Peer cluster
Automotive service operations have three characteristics that break most generic software : the volumes are high, the integration surface with insurers and DVLA is wide, and the SLAs are uncompromising. Here is what running at this scale looks like in the wild.
Automotive back-offices live on integrations. The question is never whether a platform can technically integrate. It is whether a comparable operation has already run this integration surface at volume and not broken. That is what peer proof solves for.
Benchmarks in this sector
1.75M+
Cases under management at one operator
Eight custom schemas covering the full service lifecycle.
5M+
API calls per year across integrations
Six integrations operating as part of the core workflow, not as exceptions.
3 days
Average case completion at scaled operator
Down from weeks under the previous process.
Named peers
Named firms, not logos in a grid. Each one has a case study you can read in full.
Where firms start
None of these are theoretical. Each is a workflow that at least one firm in this sector has piloted and then scaled.
DVLA integration, insurer portal integration, vehicle-data compliance, motor-claims legal and regulatory constraints. SwiftCase handles these as part of the workflow surface, not as custom-coded exceptions.
When firms pilot
New insurer contracts come with new SLAs and integration demands. Pilots often get triggered here.
Winning a new insurer panel doubles volume overnight. Existing processes that were adequate at the old volume break.
When per-case fees tighten, any manual handling becomes unaffordable. Automation moves from nice-to-have to survival.
The pilot is designed exactly for this : one workflow, 30 days, fixed scope, peer-precedent documented. Start with the diagnostic, the estimator, or the scoping call. Whichever moves you forward.
