Client’s challenge
A mid-size SaaS company delivers customer service platforms for businesses. Their company carries out 100K+ monthly support requests.However, as the customer base grew, scaling issues began to emerge: high agent load, response delays, and rising infrastructure costs. Many disruptions and setbacks made a great impact on user trust, increased maintenance costs, and SLA compliance.
The client wanted to maintain service quality while handling a growing volume of requests, without expanding their team or increasing costs. Manual routing, repetitive questions, and inconsistent response times were hindering growth and reducing user satisfaction. Primary flaws to resolve:
The client wanted to maintain service quality while handling a growing volume of requests, without expanding their team or increasing costs. Manual routing, repetitive questions, and inconsistent response times were hindering growth and reducing user satisfaction. Primary flaws to resolve:
- Persistent downtime and service volatility as a result of inconsistent architectureShopify migration during peak season
- Limited automation in customer service
- Lack of AI-driven engagement
- Cumbersome endorsement hindering feature delivery
Solutions
Our approach was based on a holistic transformation of the support ecosystem. That’s why we integrated cutting-edge AI with deeply engineered workflows and footing of regular improvement.
AI agents with RAG for smarter, scalable support
NEKLO implemented AI agents powered by RAG. It enables real-time processing of incoming customer requests. The model now leverages an internal knowledge base and historical support data to deliver precise, contextual responses. At the same time, it automatically escalates complex or sensitive cases to human operators. This balance between automation and human oversight helps achieve accuracy, speed, and trust at scale.
Workflow optimization and system integration
Beyond AI, to remove friction and latency, our engineering team rethought the entire workflow architecture. We fully automated request routing and escalation, enforced integrations with internal systems, and redesigned the message queue and response chain. Subsequently, customer interactions became faster, smarter, and fully trackable from intake to resolution.
Continuous reliability through CI and monitoring
One more result to achieve was long-term stability. So, our experts settled continuous integration pipelines and automated monitoring. Now, automated proof and testing within each release guarantee consistent quality and shorten delivery cycles. This way, even during high-traffic peaks, the client’s platform offers 99.9% uptime, faster updates, and dependable performance.
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Boost your service with AI that truly delivers.
Anastasia Vasilevich
Business development manager
Technologies
Back-end
AWS BedRock
Apache Kafka
FastAPI
PostgreSQL
Python
Temporal Workflow
Result
Our experienced team transformed the client’s unsteady customer support platform into a highly-efficient, AI-driven system. Now, it operates perfectly with intelligent automation refining interactions, decreasing operator burden, and stabilizing uptime under demand surges.
Consequently, the client acquired notable progress in efficiency and customer satisfaction.
Before/After
The implementation of the AI solution yielded not only technological but also tangible commercial benefits. As a result of NEKLO’s meticulous work, the client received a smart, resilient, and scalable support system that not only improved the user experience but also drove overall business growth.
- The number of active users increased by 30% thanks to fast, 24/7 support;
- Total revenue increased by 43% due to increased customer retention and reduced operating expenses;
- Reduced dependence on operators allowed end clients to cut down their own support costs by 25-30% and made the platform more competitive.
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