LocalMatch

Find nearby in-stock parts before you wait days for shipping.

LocalMatch is an AI-assisted part lookup tool for service teams and parts counter staff that checks a requested part number against nearby retailers within a customer’s ZIP code. It reduces repair delays by surfacing likely local availability, alternates, and store contact details in seconds so teams can choose the fastest fulfillment path.

Business Goals

  • Reduce average time-to-part-decision from 20 minutes to under 2 minutes within 90 days of launch.
  • Increase repair ticket first-time completion rate by 10% within 6 months by reducing STO-related delays.
  • Drive a 15% lift in customer satisfaction scores for jobs that require parts sourcing within 2 quarters.
  • Achieve 40% weekly active usage among eligible service tickets within 120 days.
  • Create a 25% reduction in manual parts sourcing calls to local stores within 6 months.

User Goals

  • Check a part number against nearby stores in seconds.
  • See only likely-matching stores inside a defined ZIP or radius.
  • Get confidence indicators and alternates when the exact part is unavailable.
  • Save verified matches to the customer ticket or work order.
  • Avoid waiting days for shipping when a local option exists.

Non-Goals

  • We are not a marketplace that sells inventory directly or processes checkout.
  • We are not replacing OEM catalog systems or enterprise parts ERP.
  • We are not guaranteeing real-time store inventory unless a source provides it.
  • We are not building a consumer shopping app for unrelated retail categories.

Service Advisor Dana, 38 - Dana works at a repair counter and needs to keep customers informed on part arrival times. She wants a fast way to know whether a local store can save the job from a multi-day wait.

Service Advisor Dana, 38

  • As a service advisor, I want to enter a part number and ZIP code, so that I can tell the customer the fastest realistic sourcing option.
  • As a service advisor, I want the system to show confidence and source freshness, so that I know whether to trust the result.
  • As a service advisor, I want to attach the result to the work order, so that everyone on the team sees the same sourcing decision.

Parts Manager Leo, 52 - Leo manages parts sourcing for a busy repair shop and frequently handles urgent requests. He needs fewer calls, less manual searching, and a consistent process for substitutes.

Parts Manager Leo, 52

  • As a parts manager, I want to search multiple local sources at once, so that I can find parts without calling each store individually.
  • As a parts manager, I want alternates and compatible SKUs suggested, so that I can keep the repair moving if the exact part is missing.
  • As a parts manager, I want an audit trail of what was checked, so that I can explain sourcing decisions later.

Independent Tech Priya, 29 - Priya is an independent technician who handles repairs on tight timelines. She needs a simple mobile-friendly way to find a local part before committing to a long delay.

Independent Tech Priya, 29

  • As a technician, I want to scan or paste a part number from my phone, so that I can check availability while I am on-site.
  • As a technician, I want a map and call button for nearby stores, so that I can reserve or confirm stock quickly.
  • As a technician, I want to know if the result is exact-match or possible-match, so that I do not waste time on false positives.

Part Number Search and Normalization · High priority

  • Accept user-entered part numbers from text entry, clipboard paste, or scan and normalize them before searching local sources.
  • Support alphanumeric part numbers with punctuation stripping, whitespace cleanup, and common manufacturer prefix handling.
  • Detect likely OCR mistakes from camera input and prompt the user to confirm ambiguous characters.
  • Validate minimum query quality and warn when the input is too short or too generic.
  • Store the original part number and normalized query separately for auditability.

Local Inventory Cross-Check · High priority

  • Query nearby retailers and source systems to identify likely in-stock matches within a ZIP code or radius.
  • Allow searching by ZIP code, city, or geofenced radius with defaults based on the user profile.
  • Rank results by distance, source freshness, exactness of match, and confidence score.
  • Show exact match, probable match, and alternate compatible part separately.
  • Fallback gracefully when a source times out by showing partial results and source status.

