Company Profile
Challenges Before FawksAI
- 22% NDR rate — 9,900 failed deliveries/day at ₹80–120 each = ₹18L+ daily losses
- 38% of NDRs: customer not home — no pre-delivery availability confirmation
- 29% of NDRs: incomplete or wrong address — discovered only when delivery partner arrives
- 12-minute average support wait for customers wanting to reschedule
- Merchant SLA clauses triggering penalty payments at delivery rates below 85%
The ₹18L/Month NDR Problem Killing Last-Mile Margins
SwiftDeliver Logistics — handling 45,000 daily shipments for 300+ D2C and e-commerce clients — was experiencing a 22% Non-Delivery Report (NDR) rate. In absolute numbers: 9,900 failed delivery attempts every single day. At ₹80–120 per failed attempt (re-delivery costs, storage, reverse logistics), this translated to ₹18 lakhs in daily losses.
Enterprise merchant clients had NDR-linked SLA clauses in contracts. If SwiftDeliver's successful delivery rate fell below 85%, penalty clauses triggered. At a 78% success rate, penalties were already accumulating.
Why 22% of Deliveries Were Failing
An audit of NDR reason codes across 30 days revealed the breakdown:
- Customer not available (38% of NDRs): Customer was at work, market, or hospital — simply not at the delivery address during the attempt window. No prior notice was given
- Address incomplete or incorrect (29% of NDRs): Missing landmark, wrong pin code, building name missing — the delivery partner couldn't locate the address without calling the customer manually
- Customer refused delivery (18% of NDRs): Changed their mind after ordering, or COD amount different from expectation — especially for COD orders placed impulsively
- Customer unreachable (15% of NDRs): Phone switched off, wrong number provided at checkout — no way to coordinate
FawksAI Deployment: Pre-Delivery Coordination + NDR Resolution
Pre-Delivery AI Call — NDR Prevention Workflow
The pre-delivery call happens when the delivery partner is 60–90 minutes from the address. Address corrections and reschedules captured during this call are pushed to the delivery app in real time — the delivery partner receives an updated instruction before arriving at the wrong location.
Real-Time WMS Integration
FawksAI integrated with SwiftDeliver's Warehouse Management System (WMS) and the delivery partner app via API. When a shipment was scanned as Out-for-Delivery, FawksAI received the trigger, accessed the customer's contact details and delivery address from the WMS, and initiated the pre-delivery call automatically. Customer responses — confirmed available, rescheduled, address corrected — were written back to the WMS and delivery app in real time.
Impact: Month 2 Post Deployment
Our NDR rate was killing our margins. Every failed delivery cost us ₹100 and a client complaint. FawksAI now calls every customer before the delivery window — confirms they're home, fixes address issues, and offers rescheduling. In 2 months we went from 22% NDR to 5%. That's ₹18 lakhs every month straight back to our bottom line.
AI Pre-Delivery Calls as a Competitive Advantage in Indian Logistics
India's last-mile logistics sector is intensely competitive — Delhivery, XpressBees, Ecom Express, and Shadowfax all competing for merchant contracts on price and SLA. The ability to offer merchants a 90%+ first-attempt delivery rate, real-time NDR visibility, and automated merchant notifications represents a genuine product differentiation that is hard to replicate without AI.
For D2C brands specifically, logistics is an extension of brand experience. A proactive pre-delivery AI call in the customer's language — Hindi, Tamil, Bengali, or English — signals a level of care and organisation that builds brand trust and reduces customer service escalations. NDR reduction is not just an operations metric; it's a customer experience play.
Scaling the Model: From 45K to 2L Daily Shipments
Because FawksAI scales horizontally without additional cost per call, SwiftDeliver's pre-delivery calling capacity scales automatically as shipment volume grows. Adding 10,000 new daily shipments requires no new hires, no additional infrastructure — the AI handles the volume increase transparently. This linear cost structure (vs. headcount-based cost) is why last-mile operators with AI calling have a permanent structural cost advantage over those without.