AI for hiring that gives every candidate a fair look.
We embed engineers inside HR-Tech platforms, enterprise talent teams, and staffing firms for 4 weeks shadow recruiters, sit in interview debriefs, audit ATS hygiene, read every rejection rationale. Then we ship fairness-audited AI every month. 2.6x qualified pipeline at the same cost is not a slide it is what a staffing leader measured in 90 days.
qualified pipeline at same cost
faster time-to-shortlist
lift in offer-to-join conversion
Why "AI hiring" keeps making headlines for the wrong reasons
Fairness was assumed, not audited
Rankers optimised for historical hires reproduce historical biases. Without explicit protected-attribute audits, the model quietly filters out under-represented groups.
The AI was pitched as "autonomous hiring"
Employees and candidates revolt. Legal bans it. The project is killed not by technology but by framing. Human-in-the-loop is the only viable stance.
Candidate privacy was an afterthought
Resume storage, face-biometrics in interviews, and unconsented enrichment trip DPDPA and GDPR. Compliance kills the rollout in user-acceptance testing.
Interviewers got a tool, not training
Even the best scorecard fails without calibration sessions and manager coaching. Tech alone never fixed hiring.
Every metric is a problem we solved.
Real numbers from live HR Tech & recruiting deployments.
Recruiters screen the first 100, not the best
Offer-to-join drops 18%
Onboarding is 40 PDFs across 6 systems
HR helpdesk drowns in repeat queries
What your team actually says.
"I get 4,000 resumes. My recruiter looks at the first 100."
Head of TA
"Hiring bar drifts team to team. Nobody agrees on what good looks like."
Chief People Officer
"22% of offers don't convert. Poaching is up."
Head of Recruiting
"Onboarding is 40 forms across 6 systems."
HRIS Lead
"My HR helpdesk is drowning in leave and payroll queries."
HR Ops
"I see attrition in the exit interview. Too late."
Engagement Lead
Use cases that move the needle.
01Fair Candidate Ranking
Explainable ranking against role competencies with fairness audit on protected attributes.
02Structured Interview Copilot
Interviewer-facing copilot that suggests questions, captures signals, and drafts debriefs.
03Offer-to-Join Retention
Drop-off risk prediction and recruiter playbook per candidate.
04AI Onboarding Orchestrator
One-shot intake that fans out across HRIS, ID, payroll, IT, and asset.
05Employee Helpdesk Copilot
AI answers policy, leave, payroll queries grounded on your HR policy library.
06Attrition Early-Warning
Signals from engagement, pulse, manager feedback, and performance to flag flight risk.
Four pillars. Translated for HR Tech.
An Engineer Inside Your Talent Ops
Our Forward Deployed Engineer shadows recruiters, sits in debriefs, audits ATS data, and interviews hiring managers. They understand why your product org has a 3.4-week TTS while sales has 1.1 and it is not the ATS.
Fairness-First R&D
Our Research Engineers run 2-week sprints on protected-attribute audits, calibration-curve fairness, and candidate-experience measurement so the model survives a DPO review and a candidate complaint.
A Working Release Every 30 Days
Mid-month shadow-mode on one req type. End-of-month rollout to one function. Every release ships with fairness reports, candidate-experience pulse, and manager feedback.
We Own the Quality-of-Hire Number
We don't bill hours. Every month you get delta on pipeline quality, TTS, offer-to-join, onboarding NPS, and 90-day retention. If the numbers aren't moving, you'll know.
What happens in the first 30 days.
Talent Ops Walk & Data Inventory
Our engineer shadows TA, HRIS, and onboarding. Audits ATS, HRIS, LMS, IT provisioning, and policy libraries.
Fairness & Privacy Mapping
DPDPA, GDPR, EEOC (if applicable) obligations translated into audit and consent requirements. Historical-bias baselines measured.
AI Opportunity Scoring & Mockups
Each opportunity scored by quality-of-hire impact, feasibility, and data readiness. Mockups validated with recruiters and hiring managers.
Strategy Deck & Roadmap Delivery
12-month AI roadmap, cost-benefit case, integration architecture, and measurement plan handed over. Yours to keep.
What you walk away with
We speak your regulatory language.
Regulations & Certifications
- DPDPA 2023 — Candidate and employee PII
- GDPR — For EU candidates
- EEOC / OFCCP — US equal opportunity guidance
- POSH Act — Indian workplace-harassment compliance
- Labour Codes — Indian wage and industrial-relations codes
Data & Protocol Standards
- HR Open Standards
- SCIM (user provisioning)
- OAuth / SAML SSO
- OpenID Connect
- OpenAPI / REST
Enterprise Systems We Integrate
- ATS Greenhouse, Lever, Workday Recruiting, SAP SuccessFactors, Naukri RMS, Keka
- HRIS Workday, SuccessFactors, Keka, GreytHR, Zoho People
- LMS Cornerstone, Docebo, Learnyst
- Payroll ADP, Zoho, Razorpay Payroll, Keka
- Engagement Leapsome, Lattice, Engagedly
- Collaboration Slack, MS Teams, Google Workspace
Questions we hear on the shop floor.
Book the 4-Week HR Tech Audit
Fairness-audited · DPDPA / GDPR ready. ATS + HRIS native.
The first step is always a conversation.