Result Confidence and Decision Support · High priority

  • Explain why a result was returned so users can trust and act on it quickly.
  • Display confidence score with clear labels such as exact, likely, or needs review.
  • Show source timestamp, store name, phone number, hours, and whether inventory data is live or estimated.
  • Provide alternate SKUs or equivalent parts when exact inventory is unavailable.
  • Highlight results that are stale or missing critical fields so users know when to verify by phone.

Work Order and CRM Integration · Medium priority

  • Attach sourcing results to customer tickets and service records to avoid rework and improve continuity.
  • Export search results to CSV and PDF for manual workflows.
  • Push selected results into a work order note via API integration.
  • Link search history to customer/job identifiers with permissions-based access.
  • Support webhook events for downstream systems when a part match is saved.

Admin Configuration and Monitoring · Medium priority

  • Let operations teams configure store sources, search rules, and alerting while monitoring quality and usage.
  • Configure source priority by retailer, manufacturer, or region.
  • Manage ZIP code coverage and radius limits per business unit.
  • View system health by source, including timeout rates and match quality.
  • Set alerts when source freshness or success rates fall below thresholds.

Fast Start Lookup

  • Open LocalMatch from desktop, tablet, or mobile.
  • Paste, type, or scan the part number.
  • Enter ZIP code or allow location access for a default search radius.
  • Review results with confidence, distance, and source freshness.
  • Save the best match to the job or call the store directly.
  • Time to first useful result should be under 15 seconds for 90% of searches.

1. Capture the part request

  • The user enters a part number or scans a label. The app normalizes the value and validates that it looks like a real part before searching.
  • Show inline validation if the input is too short, contains only symbols, or appears ambiguous.
  • Preserve original and normalized forms for later review.
  • If OCR confidence is low, ask the user to confirm the characters before continuing.

2. Set search area

  • The user supplies a ZIP code or uses their current location. The app resolves nearby stores inside the chosen radius.
  • Default radius should be 10 miles, expandable to 50 miles.
  • If location permission is denied, fall back to manual ZIP entry.
  • Show a count of sources being searched before the query runs.

3. Search local sources

  • The system queries configured sources and aggregates results into a single ranked view.
  • Handle timeouts per source without failing the whole search.
  • Deduplicate results from the same chain or store cluster.
  • Surface source freshness and note when data is older than a configured threshold.

4. Review match quality

  • The user compares exact matches, likely matches, and alternates to determine the best option.
  • Display match type, confidence score, distance, and store availability status.
  • Flag probable matches that require phone verification.
  • If no exact match is found, show closest alternates and suggest expanding radius.

5. Act and save

  • The user calls the store, navigates to it, or saves the result to the job record.
  • One-tap call, map, and copy part number actions.
  • Allow saving a selected result with notes and timestamp.
  • When no result is found, offer a resend with broader radius or alternate source set.

Advanced Capabilities

  • Saved source profiles by store region, brand, or technician team.
  • Suggested alternates based on manufacturer cross-reference tables.
  • Batch lookup for multiple part numbers from a repair estimate.
  • Store-hours and holiday-aware filtering.
  • Result history with repeat-query shortcuts for frequently used parts.
  • Manual override mode for admins to mark confirmed local stock.

Interface Principles

  • Large part-number input with strong contrast and scan-first mobile layout.
  • Clear ranking cards with exactness, distance, and freshness shown above the fold.
  • Accessible color system that does not rely on color alone to indicate match confidence.
  • Fast-loading results with skeleton states and partial-result rendering.
  • Persistent action buttons for call, map, save, and export.
  • Keyboard-friendly desktop workflow for counter staff using only tab and enter.

Dana receives a repair request for a washer motor assembly that would normally take several days to arrive through standard shipping. She opens LocalMatch, pastes the part number, and enters the customer’s ZIP code. Within seconds, she sees two nearby hardware retailers with likely matches and one exact match flagged as freshly updated.

