All Case Studies
NestawayProperty Management

How Nestaway Resolved 68% of Tenant Requests with AI

68% of tenant requests resolved by AI - across 15,000 apartments and 12 cities.

What this engagement delivered.

  • 0168% of tenant requests resolved by AI without human involvement
  • 02<5 min average time to close a tenant request
  • 03+35 pts increase in tenant NPS post support interaction

The Challenge

Nestaway is India's largest property management company, managing more than 15,000 apartments across 12 cities. Operating at this scale means managing a continuous and high-volume stream of tenant interactions - from maintenance requests and document queries to KYC updates and payment coordination. With a portfolio of this size, delivering consistent, high-quality tenant support is a significant operational challenge.

Nestaway's tenant support operation was under sustained pressure. Tenants across 12 cities were reaching out 24/7 with requests that were individually simple but collectively overwhelming.

High-volume repetitive requests. The majority of inbound tenant contacts involved routine tasks: logging maintenance complaints, downloading rental receipts, updating KYC documents, and answering standard queries. Each task was low complexity but required a human representative to handle.

Round-the-clock demand. Tenant requests did not follow business hours. A large team of support representatives was required to cover this demand, with no mechanism to triage or automate routine cases.

Inconsistent experience. With a large support team handling high volumes, conversation quality and response time varied. There was no consistent standard of service delivery across the portfolio.

Our Approach

Brahmastra Labs deployed a full three-channel AI workforce for Nestaway, covering voice, WhatsApp, and email.

Proprietary PMS integration. The AI integrated directly with Nestaway's custom-built, in-house property management system, enabling it to authenticate tenants, verify residency, pull contract details, and log actions in real time.

SOP-based training. The AI was trained on Nestaway's internal business processes and support SOPs, ensuring every interaction followed the same standard the human support team was expected to maintain.

Conversation reinforcement training. Historical support conversations between Nestaway's team and tenants were used to fine-tune the AI's understanding of which conversation types to handle autonomously and which to escalate.

Omnichannel deployment. The AI was deployed across voice, WhatsApp, and email simultaneously, meeting tenants on the channel of their choice and maintaining consistent context across interactions.

The Results

Following deployment across Nestaway's portfolio:

68% of all tenant requests are now fully resolved by AI without any human involvement.

Average task completion time is under 5 minutes from first contact to resolution.

Tenant NPS following a support interaction increased by 35 points.

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