All work

MyLotSpy

Automotive & Dealerships · Inventory Intelligence SaaS

Competitive inventory intelligence for dealership sales teams

A web portal giving dealers detailed visibility into competitor inventory across automobiles, RVs, powersports and marine.

Data pipelinesVertical SaaSSearch
Product viewMyLotSpyReplace with a 16:10 product screenshot

The starting point

A dealership intelligence portal aggregating competitor vehicle inventory data.

What had to change

Competitor inventory data sits across many dealer websites in different shapes and goes stale within hours, so sales teams priced against guesswork.

What couldn't break

Inventory data is scattered across many dealer sites and changes constantly, so the portal had to stay current to stay useful.

Why this was hard

Source sites vary in structure and reliability, and the resulting data still had to arrive as something a salesperson can search in seconds.

What Datics changed

Structured, searchable competitive inventory that sales teams can act on inside their existing routine.

Data pipelines and search built into the portal dealers already open, with no change to how their team works.

System flowMyLotSpy workflow / architectureReplace with a workflow or architecture visual

What changed

Sales teams price and position stock against what is actually on competing lots.

Vehicle categories covered
Automotive, RV, powersports, marine
Inventory sources
Many competitor dealer sites, normalized into one schema
Refresh model
Continuous ingestion, searchable in seconds

Under the hood

Datics role
Data engineering and product delivery: ingestion pipelines, normalization of heterogeneous sources and the search surface dealers use.
Integrations
Competitor dealership inventory sources.
Deployment
DigitalOcean-hosted multi-tenant portal (React, Node.js, PostgreSQL) with scheduled crawling and ingestion pipelines.
Production boundary
Multi-tenant cloud portal.

What this unlocked

A structured inventory corpus is exactly the kind of grounded context an agent can reason over later.

Published write-up on datics.ai

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