Vehicle Truth Engine by TransferAuto

The end-to-end vehicle verification ecosystem, combining live OBD evidence, vehicle records and AI from pre-purchase checks to ownership transfer.

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Inspiration

Buying or transferring a used vehicle is still a fragmented process. Mechanical diagnostics, historical records, paperwork and customer support usually live in separate tools, providers and workflows.

We built TransferAuto AI Vehicle Ecosystem to connect those layers into one closed-loop system.

What it does

TransferAuto AI Vehicle Ecosystem is an end-to-end platform for vehicle intelligence and transactions.

It combines:

  • OBD Scan Pro for free live vehicle diagnostics using compatible OBD adapters
  • TransferAuto Analytics for Spain + international vehicle reports
  • TransferAuto Online for transfer, registration and vehicle paperwork workflows
  • DORA, our 24/7 AI transaction assistant on WhatsApp

The system is designed so that a user can start with a free vehicle scan, understand the vehicle better, verify its history, and complete the next step inside the same ecosystem.

For this submission, we are focusing on a new AI layer that turns raw vehicle evidence into an explainable decision workflow. We combine live OBD data, vehicle records and workflow logic, then use GPT-5.6 to generate a structured summary of:

  • what is known
  • what looks inconsistent
  • what is still unknown
  • what should be checked next
  • what action the user can take next

How we built it

We built the project as a connected ecosystem instead of a single isolated app.

  • OBD Scan Pro captures live vehicle data from the car
  • TransferAuto Analytics provides report and verification context
  • TransferAuto Online connects the insight layer with real vehicle transactions
  • DORA helps guide the user through support and workflow automation
  • OPEN AI API is used to transform structured evidence into clear, useful explanations, and maintance conected all the ecosystem
  • Codex was used during Build Week to accelerate implementation, iteration and integration work

At the center of the platform is a closed-loop intelligence model: the more diagnostic interactions and verification workflows the system processes, the more useful and scalable the ecosystem becomes.

Challenges we ran into

One of the main challenges was combining very different sources of truth in a responsible way.

Vehicle diagnostics are noisy and vary by brand, model and ECU coverage. Historical and administrative data also varies by availability and source. Another challenge was making the output understandable for normal users without overstating certainty.

We wanted the system to explain risk clearly, without pretending to know more than the evidence actually supports.

What we learned

We learned that the real value is not only in diagnostics or reports alone, but in connecting the full user journey:

  1. attract users with a free utility
  2. verify the vehicle with deeper intelligence
  3. convert that insight into a real transaction or service
  4. automate support and operations through AI

We also learned that GPT-5.6 works best when it receives structured evidence and clear boundaries, instead of being asked to guess.

What's next

Our next steps are:

  • expand vehicle and ECU coverage
  • improve the evidence comparison layer
  • deepen B2B workflows for professionals
  • expand international report intelligence
  • continue automating vehicle transactions and support flows with AI

Our goal is to build the trust and decision layer for vehicle ownership, verification and transfer.

Built With

  • agents
  • ai
  • analytics
  • android
  • apps
  • automation
  • backend
  • business
  • cloud
  • codex
  • customer
  • data
  • gpt-5.6
  • ios
  • mobile
  • obd-ii
  • openai
  • postgresql
  • reports
  • support
  • vehicle
  • verification
  • whatsapp
  • workflow
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