| Format | Example | Percentage |
|---|---|---|
| Format:firstNameInitiallastName | jdoe@drivertech.com | Percentage:57% |
| Format:lastNameInitial-firstName | d-jane@drivertech.com | Percentage:18% |
| Format:lastName.firstName | doe.jane@drivertech.com | Percentage:17% |
| Format:firstName-lastNameInitial | jane-d@drivertech.com | Percentage:5% |
| Format:firstNameInitial.lastName | j.doe@drivertech.com | Percentage:2% |
| Format:lastName_firstName | doe_jane@drivertech.com | Percentage:1% |
DriverTech employee email verification for instant deliverability checks.
DriverTech was established in 1995 and is headquartered in Salt Lake City, UT. The independent company employs 10‑50 professionals and generates between $10 million and $50 million annually.
DriverTech develops software solutions for the freight delivery sector, focusing on commercial over‑the‑road trucking, emergency vehicles, and military applications.
Its portfolio includes electronic logging devices (ELD), full truckload management (FMT), vehicle GPS tracking, driver inspection reports, navigation tools, for‑hire trucking support, private fleet solutions, telematics, IFTA reporting, dashcams, and more.
Mark Haslam serves as CEO and owner, steering the company’s product strategy alongside a leadership team that covers engineering, operations, client services, sales, and IT.
DriverTech uses 6 email formats across its organization. The most common pattern is firstNameInitiallastName (e.g., jdoe@drivertech.com), used in approximately 57% of work addresses.
DriverTech currently employs over 10-50 people from United States, with a head office in Salt Lake City, UT, US.
SignalHire complies with the General Data Protection Regulation (GDPR). SignalHire follows GDPR requirements, including but not limited to rights of data subjects to access, correct, or delete their personal information and supports the right to be forgotten.
SignalHire is CCPA-compliant and provides California residents the right to know, access, opt out, and request deletion of their personal data.
