Fairness
We actively test for and mitigate bias in every AI model we deploy. No hiring decision should be influenced by protected characteristics. We monitor outcomes continuously, not just at launch.
Responsible AI
AI should explain itself. Every time.
At Bodhitva, responsible AI isn't a policy document — it's an engineering discipline embedded in every product decision, every model deployment, and every customer interaction.
Our Principles
Four commitments that guide every system we build.
Explainability
Every AI-generated recommendation includes a human-readable rationale. Black boxes don't belong in hiring. If we can't explain it clearly, we don't ship it.
Privacy
Candidate and customer data is processed with strict purpose limitation, encrypted at rest and in transit, and never used for model training without explicit consent.
Human oversight
AI assists, humans decide. Every consequential output in HyreSure can be reviewed, overridden, and audited by a human decision-maker.
In Practice
How governance works in our products.
Audit trails
Every AI interaction is logged with timestamps, model versions, input context, and output rationale. Complete traceability from recommendation to decision.
Bias monitoring
Continuous statistical monitoring of AI outputs across demographic dimensions. We don't wait for complaints — we measure proactively and act on anomalies.
Model transparency
Customers can request documentation on model capabilities, limitations, and training data provenance. We publish what our models can and cannot do.
Incident response
Defined escalation path for AI-related concerns, with committed response times. When something goes wrong, we investigate openly and fix systemically.
Standards
Frameworks we build against.
We align our engineering and operational practices with recognized regulatory and industry frameworks.
EU AI Act
GDPR
CCPA / CPRA
SOC 2
EEOC Guidelines
NIST AI RMF
ISO 27001 (target)
India DPDP Act
Our commitment
Responsible AI is not a destination — it's a practice. We commit to continuous improvement in how we build, test, deploy, and monitor AI systems. When we fall short, we will be transparent about what happened and what we're doing to fix it.
We believe the companies that will define enterprise AI are the ones that treat governance as a competitive advantage, not a compliance burden. That's the company we're building.
Questions about our AI practices?
We welcome conversations about responsible AI, governance, and how we approach these challenges.
Contact Our Team