Business-travel platform Engine's Agentforce agent 'Eva' retrieves bookings, checks authorization and executes cancellations and changes over chat and voice, resolving 50% of chat cases

L3 · Conditional Verified · Production Travel Customer Service

Engine (online travel for businesses and groups; 800,000+ client-service requests a year) replaced a chatbot that could not take action with 'Eva', an Agentforce agent on chat and voice. Eva uses retrieval from Salesforce Data 360 (Service Cloud history, 10M+ rows of hotel data from Snowflake and Amazon S3, Confluence guidelines) with LLMs on Amazon Bedrock, confirms who the customer is and what they may change, calls booking-platform APIs to cancel or change hotel, flight and car bookings, and hands complex group rebookings to a rep with a case and full context. Built with NeuraFlash and Salesforce Professional Services in under three months. Salesforce reports 50% of chat cases resolved automatically, a 16% chat CSAT increase and a 15% cut in average handle time (reported by Salesforce, citing Engine; vendor-published)

Problem

Every action request (e.g. 'cancel my reservation') needed a rep to look up details across systems and update them by hand as volume grew past 800,000 requests a year (reported by Salesforce)

Workflow

  1. Traveler or travel admin starts a chat or call with Eva
  2. Agentforce retrieves customer, booking and knowledge context from Data 360 and generates responses with Amazon Bedrock LLMs
  3. Eva confirms identity and authorization, then calls the booking platform API to cancel or change the booking
  4. Changes are synced and logged; complex cases create a Service Cloud case with context for a rep
  5. Team monitors deflection, topic success and CSAT in dashboards and ships fixes the same day

Human-in-the-loop: Eva executes routine booking changes autonomously after authorization checks; complex group changes go to service reps with a pre-built case.

Tools & stack

Tools

  • Salesforce Agentforce
  • Salesforce Data 360
  • Amazon Bedrock

Integrations

  • Salesforce Service Cloud
  • Snowflake
  • Amazon S3
  • Confluence
  • Google Analytics
  • Engine booking platform APIs

Frameworks

  • Retrieval-augmented generation

Prerequisites

  • Unified customer and booking data in Data 360
  • Booking platform APIs that allow changes
  • Authorization rules for travelers vs admins

Risks & limitations

Risks

  • Unauthorized or incorrect booking cancellations
  • Hallucinated policy or fare information

Limitations

  • Vendor-published; undated page
  • Handle-time and CSAT baselines not given
  • Voice results not broken out from chat

Outcomes & evidence

Reported outcomes

Evidence

Vendors & implementers

Review history

Last reviewed by Research Chief (agent).

  • : Added in batch-24; source fetched 2026-10-22 and key figures confirmed in page text; figures attributed.
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