Hotcan Group › Services › AI Software Development
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AI Software Development

Centered on large language models, delivering end-to-end AI application development services that bring artificial intelligence to real-world business scenarios and create measurable value.

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Service Overview

Hotcan Group's AI software development practice focuses on transforming large language models (LLMs), machine learning, and intelligent automation technologies into practical enterprise applications that address real-world efficiency bottlenecks and decision-making challenges.

We don't do "AI concept packaging" — instead, we start from the client's actual business processes, designing and delivering AI systems that truly operate and continuously improve. Whether it's enterprise knowledge management, intelligent customer service, process automation, or industry-specific model fine-tuning and AI product development, we bring mature delivery capabilities and engineering infrastructure.

Core Services

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    LLM Application Development Building enterprise knowledge base Q&A systems, AI writing assistants, intelligent contract review, multilingual content generation, and other scenario-based applications on top of GPT, Claude, Gemini, ERNIE Bot, Qwen, and other leading LLMs. Supporting RAG (Retrieval-Augmented Generation) architecture design to ensure accurate and traceable outputs.
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    AI Agent Systems Designing and developing AI Agent systems capable of autonomous planning, tool calling, and multi-step task execution. Covering complex automation scenarios such as sales lead follow-up, financial report generation, supply chain anomaly alerting and resolution, and scheduled market intelligence collection and analysis.
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    Custom Enterprise Software Development Providing full-stack enterprise software development services, including frontend (React/Vue), backend (Python/Node.js/Go), database design, and API integration. Primarily serving SMEs with management systems (lightweight ERP), customer relationship management (CRM), and business process digitization.
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    Machine Learning & Data Intelligence Delivering predictive models, anomaly detection, user behavior analysis, personalized recommendation, and other ML solutions for data-rich enterprises. Covering the full lifecycle from feature engineering, model training, evaluation, deployment to continuous optimization.
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    RPA Intelligent Automation Combining RPA (Robotic Process Automation) with AI to automate highly repetitive, rule-based business processes such as invoice entry, report consolidation, cross-system data synchronization, and email classification and routing. Effectively freeing up human resources while reducing operational errors.

Technology Stack & Ecosystem

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LLM FrameworksLangChain · LlamaIndex
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LLMsGPT · Claude · Gemini
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China LLMsERNIE · Qwen · DeepSeek
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ML PlatformsAzure ML · Hugging Face
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FrontendReact · Vue · Next.js
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BackendPython · FastAPI · Go
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Vector DBsPinecone · Weaviate · PGVector
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CloudAzure · AWS · Alibaba Cloud

Project Delivery Process

01
Requirements Discovery & Scenario Definition Deep engagement with the client team to identify the highest-value AI use cases, assess data availability, technical feasibility, and ROI expectations, and define project scope and success criteria.
02
Rapid Prototyping (POC) Delivering a demonstrable functional prototype within 1-2 weeks, validating core assumptions with real data to reduce full-scale development risk and confirm the technical approach.
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Iterative Development & Engineering Operating on 1-week iteration cycles with continuous delivery of usable features, concurrent system architecture optimization, security hardening, and performance tuning to ensure production readiness.
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Deployment & Ongoing Support Assisting with cloud deployment, on-premises private deployment, or hybrid architecture implementation, providing post-launch monitoring, maintenance, and continuous model optimization to ensure stable operations and evolving improvements.

Use Cases

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    Enterprise Knowledge Base Q&A Building AI-powered Q&A systems based on internal documents, policy manuals, and historical projects, significantly improving employee information retrieval efficiency and reducing repetitive knowledge transfer costs.
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    Intelligent Contract Review Developing AI contract review tools that automatically identify risk clauses, compliance issues, and key dates, dramatically reducing contract review cycles.
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    Supply Chain Anomaly Detection Building intelligent supply chain monitoring platforms that combine ML predictive models to identify delivery risks and quality anomalies in real time, enabling early warning and rapid response.