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AI Customer Service

14 articles · Page 1 of 1
Ray's Galactic Tech
Ray's Galactic Tech
Jul 21, 2026 · Backend Development

AI Customer Service at Millions Scale: Chat API to Function Calling (SpringBoot)

The article details how a Spring Boot‑based intelligent customer service evolves from a simple chat endpoint to a robust Function Calling architecture, addressing challenges such as real‑time data access, permission checks, idempotency, error handling, token management, and scaling to tens of millions of daily conversations.

AI Customer ServiceFunction CallingSpring AI
0 likes · 27 min read
AI Customer Service at Millions Scale: Chat API to Function Calling (SpringBoot)
LuTiao Programming
LuTiao Programming
Jun 17, 2026 · Backend Development

Why Salesforce’s $3.6B AI Customer Service Bet Highlights the Real Opportunity for Java Back‑End Developers

The article explains how Salesforce’s $3.6 billion acquisition of Fin signals a shift from simple chatbot answers to AI agents that execute end‑to‑end business actions, and why Java/Spring Boot developers must expose secure, auditable services rather than merely wrapping large‑model APIs.

AI Agent ArchitectureAI Customer ServiceIdempotency
0 likes · 21 min read
Why Salesforce’s $3.6B AI Customer Service Bet Highlights the Real Opportunity for Java Back‑End Developers
AI Illustrated Series
AI Illustrated Series
Jun 8, 2026 · Artificial Intelligence

AI Agent Learning Roadmap for Career Switch – Bookmark This Guide

This article provides a comprehensive, up‑to‑date map of all AI Agent learning resources—including basics, enterprise‑grade customer‑service projects, interview question collections, daily practice, industry trends, multi‑language tutorials, and a supporting website—so newcomers and seasoned readers can quickly locate the content they need.

AI AgentAI Customer ServiceFunction Calling
0 likes · 8 min read
AI Agent Learning Roadmap for Career Switch – Bookmark This Guide
SpringMeng
SpringMeng
Mar 26, 2026 · Artificial Intelligence

Building a Dify‑Powered Multi‑Agent RAG AI Service with Chinese Large Models

After the New Year the author landed several AI contracts, delivering a six‑week knowledge‑base Q&A system and a two‑month AI customer‑service platform built with Dify, multi‑Agent workflows, RAG, and domestic large language models, cutting staff from fifteen to two and boosting development efficiency twofold.

AI Customer ServiceChinese LLMDify
0 likes · 7 min read
Building a Dify‑Powered Multi‑Agent RAG AI Service with Chinese Large Models
Fighter's World
Fighter's World
Feb 28, 2026 · Industry Insights

How Giga Builds a Differentiated Edge in the Crowded AI Customer Service Market

Giga, an AI agent startup founded by IIT Kharagpur alumni, pivoted to AI customer service, leveraging a Python-as-Primitive architecture and the Atlas multi‑agent system to automate FDE work, achieve 98% resolution rates, and position itself against competitors through speed, complex‑scenario handling, and a reusable Skills library.

AI Customer ServiceAI agentsATLAS
0 likes · 21 min read
How Giga Builds a Differentiated Edge in the Crowded AI Customer Service Market
Fighter's World
Fighter's World
Jan 30, 2026 · Industry Insights

How Decagon’s Engineering Edge Beats Sierra’s $10B Valuation in AI Customer Service

The article analyzes why AI‑customer‑service startup Decagon, with $1.5B valuation and rapid ARR growth, outperforms the $10B‑valued Sierra by leveraging a self‑evolving control loop, multi‑model orchestration, AOP framework, per‑resolution pricing, and a fast‑feedback execution culture.

AI Customer ServiceAOP FrameworkMulti-Model Orchestration
0 likes · 28 min read
How Decagon’s Engineering Edge Beats Sierra’s $10B Valuation in AI Customer Service
Youzan Coder
Youzan Coder
Jan 13, 2026 · Artificial Intelligence

From Hackathon to Scalable AI Customer Service: Lessons and Best Practices

This article chronicles the end‑to‑end development of an AI‑driven customer service system, detailing the shift from a rapid‑prototype Dify platform to a hybrid engineering architecture, model selection strategies, workflow design, knowledge engineering, evaluation methods, and future directions for continuous improvement.

