Industry dynamics

EV startup Enovate bags 5 billion yuan in new financing round

Publishtime:2019/08/16 Views:6

Shanghai (ZXZC)- Enovate has banked 5 billion yuan ($741,146,950) in a new financing round, which is led by local government industry guidance funds and large-scale state-run banks, the Chinese EV startup announced on October 14 via its WeChat account.

The proceeds from the latest fundraising will be used in the R&D of new vehicle models, the intelligent manufacturing, the construction of sales channels and service system, and the brand promotion.

The startup said it intends to launch IPO in 2021. Currently, relevant preparation works are underway and a new Pre-IPO financing round has kicked off.

EV startup Enovate bags 5 billion yuan in new financing round

Enovate ME7

The ME7, Enovate's first mass-produced model, hit the market on September 19 and was showcased at the Auto China 2020. With post-subsidy prices ranging from 218,800 yuan ($32,430) to 289,800 yuan ($42,960), the Enovate is built on iMA (Intelligent Modular Architecture), Enovate’s self-developed digital complete vehicle architecture, boasting such technical facilities and features as a 5-screen interactive display, AI-enabled voice assistant, “Face ME” facial recognition and “ME Pilot” intelligent driving system.

The EV manufacturer said it will speed up the construction of its offline sales network with the aim of deploying 30 sales outlets in 20 cities by 2020, and over 200 shops in all first-tier and second-tier cities and some third-tier cities by 2025.

What’s more, Enovate attempts to build a comprehensive charging service system that includes fast-charging stations, dedicated charging piles at sales outlets and public charging facilities. By partnering with charging service providers like State Grid and Star Charge, it will develop a charging system covering residential communities, populous business districts and expressways.

The company also revealed that smooth progress is being made in the project of its second production model.