Turn every shop visit into a recall completion opportunity.
RecallPilot is a service-department execution platform that helps dealership and fleet service teams identify, prioritize, and complete open manufacturer recalls and campaigns on vehicles already in the shop. It gives advisors, technicians, and managers one shared workflow so eligible work is surfaced automatically, assigned quickly, and tracked to completion, improving safety, revenue capture, and customer trust.
Service Advisor Elena, 34 - Elena manages a busy lane with dozens of repair orders per day. She needs to quickly spot eligible recalls on the vehicles she is checking in and get them into the right workflow without slowing the customer experience.
Service Manager Jordan, 48 - Jordan is accountable for throughput, CSI, and lost opportunities. He needs visibility into recall completion rates, bottlenecks, and which teams are falling behind so he can intervene early.
BDC / Campaign Coordinator Priya, 29 - Priya monitors service campaigns across multiple rooftops and helps with customer outreach. She needs a reliable queue of eligible vehicles and a simple way to prioritize follow-ups by campaign urgency and parts availability.
Elena is checking in a pickup truck for routine service. As soon as she scans the VIN, RecallPilot surfaces two open manufacturer campaigns and tells her one can be completed today because the parts are in stock. She offers the work during the write-up, attaches it to the repair order, and sends the truck straight into the right queue instead of missing the opportunity.
Later, Jordan opens the dashboard and sees that the store completed 71% of eligible campaigns that came through the lane this week, up from 19% last month. He also sees two pending items blocked by parts and one advisor who needs coaching because of repeated declinations without reason codes.
By standardizing detection, offer, and closeout, the dealership turns work it was already seeing into completed, reimbursable service. Customers get safer vehicles, the team gets a cleaner process, and the business captures revenue that was previously left on the table.
Team & resourcing - Small cross-functional team - 2 engineers, 1 product designer, 1 QA, part-time PM, and access to a dealership operations SME.
Paste this into Cursor, Bolt, Lovable, or v0 to start building.
Build a web app called RecallPilot for dealership service departments to detect, prioritize, and execute manufacturer recalls and service campaigns on vehicles already in the shop. Core product: Service advisors enter or scan a VIN, the app checks open recalls/campaigns, shows which are actionable, and lets the advisor offer, approve, decline, or complete the work. Managers need dashboards showing completion rates, stale opportunities, reasons for declines, and store/advisor accountability. The app must support multi-store tenants, role-based access, audit logs, and integrations to DMS and recall data sources. Primary screens: 1. Login/SSO screen 2. Store selection and onboarding/settings 3. VIN lookup / service queue screen with campaign results 4. Repair order detail screen with recall workflow actions 5. Manager dashboard with KPI charts, filters, and exception lists 6. Admin screen for integrations, roles, and alert thresholds Core flows: 1. Enter or scan VIN, validate it, fetch campaigns, show freshness and eligibility. 2. Attach eligible campaigns to an existing RO, capture approval or decline reason, and assign the work. 3. Update campaign status through in progress and completed states, with timestamped audit history. 4. Manager reviews stale open items, exports data, and monitors completion trends by store and advisor. Data model: Tenant, User, Role, Store, AdvisorProfile, Vehicle, VINLookup, RecallCampaign, CampaignEligibility, RepairOrder, RepairOrderCampaignLink, CampaignStatusHistory, DispositionReason, Notification, IntegrationConnection, AuditLog. Default stack: Frontend: Next.js, React, TypeScript, Tailwind CSS, shadcn/ui Backend: Node.js with NestJS, REST APIs, Zod validation Database: PostgreSQL with Prisma ORM Jobs/queues: BullMQ with Redis Auth: Auth.js or enterprise SSO via Okta/Entra ID Charts: Recharts or ECharts Observability: OpenTelemetry, Sentry, and structured logs Deploy: Docker on AWS with RDS, ElastiCache, and S3 Requirements: Implement responsive, tablet-friendly UI for service lane users, fast VIN lookup with loading and error states, configurable role permissions, audit trail, and analytics events for VIN scanned, campaigns identified, offered, declined, completed, and exception flagged. Include seed data and a clean dashboard experience. Use realistic placeholder integrations for DMS and manufacturer campaign feeds with adapter interfaces so they can be swapped later. Make the product feel enterprise-ready, polished, and fast.
Establish tools, processes, and accountability to ensure consistent and efficient execution of manufacturer recalls and campaigns on all eligible vehicles brought into our service departments. Only a fraction of open campaigns are completed when trucks are in our shops, leaving revenue and customer goodwill on the table. There is a lack of visibility, consistency, and urgency to execute these at scale.
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