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Selly - AI sales bot

AI voice agents for D2C sales + support with real-time CRM integration and analytics

Selly — AI Sales Bot for D2C Calls

A fast-scaling D2C brand was struggling to keep up with customer demand across inbound support and outbound sales. Peak-hour call queues were growing, support quality was inconsistent, and the team had limited visibility into what customers actually wanted—all while operational costs kept rising.

Selly was built to fix that: an AI-powered voice system that automates tier-1 support, qualifies leads, and drives conversions with personalized upsell flows.

The Challenge

As call volumes increased, four problems showed up immediately:

  • Delayed response times during peak call hours
  • Inconsistent support quality and uneven upselling outcomes
  • Limited insights from call transcripts and customer intent
  • High operational costs from manual call center workflows

The Solution: Conversational AI Voice Agents

We deployed AI-powered voice agents to handle both inbound and outbound conversations—end-to-end.

1) Fully Autonomous Voice Agents (Inbound + Outbound)

Using state-of-the-art ASR (speech recognition), NLU, and TTS, we developed voice agents that could converse naturally and handle:

  • Tier-1 support queries
  • Order tracking and delivery status
  • Product discovery and FAQs
  • Lead qualification and intent routing
  • Upsell prompts based on customer context

2) Intent Detection & Dynamic Workflow Handling

Built using LangChain and AutoGen, Selly adapted in real time based on:

  • User intent (support vs purchase vs complaint vs follow-up)
  • Conversation context (previous messages/orders/history)
  • Sentiment signals (frustration, urgency, positive buying cues)

When required, Selly enabled instant escalation to a human agent with context-preserving handoffs—including summaries and extracted fields.

Voice SS1

3) Real-Time CRM + Knowledgebase Integration

To avoid “generic bot” behavior, Selly integrated directly with:

  • CRM systems (customer profile, past interactions, segmentation)
  • Product catalogs (inventory, pricing, alternatives)
  • Support databases (FAQs, return policy, SOPs)
  • Order systems (status, delivery ETA, cancellation window)

This allowed the agent to deliver personalized, accurate answers and relevant offers during the call.

Voice SS2

4) Analytics Dashboard & Continuous Feedback Loop

We built a live dashboard that turned conversations into decision-grade insights:

  • Auto call summaries and outcome tagging
  • Sentiment heatmaps (by product, category, region, time)
  • Agent performance metrics (resolution, conversion, CSAT proxies)
  • Intent trends and recurring pain points

To keep improving accuracy and outcomes, we implemented:

  • Active learning loops (data-driven intent refinement)
  • Post-call AI evaluations (quality scoring + coaching signals)

Results & Impact

Selly delivered clear business wins within weeks:

  • 70%+ automation of tier-1 support and initial sales outreach
  • Reduced wait times and faster issue resolution during peak hours
  • Improved conversion rates through real-time, personalized upselling
  • Actionable insights from aggregated voice analytics + sentiment signals

What Made Selly Work

A few key principles helped drive real outcomes (not just “cool demos”):

  • Tool-using agents (CRM + order APIs) instead of static scripts
  • Intent-first orchestration to keep conversations goal-driven
  • Escalation with context to protect customer experience
  • Feedback loops to continuously improve agent behavior and KPIs