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.

GDPR Compliance

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

Encryption

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

Vulnerability Prevention

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.

Partner Agreements

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

Data Security

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.

Data Segregation

TurboHire provides customers with strong data security, both by default and as customer options.

Compliance

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