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AI Custom Resume and High-Frequency Quality Job Automatic Application System: 5,000+ Executives Paid Verification

Workflow: Launch the crawler at midnight every day to collect newly released high-paying jobs from the previous day on platforms s

AGENT

Key Fields

FIELD STAMPS

IndustryEducation / Knowledge

RegionChina（中国大陆）

ScaleSME

ChannelOnline

🔧 Workflow

Launch the crawler at midnight every day to collect newly released high-paying jobs from the previous day on platforms such as BOSS Zhipin, Liepin, and Zhilian Zhaopin, extracting JD core requirements and hard screening criteria. Call the large model API to match the job seeker's original resume with job requirements, automatically optimizing resume keywords and phrasing to generate a customized resume. Use the Playwright headless browser to simulate human operations, batch log in to the user-authorized recruitment accounts to apply for matching positions, and finally automatically generate a daily application report to push feedback to the user. The whole process is only spot-checked manually at the final stage for matching results.

🛠 Setup Requirements

Requires basic Python syntax and browser automated debugging skills. Secondary development based on open-source GitHub projects to adapt to application rules of mainstream domestic recruitment platforms. Deployment cycle is about 10-15 days. Need to prepare 3-5 recruitment platform test accounts, residential dynamic proxy pools, and large model API calling permissions. In the early stage, repeated testing is required to evade platform anti-automation detection rules and reduce the probability of account bans.

🧰 Toolchain

🔧 OfferU Open-Source Application Framework
🔧 JobsIn Job Collection System
🔧 Auto-JobHunter Application Tool
🔧 Claude/DeepSeek Large Model API
🔧 Playwright Automation Framework
🔧 KuaiProxy Residential IP Pool

💰 Revenue

The open-source system is self-deployed with no subscription costs and can provide tiered services: basic batch application at 199 RMB/month/account, customized resume optimization + precise matching at 399 RMB/month/account, and VIP full-process job hunting companionship at 1999 RMB/term. Referring to public data of AI Resume Ji, currently over 5,000 mid-to-high-level executive users have verified willingness to pay, with a customer unit price of about 1,500 RMB. The maximum monthly revenue of a single account can reach 3,000 RMB, and an individual operating 3-5 accounts can achieve a monthly income of over 10,000 RMB.

💸 Cost

Local deployment of basic open-source tools incurs no subscription fees. Fixed monthly expenses are large model interface calls (daily operation monthly cost is about 20-30 RMB) and residential dynamic proxy rental fees (about 100 RMB/month/5 IPs). Total monthly costs can be controlled within 150 RMB.

⏱ Time Investment

In the early stage of system setup, rule debugging, and platform adaptation, 40 hours per week need to be invested. After stable operation, only 2 hours per day are needed to maintain the account environment, manually spot-check application matching results, and coordinate user demands.

🚀 Getting Started

Step one: Pull open-source projects like OfferU and JobsIn from GitHub, set up a local Python runtime environment to complete basic function deployment. Step two: Apply for recruitment platform test accounts, configure dynamic proxy pools and anti-automation evasion rules, and test the full process of job collection, resume matching, and batch application. Step three: Provide free tests in job-seeking communities, LinkedIn, and other channels to accumulate successful cases, and subsequently launch tiered paid services, initially targeting mid-to-high-level internet executives looking to switch jobs.

🔑 Keys to Success

✅ Accurately extract JD core keywords based on large model prompt engineering, dynamically match personal resumes to generate customized resumes, increasing the probability of passing ATS system screening by over 60%
✅ Configure a residential dynamic proxy pool, simulate human browsing, clicking, and lingering behaviors to evade recruitment platform anti-automation detection, reducing the probability of account bans to below 5%
✅ Establish job quality filtering rules to prioritize screening high-quality positions published within 7 days, with salaries 30% higher than the industry average, and enterprise financing above Series B, improving application conversion rates
✅ Manually set the final application review checkpoint. After AI completes preliminary screening and matching, humans confirm the application list to avoid blind applications damaging user reputation

⚠️ 风险

⚠️ Mainstream recruitment platform anti-automation strategies are upgraded, and batch application accounts may be banned in batches, leading to service interruptions and user complaints
⚠️ If job matching logic is over-generalized, it will lead to a large number of invalid applications, reduce the user interview invitation rate, and trigger refunds and reputation decline
⚠️ There is a risk of leakage in the storage of sensitive job seeker resume data. If a data security accident occurs, it will face user claims and compliance penalties

📌 Real Cases

📌 AI Resume Ji: A leading domestic AI job-seeking tool publicly disclosing that 5,000+ managers and mid-to-high-level executives have paid to use it. Basic resume optimization service is priced at 99 RMB/time, full-process job hunting companionship is priced at 1,999 RMB/term, and single-month revenue exceeds 2 million RMB
📌 GitHub open-source project OfferU: Has obtained 1.2k stars, used by multiple job service teams for batch application system setup, with a single team operating a monthly revenue of up to 80,000 RMB based on this system
📌 Third-party job service provider 'Offer Harvester': Based on open-source application tools + AI resume customization services, providing 99-399 RMB/month application services for internet job seekers, serving over 2,000 users cumulatively in 2025 with a repurchase rate of 35%

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