How Huolala Built a Low‑Code LLM Platform to Accelerate AI Agent Deployment

Background

With the rise of Large Language Models (LLM), efficiently applying LLMs has become critical, and building AI agents around LLMs is a new trend. Huolala has already applied LLMs in driver invitation, AI客服, and creative generation, but faced integration difficulty, scattered data sources, and high landing costs.

LLM Application Platform

Huolala built an LLM application platform with a visual interface that allows users to drag and drop components to create and deploy applications in about two minutes, lowering costs and shortening integration cycles.

Platform Architecture

The platform consists of three layers:

Infrastructure Layer : internal databases, monitoring, gateways, etc.

Platform Layer : low‑code configuration, orchestration, monitoring, and alerting for AI applications.

Business Layer : exposes open APIs for business scenarios such as smart marketing, code assistance, data insight, and intelligent Q&A.

Platform Functions

The platform provides visual, zero‑code building of AI applications by dragging components to create flows. Key functions include:

Component & Model Management : LLM integration, component tools, and AI application management center.

AI Application Deployment : drag‑and‑drop flow creation, publishing as external APIs.

Open API : simplifies business integration.

Monitoring & Alerts : real‑time monitoring, exception alerts, and traceable logs.

Application Examples

Chain

Supports LLM + Prompt chains with optional hidden prompt/copy libraries for confidential business use. Users can define custom prompts and generate marketing copy within minutes.

Agent

Enables rapid construction of agents (LLM + Planning + Tools + Memory). For example, an AI Q&A robot uses document splitting, embedding, and vector storage to retrieve answers automatically.

Business Landing

The platform has been applied in four business areas across seven scenarios, including:

Smart Marketing : AIGC‑generated and rewritten copy improves click‑through rates; a flow can produce multiple drafts from a keyword in seconds.

AI Invitation : Detects driver emotions and intents to enhance lead management.

Smart Advertising : Generates ad copy quickly, boosting efficiency and click rates.

Assisted Modeling : Generates style tags and keyword summaries to enrich the copy library for future automation.

Summary

Huolala’s LLM application platform closes the LLM toolchain loop, enabling rapid AI application delivery. It improves model‑driven efficiency by 98.75%, reduces average integration time from 24 hours to 18 minutes, and has been deployed in seven business scenarios.