Instead of telling the customer to wait for STO, Dana calls the closest store, confirms stock, and books the repair for the next day. The customer gets a faster fix, Dana spends less time on manual searching, and the shop avoids losing the job to a long fulfillment delay.

User-Centric Metrics

  • Median time from part request to actionable result under 15 seconds.
  • At least 80% of searches produce a clear exact, likely, or alternate match outcome.
  • Reduce manual call-outs to local stores by 25% within 6 months.
  • Achieve a 4.5 out of 5 satisfaction rating from service staff after 90 days.
  • Increase successful same-day or next-day repair scheduling by 10% for part-dependent jobs.

Business Metrics

  • 40% weekly active usage among eligible repair tickets within 120 days.
  • 15% improvement in customer satisfaction for jobs involving part sourcing within 2 quarters.
  • 10% increase in first-time completion for parts-dependent repairs within 6 months.
  • 20% reduction in average sourcing labor cost per job within 6 months.

Technical Metrics

  • 99.9% uptime for search and results APIs.
  • P95 search latency under 2.5 seconds for aggregated local queries.
  • Source connector failure isolation so one bad source does not block overall results.
  • All user and query data encrypted in transit and at rest.

Tracking Plan

  • part_search_started
  • part_search_validated
  • source_query_completed
  • source_query_timed_out
  • result_viewed
  • result_saved_to_job
  • store_call_clicked
  • map_opened
  • alternate_selected
  • search_no_match

Technical Needs

  • Frontend in Next.js with mobile-first responsive components.
  • Backend API in Node.js or TypeScript with a job queue for source aggregation.
  • Search orchestration using PostgreSQL for core records and Redis for caching.
  • Background workers for API polling, normalization, and freshness checks.
  • OCR and barcode scanning support via a mobile camera library such as Google ML Kit or a browser-based scanning package.
  • Observability with OpenTelemetry, structured logs, and dashboards in Datadog or Grafana.
  • Role-based access control for admins, managers, and standard users.

Integration Points

  • Google Maps Places API or Mapbox for location and routing context.
  • Retailer inventory or catalog APIs where available, including chain-specific connectors.
  • Manufacturer catalogs or cross-reference datasets for compatibility mapping.
  • Auth via Auth0, Clerk, or Microsoft Entra ID for business accounts.
  • Webhook integrations to common work order systems such as ServiceTitan, Salesforce, or HubSpot where applicable.

Data Storage & Privacy

  • Store only the minimum customer/job metadata needed to link a lookup to a work order.
  • Encrypt search history, user identity data, and any saved job notes at rest.
  • Respect GDPR and CCPA requests for export and deletion of personally identifiable data.
  • Do not persist raw location beyond what is needed for the search unless the user consents.
  • Log source usage and query metadata without storing sensitive customer details in analytics events.

Scalability & Performance

  • Cache common part lookups and source metadata for short periods to reduce repeated calls.
  • Use per-source rate limits and circuit breakers to protect against partner API instability.
  • Support horizontally scalable worker pools for concurrent ZIP-based searches.
  • Paginate and lazy-load result sets so dense metro queries remain responsive.

Potential Challenges

  • Inventory data may be stale or inaccurate; mitigate by showing freshness timestamps and confidence labels.
  • Retailer APIs may differ widely; mitigate with an adapter layer and a source onboarding checklist.
  • False-positive matches could mislead users; mitigate with exact-versus-likely result separation and verification prompts.
  • Rate limits and timeouts could slow searches; mitigate with caching, retries with backoff, and source health monitoring.
  • Users may expect guaranteed availability; mitigate with clear product copy stating that results are best-effort and must be confirmed before commitment.

Team & resourcing - Small team - 2 engineers, 1 designer, part-time PM, and shared QA/ops support.

