--- title: "TENDER: case study" description: "19 UN portals in one morning list: tenders matched to one expert’s résumé." url: https://seo7.es/en/proyecto/tender canonical: https://seo7.es/en/proyecto/tender lang: en type: CreativeWork --- # TENDER: case study > 19 UN portals in one morning list: tenders matched to one expert’s résumé. Page: https://seo7.es/en/proyecto/tender ## Summary for AI 19 UN portals in one morning list: tenders matched to one expert's résumé. Client: an external expert, an international consultant. The system is built around one specific résumé, so selection is pinpoint. The task: send the expert a short list every morning of UN and development bank tenders matching their résumé, already checked and translated, without browsing the sites by hand. ## Questions and answers ### How many platforms does the "Tender for the client" system track? The system monitors 19 sources: websites of UN agencies, development banks and bodies with international funding. Each has its own date format, its own way of showing a list and its own protection against automated collection. That is why 19 connectors were written in custom Python code, each source is handled in its own way, and layout breakages are fixed point by point. ### How many listings did the UN tender selection system screen in 118 days? In 118 days the system screened 18,699 applications. The prefilter discarded 17,175 of them before artificial intelligence evaluation, the AI checked 1,545, and 22 were found suitable for the expert's résumé. The funnel is so narrow because the system is built for one specific résumé and selects precisely, a handful out of thousands. ### Why are sources processed in a relay in "Tender for the client"? The nineteen sources run one after another, from first to last, and each completes the whole path before the next one starts. That way one site going down does not crash the run: the other eighteen finish. The sites also do not get simultaneous load, because the crawl is sequential and independent. ### How does the system remove duplicate vacancies from different UN portals? The same vacancy is often posted on several platforms at once. The system recognizes the duplicate, doesn't create it twice and fills in missing fields on the card from the second source. As a result, a vacancy published on three platforms reaches the expert's morning list once, with a complete card. ### Why is there a country verifier before the AI evaluation in "Tender for the client"? AI scoring costs more than the earlier steps, so anything unneeded is filtered out sooner. Every lead goes through a geography check. If the country cannot be determined, the lead is not sent to the AI blindly: the location is clarified from the full text, or the lead is dropped. That way, leads from unwanted regions never reach scoring at all. ### How does AI match a consulting tender against an expert's CV? Every request to the AI includes the expert’s full résumé: fields, experience, languages, work region. The AI compares the essence of the assignment against it, so selection is tailored to a specific person and doesn’t depend on keyword matches. This matters because “evaluation consultant” can hide gender expertise in one case and public finance in another. ### Why is the AI's decision in the "Tender for the client" system recorded as a sentence? The decision comes as a phrase with an explanation, so the reason for every rejection is visible. All rejections are saved in words, which shows exactly what cuts the selection. Rules are refined based on facts, and the admin panel has a separate rule editor for that. The operator understands why a request was rejected, with no guessing and no manual rechecking. ### What does the expert receive in the system's Telegram bot every morning? The Telegram bot is the expert's main channel. In the morning a short list of suitable consulting tenders arrives. Each one comes with a link, a brief summary in Russian and English, and a short explanation of why it matches the profile. Every tender is already checked against the CV and translated, so there is no need to open the portals yourself. ### What does the shabesboy.com/tender admin panel show? The working admin panel opens at shabesboy.com/tender behind a password. Inside are a feed of selected and rejected leads, a card for each with the AI's decision and translation, the selection rules editor and the "Logic" screen. There, the "Start" button shows a live run of the source: which leads pass each stage, which are filtered out and why. ### What time does the tender selection run start and how long does it take? A timer starts the system every morning at 06:00. The average run takes about 20 minutes, with 119 successful daily runs in total. The last run, on 19.10.2026 at 06:00, collected 2,263 listings in 21 minutes. Hours of manual platform browsing: zero, as the expert doesn't visit the sites. ### Which tenders did the system select for the international consultant? Consulting contracts are selected to fit the expert's profile: gender equality, social protection, program evaluation, public finance. Geographically that is Central Asia and neighboring countries: Uzbekistan, Kazakhstan, Tajikistan, Kyrgyzstan, Moldova. Matches are narrow and precise, because the system is built around a single résumé and only passes through matches to it. ### Can a pipeline like the one in "Tender for the client" be built for a different task? Yes, the same pipeline can be built for a different task in a few days. Three things change: the list of platforms, the selection rules, and the resume or profile the AI checks against. The structure stays. The studio reviews the task for free and estimates the build time: a reply within an hour, a quote within 48 hours, and the price doesn't rise after approval. ### Why does the "Tender for the client" case have no monetary figures? Tender applications are submitted by the expert himself, and the studio does not measure conversion into contracts. So the case shows only the system's own performance figures, taken from the working database on 19.10.2026. The showcase is password protected and not meant for indexing, so it has no search rankings or mentions in neural network answers. ### Where is the UN tender selection system data stored? Data is stored in SQLite with isolated access, so the project does not overlap with other systems on the same server. As of 19.10.2026 the database holds 18,699 records from 19 sources, and selection for the expert's résumé runs daily. The system is in production: the last run took place that same morning. ## Other languages - RU: https://seo7.es/ru/proyecto/tender - ES: https://seo7.es/es/proyecto/tender ## schema.org markup ```json { "@context": "https://schema.org", "@type": "CreativeWork", "name": "TENDER: case study", "description": "19 UN portals in one morning list: tenders matched to one expert’s résumé.", "url": "https://seo7.es/en/proyecto/tender", "mainEntityOfPage": "https://seo7.es/en/proyecto/tender", "inLanguage": "en-GB", "isPartOf": { "@type": "WebSite", "name": "SEO7.ES", "url": "https://seo7.es/" }, "publisher": { "@type": "Organization", "name": "SEO7.ES", "url": "https://seo7.es/" } } ```