Parsing open data about sellers from marketplaces

Budget: 25000 UAH Deadline: 7 days

We can take the first stage - check the possibility of automated data collection, gather a test database of sellers, and show which fields can be reliably obtained.

We have worked with marketplaces and e-commerce on tasks related to data collection, catalogs, sellers, products, prices, stocks, ratings, categories, links, quantities of products, contact and public business fields - if they are open and accessible without violating the platform's rules.

> What I would do at the start
>> define the list of marketplaces and technical limitations for each
>> check available fields - seller name, link, categories, rating, quantity of products, product pages, other open data
>> gather a test sample and structure the database
>> prepare the logic for updating, deduplication, and data quality control

Look, there’s a nuance - for an accurate assessment, two things need to be known.
> Which specific marketplaces need to be processed
> Is the database needed once or as a regular data update tool

Examples of similar work by Ingello
> https://business.ingello.com/prime-eva - e-commerce, processes, data, and system automation
> https://business.ingello.com/eva - retail, data structure, and working with large volumes of information
> https://business.ingello.com/vorfahr - automation of data collection and processing, close to the task logic

The main page of Ingello for the exchange - https://systems-fl.ingello.com/ua

Preliminarily, I would estimate the first stage at 25,000 UAH and 7 days. After the test sample, it will be clear whether we can scale the collection reliably or if it’s better to create separate logic for each platform. !!The main thing is to first check the actual availability of data, not to build a system on assumptions!! =/ Expand

Budget: 1500 UAH Deadline: 2 days

Hello. The task is clear; automating the collection of such data is entirely possible (through marketplace APIs or web scraping with bypassing block protection).

Answers to your questions:

Experience with marketplaces: I have worked with parsing Prom, Rozetka, OLX, as well as foreign Amazon and Allegro.

Data I can collect: Company/seller name, store link, contact details (if they are publicly available/in the profile), rating, number of reviews, assortment volume (number of products), main categories, and current status (active/inactive).

Project examples: I collected a supplier database from Prom.ua by categories with export to Google Sheets, and also monitored prices and product availability among competitors on Rozetka.

I am ready to do a test collection of a few items for you to check the quality and structure of the data. Expand

Budget: 700 UAH Deadline: 4 days

Good day, Olga! I am gathering databases of sellers from marketplaces using Python — I export the name, link, categories, rating, and quantity of products into a structured table. First, I check if the platform provides data without blocks, and I do a small test sample so you can immediately see the format and completeness of the fields. Which marketplaces are we working with — Ukrainian Rozetka/Prom or also foreign ones?

Budget: 5000 UAH Deadline: 3 days

Hello! I am ready to implement an automated data collection system for sellers for you. The task is absolutely feasible, as I specialize in web scraping and bypassing marketplace protections.

I will answer your questions point by point:

1. Which marketplaces I work with:
I have experience parsing Wildberries, Ozon, AliExpress, Rozetka, Prom, and Amazon. Separate algorithms are written for each platform using Python (Requests, Scrapy, Playwright) and proxy rotation to bypass blocks.

2. What data can be obtained:
The exact list depends on the specific platform, but in most cases, the following can be extracted:

Seller name (individual entrepreneur/legal entity/brand) and a link to their storefront.

Legal data (TIN, OGRN), if the marketplace publishes them.

Overall seller rating and number of reviews.

Number of products (SKU) in stock.

Categories and niches in which the seller is represented.

Sales volume (estimated, based on purchases/reviews).

Contact details (if they are specified in the profile or open registers by TIN).

3. Examples of similar projects:

Collection of a database of 15,000+ sellers from Ozon and Wildberries in the "Clothing" category for a B2B mailing of a logistics company.

Parsing contact details of sellers from the Prom.ua platform with the export of their catalog structure.

Monitoring the top 100 sellers on Amazon with daily updates of their ratings and the number of new products.

I am ready to discuss which specific marketplaces interest you first and to make a free test export of 50-100 sellers so you can evaluate the quality of the data. I look forward to your message! Expand

Budget: 2500 UAH Deadline: 3 days

Hello! I specialize in data parsing and structuring — I can gather open information about sellers and create a database in your format (Excel/CSV/Google Sheets or directly in a database).

Marketplaces: I have worked with OLX, Prom, Rozetka — I parsed listings, prices, seller data. I will adapt my approach to the platform you need.

