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AI X-Ray for Bidding Scoring Items: Technical Response Matrix One-Click Breakdown, 15k RMB/Month

Workflow: Spend 1 hour every morning taking orders in bidding communities, Xianyu, and other channels. After a client sends the bi

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Key Fields

FIELD STAMPS

IndustryContent / Creator Economy

RegionChina

ScaleSME

ChannelOnline

🔧 Workflow

Spend 1 hour every morning taking orders in bidding communities, Xianyu, and other channels. After a client sends the bidding PDF file, the Agent first uses PDF parsing tools to extract the scoring criteria tables from the file, breaking down the score, weight, and evidentiary material requirements for each item item-by-item. Next, it calls the LLM API to generate technical response content item-by-item, automatically matching the enterprise's existing performance and qualifications to generate a technical deviation table. Finally, it outputs a formatted technical response matrix Word document, which is delivered to the client after 1 hour of manual review.

🛠 Setup Requirements

Setup requires no complex coding. Use pdfplumber or PyMuPDF for PDF table extraction scripts, and configure the scoring item breakdown, response generation, and qualification matching processes into low-code platforms like Coze or Dify. Create the front-end client file upload entry using Lark forms (Feishu Forms) or WeChat mini-programs. With basic Python and low-code tools, you can run the process in 3-5 days and officially launch external services within 1 week at most.

🧰 Toolchain

🔧 Coze
🔧 DeepSeek API
🔧 PyMuPDF
🔧 Lark Bitable

💰 Revenue

① Technical bid breakdown and response matrix charged per order (Main revenue): Bidding enterprises pay per section, with regular technical bids at 500-800 RMB/order and complex government-enterprise major bids at 1200-1500 RMB/order. Urgent orders incur a 30% premium. 15-20 orders per month = approx. 15,000 RMB/month. The exact proportion of monthly revenue this accounts for has not been publicly stated (sourced from cases, independently unverified, observed around 2026); ② Response template library subscription: Monthly or annual subscriptions for repeat clients. Subscription prices are not public, and statistics on the number of renewing clients are unavailable; the revenue share from subscriptions is not mentioned; ③ Bidding tool account resale: Market tools priced from 399 RMB/year (100 parses, 50 generations) to 1,999 RMB/year (500 parses, 300 generations, 5 team accounts) (platform public pricing). No data is available on how many copies are resold, and the revenue share from resale is not listed separately; ④ Opportunity direction: Batch long-text auto-generation: Reportedly generates 200,000-word long texts in 10 minutes with 10x+ efficiency improvement (media estimate, independent recalculation pending). This can raise the order intake ceiling, though its exact revenue contribution remains unclear.

💸 Cost

Monthly expenses are around 300 RMB: DeepSeek API costs about 150 RMB, lightweight cloud hosting accounts for 50 RMB, and the remaining 100 RMB is for occasionally purchasing industry qualification template library memberships. Coze's free version is used at zero cost.

⏱ Time Investment

3-4 hours per day

🚀 Getting Started

Step 1: Go to the China Government Procurement Network to download 3-5 real bidding documents from the same industry, test the accuracy of PDF scoring table extraction and response generation, and organize 2-3 delivery samples. Step 2: Post service listings on Xianyu, bidding part-time communities, and enterprise service platforms. Take 10 low-priced test orders first to build up case studies, then gradually increase the unit price to over 500 RMB.

🔑 Keys to Success

✅ Familiarity with the Bidding Law and scoring standards across different industries, enabling quick identification of core requirements in scoring items
✅ Mastery of PDF table extraction technology to ensure complex format scoring tables are not misaligned or missing items
✅ Conducting manual polish on LLM-generated response content to avoid common-sense errors or content that violates industry norms
✅ Accumulating qualification and performance template libraries for various industries to enhance the matching degree and professionalism of response content
✅ Familiarity with disqualification rules, cross-checking response content before delivery to ensure it does not trigger disqualification clauses

⚠️ 风险

⚠️ Significant format variations in bidding documents across regions and industries require frequent adaptation of extraction scripts. Missing key scoring items may lead to client bidding failure, bearing refund or liability risks
⚠️ LLM-generated response content carries hallucination risks. Direct delivery without strict manual review may cause the response to fail bidding requirements, triggering disqualification
⚠️ Some bidding documents contain corporate trade secrets. Uploading files to unencrypted third-party AI platforms may leak client information and trigger legal disputes
⚠️ If generated response content plagiarizes other bids, it may trigger intellectual property disputes, requiring preliminary originality checks

📌 Real Cases

📌 Biotaniz AI Bidding Tool launched scoring item breakdown and response generation features, serving over 1.2 million bidding users cumulatively with over 80,000 bids processed per month
📌 Xique Bidding AI integrates full-process bid preparation, covering scoring item breakdown, response generation, and automatic formatting, with over 2,000 paid enterprise clients and service fees up to 3,000 RMB for a single complex bid
📌 Lianqi AI Bidding integrates large models to generate technical and commercial bid content, connecting with over 500 bidding enterprises and generating over 20,000 bids per month on average

Sources