IPO Valuation Support Analysis of Jiuke Information and Research on the AI Agent Track

• Valuation Support (Qualitative):
  Jiuke Information’s central enterprise intelligent automation track has strong “scene stickiness + policy resonance” characteristics. Its disclosed penetration rate (over 30%) and high repurchase rate (over 80%) in the central enterprise market positively support valuation, but due to the lack of company financial and revenue measurement standards, it cannot provide a rigorous quantitative range.
• Core Premises:
  To form a rigorous IPO valuation judgment, the following core data is required (priority: A/B/C):
  • Class A (Mandatory):
    Audited revenue, gross profit, EBITDA, net profit, operating cash flow over the past 3 years; customer unit price distribution (new signings/renewals), repurchase measurement standards, order structure and industry concentration; Customer Acquisition Cost (CAC)/Lifetime Value (LTV), per capita efficiency/efficiency ratio.
  • Class B (High Value):
    Product structure proportion (bit-Agent vs traditional RPA + Low-Code/Process Mining); annual breakdown of new ARR, churn rate, NRR, GRR; revenue proportion and delivery cycle of cloud-native vs local deployment, gross margin difference.
  • Class C (Bonus):
    R&D investment details, employee structure and incentives, outstanding orders/undelivered contracts, channel and ecosystem revenue sharing structure, Xinchuang (Indigenous Innovation)/security certification and delivery SLA compliance status.
• Track Judgment (Based on Current Round Data):
  AI Agent is in the key window of transition from “validation” to “scaling”. The Chinese enterprise-level AI Agent application market will reach approximately 23.2 billion yuan in 2025, with a CAGR of about 120% from 2023 to 2027; the overall budget for central enterprise digital transformation will approach 700 billion yuan in 2025, with more than 55% of central enterprises in the stages of more innovative practices/comprehensive transformation/leadership; Agent application penetration rate will increase from less than 5% in 2024 to over 15%; the State Council’s “Artificial Intelligence +” action clearly states that the penetration rate of applications such as intelligent agents will exceed 70% by 2027. All these constitute structural opportunities for Jiuke Information’s track.

• Customer Structure and Stickiness:
  Multiple reports indicate that Jiuke Information’s penetration rate in the central enterprise market exceeds 30%, customer repurchase rate exceeds 80%, and average customer unit price exceeds 1 million yuan. This shows its strong entry barriers and renewal inertia in central enterprise scenarios.
• Product and Path:
  bit-Agent is positioned as a “GUI Agent”, integrating multi-modal large models with RPA/Low-Code/Process Mining, targeting central enterprise “process + decision” automation. Disclosed cases include scenario implementation such as SAIC Group’s security inspection.
• Capital and Background:
  Financing background includes TJFAS Fund, CM Venture Capital, GSR Ventures, Shenzhen Venture Capital, etc., with nearly 100 million yuan in the B2 round, and IPO preparation has been initiated. CM Venture Capital’s incubation gene has natural advantages in central enterprise bidding and compliance adaptation.
• Policy Resonance:
  The State Council’s “Artificial Intelligence +” special action requires central enterprises to take AI as a key focus in the 15th Five-Year Plan, promote high-value scenario implementation, and clearly states that “the penetration rate of applications such as intelligent agents will exceed 70% by 2027”. This provides sustained demand for Agent platforms targeting central enterprises.

• “30% Penetration Rate”:
  More likely to be the “coverage proportion in target central enterprise segmented customer groups” rather than “full market penetration”. Its valuation significance depends on:
  • The scale and payment capacity of this segmented market (structural overlap with the 700 billion yuan central enterprise digital transformation budget).
  • Whether the customer contribution distribution is healthy (avoiding excessive proportion of a few customers and high contract concentration leading to renewal fluctuations).
• “80% Repurchase Rate”:
  Needs further拆解:
  • Whether calculated by contract amount/customer count.
  • Whether includes cross-product line upselling (from RPA to bit-Agent).
  • Whether excludes the impact of non-renewal but downgrading or price adjustment.
• “Customer Unit Price Exceeds 1 Million Yuan”:
  The statistical standard also needs to be clarified whether it is “new signing standard” or “current period recognized revenue standard”. These differences will directly affect the judgment of revenue quality and profit release rhythm.

• Market Scale:
  • Global:
    Approximately 5.1 billion US dollars in 2024, expected to reach approximately 47.1 billion US dollars in 2030, CAGR ≈ 44.8%.
  • China:
    The enterprise-level AI Agent application market will reach approximately 23.2 billion yuan in 2025, with a CAGR of ≈120% from 2023 to 2027.
• Main Domestic Competitors:
  • RPA+AI/Agent Transformation:
    Shizhen AI (ISSUT intelligent screen semantic understanding + “natural language generation process” capability), Laiye Technology (“Laiye UiBot” has strong government affairs implementation), HyperCyclone (AIGA, large model + RPA), Kingdee Wise, CloudExpander Technology, Rongzhi Information, Daguan Data, Shadow Robot RPA, iS-RPA, Newlink Technology, etc.
  • Big Factory and Platform Type:
    Tencent Yuanqi, Coze (ByteDance) rely on ecosystem and developer communities to cover broader scenarios.
  • Open Source and Framework:
    Dify, LangGraph promote developer ecosystem innovation.
• Differentiation Elements of Jiuke Information:
  • CM Venture Capital’s incubation gene, natural adaptation to central enterprise business logic/management system/compliance requirements.
  • Product matrix of “AI + RPA + Low-Code + Process Mining” and bit-Agent GUI Agent capability.
  • Scenario precipitation and benchmark cases in central enterprise-intensive fields such as energy, manufacturing, finance, government, and military industry.