Phase 1: MVP Lookup Flow · Weeks 1-4

  • Part number input with normalization and validation
  • ZIP/radius search form
  • Single aggregated results page with confidence, distance, and freshness
  • Basic save-to-job notes
  • Analytics for search start, result view, and save actions

Phase 2: Source Connectors and Ranking · Weeks 5-8

  • Retailer source adapter framework
  • At least 2 live inventory or catalog integrations
  • Ranking engine for exactness, distance, and freshness
  • Timeout handling and partial-result rendering
  • Admin source configuration screen

Phase 3: Workflow Integrations · Weeks 9-12

  • Work order export and webhook support
  • Role-based access control
  • Search history and repeat-query shortcuts
  • Call, map, and copy actions on results
  • Mobile camera scan support for part labels

Phase 4: Optimization and Scale · Weeks 13-16

  • Caching and rate-limit controls
  • Monitoring dashboards and alerting
  • Alternate part suggestions and compatibility mapping
  • A/B testing for ranking and result layout
  • Compliance-ready data export and deletion tooling

Paste this into Cursor, Bolt, Lovable, or v0 to start building.

Build a mobile-first web app called LocalMatch that helps repair teams and parts staff check a part number against nearby local stores within a ZIP code or radius and quickly find likely in-stock matches.

Core product requirements:
1) Part lookup flow
- Users can type, paste, or scan a part number.
- Normalize input by trimming spaces, removing common punctuation, and preserving original plus normalized values.
- Validate the part number before search and handle low-confidence OCR or ambiguous characters.
- Users enter a ZIP code or use current location; default radius is 10 miles and can expand up to 50 miles.

2) Search orchestration and results
- Query multiple source connectors in parallel and aggregate results.
- Rank results by exactness, confidence, source freshness, and distance.
- Show result cards with store name, address, distance, phone, hours, source freshness timestamp, match type, and confidence.
- Support exact match, likely match, and alternate part suggestions.
- If one source fails or times out, show partial results and source status instead of failing the search.

3) Actions
- One-click call store, open map, copy part number, and save result to job notes.
- Include a simple export to CSV/PDF for manual workflows.
- Add a searchable history page with previous lookups and saved results.

4) Admin
- Admins can configure sources, search radius defaults, and result ranking preferences.
- Add a source health dashboard with timeout rate, freshness, and match volume.

Suggested tech stack:
- Frontend: Next.js, TypeScript, Tailwind CSS, shadcn/ui
- Backend: Next.js API routes or Node.js NestJS, TypeScript
- Database: PostgreSQL with Prisma
- Cache/queue: Redis with BullMQ
- Auth: Auth0 or Clerk
- Maps: Google Maps or Mapbox
- OCR/scan: Google ML Kit or a browser camera scanning library
- Analytics: PostHog
- Observability: OpenTelemetry + Datadog or Grafana

Data model:
- User(id, name, email, role, organizationId)
- Organization(id, name)
- Search(id, userId, organizationId, originalPartNumber, normalizedPartNumber, zipCode, radiusMiles, status, createdAt)
- SearchResult(id, searchId, sourceId, storeName, address, phone, distanceMiles, matchType, confidenceScore, freshnessTimestamp, inStockStatus, alternatePartNumber, mapUrl, callUrl)
- Source(id, name, type, status, configJson, lastHealthCheckAt)
- JobLink(id, searchId, externalWorkOrderId, notes)

Primary screens and flows:
- Login / organization selection
- New lookup page with part input, ZIP/radius controls, and scan action
- Results page with ranked store cards and action buttons
- Search history page
- Admin source configuration and health page

Build the app with clean responsive UI, fast loading states, skeletons, accessible contrast, keyboard navigation, and mobile-friendly touch targets. Include seeded demo data and mock connectors so the app works end-to-end even before real integrations are added.

Business Idea

AI agent that cross checks part numbers within the locations zipcode to verify if any local store has it. While it may cause some parts sales to lower, the time saved on customer repairs will easily offset it and provide a much better customer experience. STO's at times take days. If the part is at a local hardware store that the agent can easily check and cross reference, it'll pay off in dividens.

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