The problem of surplus inventory is a logistical and financial headache, but for Josh Kaplan and Dee Murthy, it's a data problem. Their company, Ghost, is a private B2B marketplace that uses AI to match brands with excess stock to retailers looking for deals, aiming to replace opaque, offline broker networks with a scalable, data-driven platform [ghst.io]. Founded in 2021, the Los Angeles-based startup has now raised a total of $95 million, including a $40 million Series C led by L Catterton in late 2024, to build what it calls "intelligent infrastructure" for this massive, fragmented market [Fortune, 2024].
The Wedge: From Apparel to Enterprise Infrastructure
Kaplan and Murthy are not technologists by training, but operators. They previously ran Five Four Group, a men's apparel holding company with several direct-to-consumer brands [TechCrunch 2022]. That experience gave them a ground-level view of the surplus inventory problem: the high costs of storage, the margin erosion from discounting, and the inefficiency of existing liquidation channels. Ghost is their attempt to productize that operational knowledge. The platform functions as a controlled, private network where sellers can list surplus goods and an AI system recommends them to a curated pool of qualified buyers, promising faster turnover and better recovery values than traditional bulk liquidation [ghst.io/privacy-policy].
Funding a Scale Play
Ghost's rapid funding trajectory signals investor confidence in both the market size and the team's operator-led approach. The company moved from a $20 million Series A in mid-2022 to a $30 million Series B in August 2023, before closing its $40 million Series C just over a year later [TechCrunch 2022] [TechCrunch 2023] [Fortune 2024].
| Round | Date | Amount | Lead Investor |
|---|---|---|---|
| Series A | July 2022 | $20M | Undisclosed |
| Series B | August 2023 | $30M | Undisclosed |
| Series C | October 2024 | $40M | L Catterton |
The Competitive Landscape and Scaling Risks
Ghost operates in a competitive space with established players like B-Stock and newer entrants like Syrup and Sotira. The differentiation claim rests on being "AI-native" and built for enterprise-grade speed and control from the outset [ghst.io].
- Data network effects. The platform's AI improves with more transaction data, but attracting that initial volume requires displacing entrenched offline relationships.
- Liquidity management. A marketplace lives or dies by liquidity. Ghost must maintain a high ratio of ready buyers to seller listings to ensure quick sales.
- Enterprise integration. For large brands, moving inventory is tied to complex ERP and warehouse management systems.
The current post-Series C hiring spree, particularly for engineering leadership, suggests the company is investing heavily to address these infrastructure demands [ghst.io/careers]. If the data models fail to accurately predict sell-through or pricing at scale, the platform risks becoming just another digital bulletin board. For now, with nearly $100 million in backing and a team built by operators who have lived the problem, Ghost has the capital and the mandate to try.