA MOT History APIEuro NCAP open dataOpen Government Licence v3.0

Contains public sector information licensed under the Open Government Licence v3.0.

Want the detail on each source? Read our DVLA API guide or MOT History API guide.

What we cover — and what we don't

✓ We include

  • DVLA registration and tax data
  • DVSA MOT history
  • Odometer trend and clocking detection
  • ULEZ compliance status
  • Euro emission standard and CO2

✗ We don't include

  • Finance outstanding (closed HPI register)
  • Stolen marker (Police National Computer)
  • Write-off history (insurance registers)

We only use authoritative public sources.

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