• Support Elements:
  • High track prosperity (AI Agent, central enterprise digitalization, Xinchuang substitution) and policy resonance.
  • Revenue quality and customer stickiness brought by high threshold scenario penetration rate, high repurchase rate, and high customer unit price of central enterprises.
  • Bargaining and trust advantages in bidding and compliance adaptation brought by state-owned capital backgrounds such as CM Venture Capital.
  • First-mover advantage and benchmark cases (such as SAIC inspection) of bit-Agent in the “GUI Agent” direction.
• Valuation Uncertainty Sources (Need to Resolve in In-Depth Research):
  • Unpublished Financial and Operational Data:
    Revenue growth rate, gross margin, EBITDA, operating cash flow, customer concentration and churn rate, R&D intensity and delivery cycle.
  • Market Competition Intensity:
    Rapid iteration and ecosystem integration of Laiye Technology, Shizhen AI, HyperCyclone, Kingdee Wise, etc. in the RPA+AI/Agent field.
  • Technology Iteration and Large Model Cost:
    Model/computing power cost structure, bargaining and switching capability with external model suppliers.
  • Policy and Demand Rhythm:
    Central enterprise project bidding cycle, budget fulfillment rhythm, Xinchuang substitution progress.
• Conclusion (Qualitative):
  Without obtaining the company’s financial and operational measurement standards, it is impossible to quantitatively give a specific range of “can/cannot support valuation”. However, based on the disclosed “central enterprise penetration rate + repurchase rate + customer unit price + product form + capital background”, it has the characteristics of a high-quality commercial “sample” on the correct track. If “healthy revenue, visible profit, reasonable customer structure, and evolvable technology” are verified in in-depth research, it will be more likely to match a reasonable valuation.

• Opportunities:
  • Dual drive of central enterprise digitalization and Xinchuang substitution.
  • Adaptation and substitution upgrade space of GUI Agent for legacy systems/multi-modal interfaces.
  • Medium and long-term demand certainty brought by the policy clearly stating that “the penetration rate of applications such as intelligent agents will exceed 70% by 2027”.
• Risk Tips:
  • Bidding and payment cycle, customer concentration and renewal fluctuations.
  • Large model cost, technology iteration and cross-system compatibility.
  • Intensified industry competition and IPO market fluctuations.

• Data Acquisition (Under Signing Confidentiality/NDA):
  • Audited financial reports for the past 3 years; product structure and order structure; customer and revenue quality indicators (NRR/GRR, CAC/LTV, per capita efficiency); outstanding orders and undelivered contracts; R&D investment and Xinchuang/security certification; SLA compliance status.
• Valuation Anchor Construction:
  • Compare PS/PE/PB and growth rate/profit margin of comparable companies (listed RPA+AI/Agent or software vendors), and conduct scenario deduction combined with Jiuke’s growth rate and retention rate.
• Technology and Product Competitiveness Evaluation:
  • Comparison of bit-Agent with other GUI Agent solutions in terms of visual analysis accuracy, cross-system stability, operation and maintenance cost, and model cost.
• Market and Competition Analysis:
  • Penetration and expansion space calculation of benchmark customers (energy/finance/manufacturing/government/military industry); product and quotation strategies and ecosystem integration paths of competitors (Laiye, Shizhen, HyperCyclone, Kingdee Wise, etc.).
• Financial and Operational Health:
  • Revenue seasonality, accounts receivable and payment cycle, customer concentration, retention/churn rate, per capita efficiency and R&D intensity, outstanding orders and undelivered contracts.

• Industry and Market Scale Chart:
  • China’s enterprise-level AI Agent application market scale (2023-2027E) and central enterprise digitalization budget structure split (process management/design R&D/risk control, etc.).
  • Central enterprise AI budget segmented distribution (20-50 million/50-100 million yuan, etc.) and AI penetration rate growth curve.
• Competitive Pattern Map:
  • Capability comparison of major domestic RPA+AI/Agent vendors (visual analysis, multi-modal, low-code, workflow orchestration, ecosystem integration, central enterprise implementation experience).
• Valuation Benchmarking and Scenario Analysis:
  • “Valuation Radar” based on comparable companies’ PS/PE/PB and growth rate/profit margin, giving Jiuke’s valuation path under optimistic/neutral/conservative scenarios.
• Customer and Revenue Quality Analysis:
  • Jiuke’s customer contribution distribution, new signing/renewal structure, industry and regional expansion map, customer unit price trend, contribution of repurchase to revenue growth.
• Technology and Product Power Visualization:
  • Comparison of GUI Agent vs traditional RPA in success rate/delivery cycle/operation and maintenance cost in complex scenarios; comparison of bit-Agent with other Agent solutions in visual analysis accuracy and adaptation coverage.

[1] 2025 Global AI Agent Industry Insight Report (Market Scale and Trends)
[2] 2025 China AI Intelligent Agent Industry Market Prospect Forecast Research Report (Sina Finance)
[3] 2025 Central Enterprise Digital Transformation New Practice and New Paradigm Report (Central Enterprise Budget and AI Application Penetration Rate)
[4] Oracle Team Re-Entrepreneurship: Jiuke Information Secures 100 Million Yuan B2 Round Financing and Initiates IPO Preparation (36kr)
[5] Jiuke Information Completes 100 Million Yuan B2 Round Financing Led by TJFAS (Zhitong Finance)