AI Customer ServiceEvaluation FrameworkPrompt Engineering
0 likes · 21 min read
From Hackathon to Scalable AI Customer Service: Lessons and Best Practices
Ubiquitous Tech
Ubiquitous Tech
Aug 7, 2025 · Artificial Intelligence

How to Use RAG Tool Calls in FastGPT for Real-Time Train Ticket Queries

This article walks through integrating RAG‑based tool calling into a FastGPT workflow to enable AI‑driven customer service that can fetch real‑time train ticket information by invoking external APIs, configuring HTTP nodes, and handling parameters step by step.

AI Customer ServiceFastGPTHTTP API
0 likes · 18 min read
How to Use RAG Tool Calls in FastGPT for Real-Time Train Ticket Queries
Ubiquitous Tech
Ubiquitous Tech
Jul 14, 2025 · Artificial Intelligence

How to Craft Human‑like RAG Prompts for AI Customer Service

This article explains why prompt engineering is essential for turning large‑language‑model‑driven chatbots into empathetic assistants, outlines a 5W1H framework for designing structured prompts, provides concrete travel‑assistant examples, and shares practical techniques and tools such as Prompt Optimizer to improve RAG reliability.

AI Customer ServiceAI ToolsChatbot
0 likes · 25 min read
How to Craft Human‑like RAG Prompts for AI Customer Service
Ubiquitous Tech
Ubiquitous Tech
May 25, 2025 · Artificial Intelligence

Understanding RAG: The Core Capability Behind AI Customer Service

This article explains why Retrieval‑Augmented Generation (RAG) is essential for AI‑driven customer service, outlines the limitations of large language models, details the three‑stage RAG workflow (indexing, retrieval, generation), and shows how to implement it with FastGPT, vector databases, and LangChain.

AI Customer ServiceFastGPTKnowledge Base
0 likes · 16 min read
Understanding RAG: The Core Capability Behind AI Customer Service
DeWu Technology
DeWu Technology
Nov 4, 2022 · Industry Insights

Inside DeWu’s First Tech Salon: E‑commerce Backend Architecture, AI Customer Service, and Anti‑Spoofing Insights

The article recaps DeWu Technology's inaugural Hangzhou tech salon, highlighting speaker insights on e‑commerce backend service stability, intelligent customer‑service evolution, anti‑spoofing facial‑recognition technology, and a six‑module fulfillment platform architecture, while showcasing the team's rapid growth and future goals.

AI Customer ServiceBackend Architectureanti-spoofing
0 likes · 7 min read
Inside DeWu’s First Tech Salon: E‑commerce Backend Architecture, AI Customer Service, and Anti‑Spoofing Insights
Qunar Tech Salon
Qunar Tech Salon
Jun 25, 2019 · Databases

Recap of QInfrarch 2019: Technical Talks on Private Cloud, Real‑time Hotel Computing, Intelligent Ticket Customer Service, and OceanBase

The 2019 QInfrarch technical carnival in Suzhou gathered nearly 160 engineers from Qunar and partner companies to share in‑depth sessions on private cloud databases, real‑time hotel computation, AI‑driven ticket customer service, and OceanBase architecture, concluding with networking, tea breaks, and a lucky‑draw for attendees.

AI Customer ServiceDatabaseOceanBase
0 likes · 5 min read
Recap of QInfrarch 2019: Technical Talks on Private Cloud, Real‑time Hotel Computing, Intelligent Ticket Customer Service, and OceanBase
Tencent Cloud Developer
Tencent Cloud Developer
Sep 20, 2018 · Industry Insights

How Big Data Drives Intelligent Outbound Calls and AI Customer Service

This article explains how a data‑driven platform combines big‑data preprocessing, behavior‑prediction models, and AI‑powered voice and text services to improve pre‑sale lead scoring, targeted SMS campaigns, and post‑sale customer support, using Tencent Cloud's TI One platform as a case study.

AI Customer ServiceBig DataIndustry Insights
0 likes · 17 min read
How Big Data Drives Intelligent Outbound Calls and AI Customer Service