Pricing

Human vs. AI workforce - modeled for India NBFCs & banks

Benchmarks use typical loaded payroll bands for acquisition, credit, collections, and operations roles in Indian metros and tier-1 hubs. Figures are illustrative in INR (lakhs/crores as noted)-not a quote. LLM and telephony are usually metered separately, consistent with global per-run agent pricing models.

Illustrative savings band

~55-85%

Typical reduction in modeled variable labor when high-volume steps-GST/banking pulls, stips, early buckets, and ops queues-move to agents, freeing teams for credit committee, restructuring, and compliance depth.

More qualified files without proportional RM / ops hiring

DSA feeds, inbound digital, and branch referrals still mean manual follow-up, document collection, and LOS hygiene. Agents run the repetitive playbook; RMs focus on closure and complex cases.

Typical human benchmark (India)

Relationship executives, sales ops, and credit assistants in metros often sit in roughly ₹6-₹18 LPA base bands before EPF/ESI and variable pay; blended loaded monthly cost per productive FTE commonly ₹55K-₹1.4L+ depending on city and channel.
Each serious lead still consumes 20-40+ minutes across calls, WhatsApp, and data entry.
Festival seasons and campaign spikes force temp hiring or SLA slips.

NBFC and private-bank recruiter surveys and Naukri/Glassdoor ranges are directional; your incentive structure changes effective cost per file.

AI workforce + LendingIQ (illustrative)

Structured vernacular scripts, document checklist chasing, and CRM/LOS updates with audit trail.
Usage-based platform fee + per-workflow metering; LLM and SMS/WhatsApp channels at transparent rates.
Human approval before soft pull / hard pull or final offer where RBI fair-practices require it.

Teams often model ₹ per completed lead package or per file ready for credit-your product mix sets the effective rate.

Example: retail / PL-LAP acquisition funnel

~3,200 meaningful conversations/month previously staffed with ~4 FTE of mixed sales-ops capacity.

Modeled human run-rate

~₹18-₹28 lakh/mo loaded labor (illustrative model)

Modeled AI + LendingIQ

~₹2.5-₹6 lakh/mo LendingIQ + LLM/MSG usage for comparable throughput (illustrative)

Typical savings vs model

Often ~65-82% vs. modeled human run-rate at this volume

How to read these numbers

All figures are illustrative INR models-not a commercial quote. City tier, captive vs outsourced, and incentive design change both human and AI economics.
GST and TDS treatment of software and AI services should be confirmed with your tax advisors.
We build a calibrated ROI model from your LOS/LMS volumes and channel mix during an AI audit.

Reference

Reserve Bank of India - regulations & circulars

Want numbers tied to your LOS, channels, and SLAs- We’ll calibrate human baselines and agent throughput in a short working session.

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