How Engine Uses Salesforce Agentforce to Cut Handle Time 15% and Save $2M
Engine, a B2B travel platform handling 500,000+ annual traveler requests, deployed an Agentforce AI agent called Eva that autonomously manages over 30% of customer cases end-to-end. The implementation reduced average handle time by 15%, lifted CSAT from 3.7 to 4.3, and delivered $2M in estimated annual cost savings — all within a 12-day deployment timeline.
Impact
15%
Average handle time reduction
$2M
Annual cost savings
30%+
Cases handled end-to-end by AI
3.7 to 4.3
Customer satisfaction score improvement
12 days
Deployment timeline
Challenge
Engine's client services team was overwhelmed handling routine reservation changes for 500,000+ annual traveler requests, while the sales team's 5x growth in one year added pressure across HR, IT, operations, and finance.
Solution
Deployed Eva, a custom Agentforce AI agent built in 12 days, to autonomously handle end-to-end case management including reservation rescheduling, multi-room modifications, and itinerary updates using integrated customer profile and booking data.
Tools & Technologies
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Full Story
Engine operates a B2B travel platform used by businesses to manage hotel, flight, and car rental bookings for employees, processing more than 500,000 traveler requests per year. As the company's sales team expanded from 50 to 250 sellers in a single year, its client services team became stretched thin handling routine reservation changes — rescheduling flights, modifying multi-room bookings, updating itineraries — alongside the growing volume of complex, high-touch cases that truly required human attention.
The core challenge was capacity: routine tasks were consuming agent time at exactly the moment demand was accelerating. Engine needed a way to offload high-volume, transactional interactions without degrading the customer experience that distinguished it in a competitive market.
Engine partnered with Salesforce to deploy Eva, an AI agent built on the Agentforce platform. Eva was built using Agentforce Builder's low-code environment and integrated directly with Engine's internal booking systems, pulling from customer profile data and interaction history to handle multi-step reservation changes autonomously. The 12-day deployment timeline demonstrated what the platform called a hybrid development approach, combining visual tools for business logic with AI-assisted code generation.
The results were measurable across every dimension. Eva now resolves more than 30% of customer cases end-to-end without human intervention. Average handle time dropped 15%. Customer satisfaction scores climbed from 3.7 to 4.3 out of 5. Engine estimates $2 million in annual cost savings from the deployment, with human agents freed to focus on the complex, high-value interactions that drive retention.
