Gunjo · Business Intelligence for the AI Era
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Xiaoshouyi NeoAgent Intelligent Sales Agent Restructures CRM

1) SaaS subscription license fees based on user count and annual terms; 2) Implementation service fees for industry-spec

MODEL

Key Fields

FIELD STAMPS
IndustrySaaS / Enterprise Software
RegionChina
ScaleMid-size
ChannelOnline

📌 Background

In 2026, AI Agents are restructuring traditional CRM, transforming it from 'retroactive data recording' to a 'business growth engine'. Xiaoshouyi launched the industry's first AI-native CRM, NeoAgent, which breaks down the entire sales process into multi-agent collaborative tasks, covering scenarios such as lead prospecting, automated follow-up, customer profiling, and opportunity forecasting.

👤 Target Customers

Sales teams of medium-to-large manufacturing and commercial enterprises, primarily purchased by CIOs, CDOs, and Sales Directors.

💰 Revenue Streams

1) SaaS subscription license fees based on user count and annual terms; 2) Implementation service fees for industry-specific Agent skill assets; 3) Usage-based billing driven by token consumption and Agent orchestration frequency.

🧮 Cost Structure

Large model inference and GPU computing power costs, investment in the Agent platform R&D team, and enterprise-grade industry implementation and customer success personnel.

🛡️ Moat

Over a decade of enterprise-grade process know-how accumulated through CRM PaaS, a multi-agent orchestration engine coupled with an industry skill library, and collaborative channels with Tencent Cloud and WeChat Work ecosystems.

🔑 Keys to Success

  • Abstract top sales champions and industry-best sales processes into a composable atomic library of Agent Skills.
  • Drive customer adoption through performance metrics like coverage and efficiency multipliers rather than isolated feature points.
  • Deep integration with WeChat Work and the Tencent ecosystem to deeply penetrate domestic sales scenarios.

⚠️ Risks

  • AI hallucinations leading to incorrect customer judgments and external communication errors, triggering corporate losses and compliance risks.
  • Enterprise SaaS budgets remaining in a contraction period in 2026, with AI upgrade and replacement willingness lower than expected.

🏢 Cases

  • Xiaoshouyi NeoAgent serves Michelin, achieving 100% AI coverage of the sales process, over 6,800 cumulative hours of Agent operation, and a 48x workflow efficiency boost.

📊 SWOT Analysis

Strengths

  • Michelin case study proves 100% Agent coverage, over 6,800 cumulative running hours, and a 48x efficiency boost in single workflows.

Weaknesses

  • Heavy reliance on foundational large model capabilities, with uncertainties in cross-industry generalization effects.

Opportunities

  • Huge room for replacement of legacy traditional CRM users and AI upgrades, with corporate AI budgets leaning toward the sales side in 2026.

Threats

  • Rapid homogenization of AI Agent capabilities among competitors likeFxiaoke, Yonyou, and Salesforce, pushing competition into a capability-stacking red ocean.