For employers
Security, tenant isolation & AI governance
How Feedback AI protects your hiring data, scopes access by organisation, and keeps humans in the loop.
Tenant isolation
Organisation data is scoped server-side. Org admins can only access users, assessments, and candidate records within their organisation. Cross-tenant query parameters are blocked with org-scoped authorization checks.
Defense in depth
- Default-deny middleware on
/api/*with an explicit public allowlist for registration, OTP, and careers browse - Assessment and question routes require authentication and assessment-level access checks
- AI endpoints rate-limited with fail-closed behavior when client IP cannot be determined
- Scheduled jobs (reminders, payment verification) require
CRON_SECRET
Human-in-the-loop hiring
AI generates questions and scores responses, but hiring decisions stay with your team. Integrity signals and authenticity scores are disclosed — never used to auto-reject without review. Verified skill badges require a passing assessment score, giving you a concrete signal beyond résumé keywords.
Data retention
Candidate responses, evaluation records, and audit logs are stored in your organisation's tenant. Production MongoDB is backed up weekly to encrypted off-site storage (AWS S3, ap-south-1) with an eight-week retention window. Contact us for data export or deletion requests per your compliance requirements.
Security testing
- Internal weekly vulnerability scanning — API auth review plus
npm auditin CI - Last structured OWASP Top 10 (2021) review: 31 July 2026 — 0 open critical or high findings
- Public scanners you can re-run: Mozilla Observatory and Qualys SSL Labs. These are automated checks, not a penetration test.
- Third-party penetration test: planned. Written report available to employers on request when completed.
Employer due diligence pack
Pilot and procurement reviews should cover security, candidate transparency, and data handling together.
- This page — tenant isolation, defense in depth, security testing, human-in-the-loop hiring
- Candidate integrity: How assessments work — matching-first, optional PRACTICE
- Privacy Policy — candidate and employer data flows
- Subprocessors — Atlas, OpenAI, Vercel, AWS S3, Resend (see Privacy Policy §4.5)
- Standard Data Processing Agreement (DPA) for EU/UK GDPR prospects — available on request; email support@feedbackai.live from your work domain before uploading candidate PII (T-172)
- Security overview one-pager — infrastructure, controls, and AI handling for employer due diligence
Mohit Kumar Meena is a lead software engineer with nine years of experience and an IIT Madras graduate (B.Tech Engineering Design, M.Tech Automotive Engineering). He founded Future Flow AI Technologies in 2025 and leads product and engineering for FeedbackAI from Bengaluru — match-ranked applicants and structured hiring for teams first; Career Copilot and match-ranked jobs for India tech candidates second. For background, credentials, and consulting, see his personal site.
- IIT Madras — B.Tech, Engineering Design (2012–2016); M.Tech, Automotive Engineering (2016–2017)
- Operated by Future Flow AI Technologies · Bengaluru, India
Mohit Kumar Meena (founder)
Future FlowMohit on LinkedInAbout FeedbackAI (253 followers)
Candidate transparency
Share our candidate-facing integrity page with applicants: How assessments work.