Client: Truck Ohkoku Co., Ltd.
Used Truck Pricing Agent
An AI agent that proposes fair acquisition and resale prices for used trucks
This case study covers how Optimium Inc. built a used-truck pricing AI agent for Truck Ohkoku Co., Ltd., the company behind Truck Ohkoku (トラック王国), a Japanese used-truck marketplace. The agent reproduces veteran buyers' market sense as explainable, evidence-backed price proposals.
Project overview
| Item | Detail |
|---|---|
| Client | Truck Ohkoku Co., Ltd. — operator of the Truck Ohkoku marketplace |
| Timeline | ~4 months (1.5-month PoC + 2.5-month build) |
| Team | 2 Optimium engineers + client-side buyers and sales reps (part-time) |
| Phases | Requirements → PoC → Production build → Operational tuning |
| Key tech | LLM agent, structured transaction-data retrieval, evidence-backed price reasoning |
Problem
Used-truck pricing depends on many variables — year, mileage, body configuration (cranes, refrigeration units, and other bed-mounted equipment), condition, market dynamics. The business relied heavily on veteran buyers' and sales reps' market sense, which slowed acquisition decisions, made onboarding hard, and left price revisions on slow-moving stock to be addressed too late.
Approach
- Structured both the company's transaction history and public market data into a referenceable corpus
- Built an agent that, given a vehicle description, proposes a market band, recommended acquisition price, resale range, and revision suggestions for slow-moving inventory — each with reasoning
- Set up an operating loop where buyer overrides flow back into the dataset, so edge cases improve the model over time
Outcome
- Faster initial pricing decisions, especially for time-sensitive auctions
- Captured veteran buyers' tacit knowledge as explainable rationale, sharable with junior staff
- Reduced case-by-case variance in pricing outcomes and shortened inventory holding periods