Issue № 02Agentic AI

Autonomous Sales Agent

An AI sales agent that moves leads from first message to qualified opportunity — reading intent, pricing dynamically, and alerting a human the moment a lead turns hot.

At a glance: Ethereal built an AI sales assistant for a travel brand that chats with customers on WhatsApp and Telegram day and night, answers their questions, works out the right price, and pings the owner the moment a buyer is ready to purchase. It passed all 62 of its tests and never lets an overnight lead go cold.

02
Client
Confidential travel-commerce brand
Industry
Travel commerceSales automation · Messaging
Year
2025
Services
Agentic AISales AutomationDynamic PricingLead LifecycleAdmin Portal
62/62logic tests passing
24/7autonomous lead handling
4 stagesautomated lead lifecycle
01

The Problem

A travel-commerce brand was losing warm leads to manual WhatsApp/Telegram handling: no after-hours response, inconsistent pricing calculations, and no systematic follow-up.

After-hours

Leads arriving overnight on WhatsApp and Telegram went unanswered until someone was back at a desk.

Manual load

Every inquiry was triaged, priced, and followed up by hand across two messaging channels.

Inconsistency

Ad-hoc quoting and follow-up produced uneven pricing and leads that quietly went cold.

02

The Solution

We implemented an autonomous agent that extracts intent and handles multi-turn customer conversations. A dynamic pricing engine resolves seasonal multipliers and discount conflicts; RAG over the client's knowledge base answers product questions; and the full lead lifecycle is automated — new → warm → hot → contacted — with hot-lead alerts to the owner and automatic re-engagement of stale leads. An admin portal adds Excel upload, audit logs, and analytics.

System architecture
L1Layer

Tenant Config

Each client's packages, pricing rules, and knowledge base are declared, not coded.

L2Retrieval

RAG Grounding

FAISS vector search grounds every answer in the client's own knowledge base.

L3State

Session Memory

Redis-backed multi-turn sessions merge intent across a conversation.

L4Core

Agent Engine

One runtime handles intent extraction, dynamic pricing, tool use, and reply generation.

Lead lifecycle
Newcaptured
Warmengaged
Hotowner alerted
Contactedclosed loop
Latency budget
62/62

logic tests passing

Dynamic pricing

Seasonal multipliers and discount-conflict resolution resolve to one defensible quote.

Re-engagement

Stale leads are automatically re-approached before they lapse.

Guardrails
Injection defense

Prompt-injection attempts are caught before they reach the model or tools.

Tenant isolation

Cross-tenant access is blocked so no client can see another's data.

Rate limiting

Per-contact limits absorb floods and abusive traffic at the edge.

Webhook verification

Inbound WhatsApp and Telegram payloads are signature-verified before processing.

Audit logging

Every pricing change and lead action is written to an immutable audit trail.

24/7 autonomy

The agent handles, prices, and routes leads around the clock without a human in the loop.

03

The Outcome

Fully automated 24/7 lead qualification. Verified through 62/62 passing logic tests, with rate limiting, prompt-injection prevention, and cross-tenant isolation.

Built with

06 technologies
01FastAPIAPI and webhook layer
02PostgreSQLLeads, pricing, audit store
03RedisSession and rate-limit state
04FAISSVector retrieval for RAG
05ClaudeIntent extraction and replies
06WhatsApp / TelegramInbound message channels
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