Security and Compliance
TurboHire offers a military-grade security of customer data that has been verified by large organizations to meet their security requirements. TurboHire has further received a CIS, ISO27001 certification.
Measures have been implemented by TurboHire for compliance with GDPR that took effect on May 25, 2018. TurboHire further stays up-to-date with new regulations on data privacy and HR practices
TurboHire uses the industry-standard Transport Layer Security (TLS) 1.2 or later protocol with 2,048-bit RSA/SHA256 encryption keys, as recommended by CESG/NCSC, to encrypt communications between the customer and the cloud, internally between Azure systems and datacenters
TurboHire has a military-grade security against various kinds of attacks on data to prevent any kind of data breach like DDoS, MitM, SQL Injection, annual VAPT
Authentication and Access Control
TurboHire uses IdentityServer (https://identityserver.io/), an OpenID Connect and OAuth 2.0 framework for ASP.NET Core, for authorization and identity management.
TurboHire runs a strict security measurement for the chosen third-party partners to allow for data protection and adherence to the security offered by TurboHire
TurboHire ensures all the data stored by a customer is only accessible by the customer itself. We have both mechanisms of private and shared cloud environment for our customers. TurboHire uses SHA256 encryption for data at rest
Backup, BCP and DR
TurboHire is committed towards data protection and business continuity. It does backup of every resource to protect customers against any disaster.
TurboHire provides customers with strong data security, both by default and as customer options.
TurboHire is committed to serve the compliances and follows the guidelines of public clouds which enables it to offer a comprehensive set of compliance offerings to help your organization comply with national, regional, and industry-specific requirements governing the collection and use of data.
Evidence-based algorithms to prevent bias and clarity in decision making using Meta-data driven matching algorithms
Documented and clear feature inputs to avoid modelling of sensitive data
Compliant data access policies and models for national, regional and industry-specific requirements
Adaptability of models for the organizational use-cases by provisions for training on organizational data