About the Company

The customer is one of India’s fastest-growing quick-commerce platforms, operating at massive scale across multiple cities and serving millions of consumers.

As the business expanded rapidly, the company needed to build and manage a large blue-collar workforce to support last-mile operations. This included not just hiring riders, but actively managing their progression through early productivity milestones to ensure consistent service levels and cost efficiency at scale.

The Challenge

As workforce volumes increased, the company’s human-led workflows began breaking under operational pressure, creating challenges across both acquisition and workforce management.

• High drop-offs early in the funnel:

  Poor connectivity rates and delayed outreach meant many high-intent candidates dropped off before meaningful engagement. Human agents were unable to provide instant turnaround due to high volumes, leading to missed follow-ups and inconsistent reattempts.
  

• Rising workforce acquisition costs:

  Manual outreach, repeated call attempts, and low early-stage conversions drove up acquisition costs as hiring scaled, putting pressure on unit economics.
  

• Limited visibility into the workforce funnel:

  The workforce journey was spread across fragmented systems, offering little real-time insight into lead movement, drop-offs, or bottlenecks, making it difficult to optimize performance or intervene proactively.
  

• Inconsistent progression to productivity:

  Beyond onboarding, the company struggled to consistently engage workers through critical milestones such as first login, first order completion, and early productivity thresholds. This led to drop-offs before workers became fully productive.
  

Together, these challenges highlighted the need for a system that could scale outreach, bring structure to workforce management, and improve acquisition efficiency, without compromising experience.

The Solution

AI-Led Blue-Collar Workforce Management with Human Escalation

SquadStack deployed a unified AI + human orchestration model where AI owned the primary blue-collar workforce lifecycle, and human experts intervened only at defined, high-value escalation points.

AI Ownership Across the Workforce Lifecycle

AI was responsible for managing the end-to-end, high-volume stages of blue-collar workforce management:

• Primary lead handling at scale: AI engaged with the majority of incoming leads immediately, ensuring no delays or missed follow-ups due to volume spikes.
  

• End-to-end lifecycle execution: AI managed worker journeys from onboarding through first login, first order completion, and early productivity milestones without human dependency.
  

• Persistent engagement and reattempts: AI systematically re-engaged workers across stages, maintaining continuity and momentum through the lifecycle.
  

• Milestone-driven progression: Engagement was structured around predefined milestones, including first order, 10th order, and sustained productivity thresholds.
  

• Live funnel intelligence: Every interaction was captured in real time, giving complete visibility into movement, drop-offs, and performance across the workforce funnel.
  

Where Humans Added Depth

Human experts were intentionally deployed only where AI escalation was required, ensuring focus on quality rather than volume:

• High-intent or complex conversations: Workers needing clarification, reassurance, or contextual guidance were seamlessly handed off to human agents.

• Exception handling: Edge cases and non-standard journeys were resolved through human judgment.

• Critical transition validation: Humans ensured readiness at key transition points without owning the full funnel.

This design allowed AI to act as the default operating layer, while humans functioned as a specialised depth layer, not a fallback.

The Impact

The AI-led operating model delivered measurable improvements across cost efficiency, scale, and workforce productivity, while maintaining enterprise-grade quality.

The Impact

The unified AI + human operating model delivered measurable improvements across cost efficiency, scale, and workforce productivity, while maintaining consistent execution at high volumes.

• 40% reduction in workforce acquisition cost, driven by instant outreach, higher connectivity, and structured funnel management across the system
  

• 90%+ connectivity across workforce journeys, ensuring reliable engagement at scale even during volume spikes

• ~15% of onboarded workers completed First Login, First Order (FLFO) milestone
  

• ~10% of onboarded workers progressed to the 10th-order milestone and beyond.
  

• Sustained worker engagement observed beyond the 10th order, with a meaningful share of workers continuing toward deeper productivity milestones, indicating long-term workforce quality and retention
  

Together, these outcomes enabled the company to scale its blue-collar workforce efficiently without proportionally increasing operational complexity or manual effort, while creating a predictable pipeline of productive workers.

Conclusion & Looking Ahead

By designing AI and humans to work together as peers executing distinct roles within a single workflow, the company transformed a traditionally manual, high-cost workforce operation into a scalable, insight-driven operating engine.

AI brought speed, scale, and consistency to high-volume stages, while human expertise delivered judgment, trust, and contextual guidance where it mattered most. Together, this unified model aligned acquisition economics, workforce productivity, and experience at scale.

Looking ahead, the platform is exploring the extension of this operating model to additional blue-collar roles, including packer workforce onboarding and productivity management, further reinforcing its ability to manage diverse frontline workforces through a unified AI + human system.