The data I can realistically extract from open pages includes: seller name, profile link, categories, rating and number of reviews, number of products, registration date — plus everything else that is publicly available. First, I will create a small test sample so you can see which fields can be realistically collected from your platform, and then we can finalize the database structure.

Please clarify: (1) which specific marketplaces and (2) is this a one-time extraction or do you need periodic updates of the database? This will affect the exact estimate.

I am starting at a low price — I am gathering my first reviews on Freelancehunt, so I am offering a good deal. I am ready to show a live demo of the parsing in the chat.

Budget: 5500 UAH Deadline: 6 days

Good day, Olga! Parsing marketplaces is my specialty (Python, automated data collection + structuring).

Regarding your points:
• Experience: I have collected public data from large trading platforms — seller catalogs, product cards, listings (via API where available, otherwise careful page parsing).
• Data I extract: seller name, profile link, categories, rating/reviews, number of products + other public fields from the seller's page (exact list will be determined for each specific platform).
• Result: structured database (CSV / Google Sheets / DB) + honest assessment of the possibilities and limitations of automation for each platform (limits, anti-bot measures, volume).

I suggest starting with a brief technical analysis of the selected platforms — I will provide a precise plan, fields, and timelines without guesswork. Please let me know which marketplaces are a priority and the approximate volume (how many sellers)? I will show examples of my work in our correspondence.

Budget: 1000 UAH Deadline: 2 days

Good day!
I have my own ready-made parsers in Python (requests + BeautifulSoup) — I have already implemented data collection from Work.ua (vacancies), Auto.ria (cars), and SvitBudov (real estate): name, price, location, link, deduplication by URL. I can show the code or an example of the exported JSON.
These platforms do not have complex anti-bot protection, so the tasks are technically similar. If your marketplaces have captcha/Cloudflare — I also have experience bypassing it through Playwright on another project, and I can adapt the approach.
I suggest starting with a test sample: 15-20 sellers from one platform, I will show a real list of fields that are consistently collected, and the format (Excel/CSV/JSON). After that, we can agree on the full scope.
Please clarify: which specific marketplaces and is it a one-time export or do you need regular updates?

Budget: 20000 UAH Deadline: 10 days

Good day. I specialize in parsing. Any fields can be parsed, as long as they are on an HTML page. We can discuss the price, deadlines, and requirements in person.

Budget: 5000 UAH Deadline: 5 days

Hello, Olga!

I have experience in automated data collection and building structured databases (Python, API/HTML parsing, exporting to Excel/Sheets or a database).

To accurately assess the volume and choose the right approach, please clarify:

1. Which specific marketplaces are you referring to (Rozetka, Prom, OLX, others)?
2. What is the purpose of the seller database — market analysis, finding potential partners, or something else? This will help understand which fields are truly needed and which are excessive.
3. Estimated volume — how many sellers do you plan to collect, and do you need a one-time export or ongoing database updates?

After clarifying the details, I am ready to propose a specific approach, timeline, and cost. Expand

Budget: 2000 UAH Deadline: 2 days

Good day!
From open data, I consistently extract: name, category, rating, number of reviews, website/phone, link to the card — here is an example of real data extraction: https://github.com/kondrat23051978/google-maps-scraper (there is also a screenshot with live data).
I have already worked with Rozetka — I know the specifics of protection (captcha at certain steps, manual verification or recognition service needed), I collected data on products: name, price, brand, specifications, link. Here is an example of the approach to structured data collection: https://github.com/kondrat23051978/google-maps-scraper
Question: which specific marketplaces are needed — this significantly changes the complexity. And is the database needed once or with regular updates?
I am ready to collect data from 1 marketplace in 2 days.

Budget: 1000 UAH Deadline: 1 day

Hello, Olga!
I have direct experience in parsing marketplaces and can show it. Structuring the extracted data into a clean database is my daily work.
Let me be honest about the main point right away. The feasibility depends on which specific platforms you are interested in. For some, sellers are willing to share data easily, while others have captchas and limits on each request. Therefore, I do the collection defensively by default: controlled request pace, retries on failures, deduplication on records. This is to ensure the database is collected steadily and doesn't get banned after ten minutes.

The fields that can realistically be obtained from open pages include: seller name, profile link, categories, rating, number of products and reviews, often the registration date. As for closed fields, such as private phone numbers or emails, I will be honest. If they are not publicly available, I won't promise what is physically not there. I will not sell non-existent data.

One point about volume. One hundred sellers and half a million are different tasks in terms of complexity. If you have an approximate idea of the number, the estimate will be more accurate.

I offer a free trial. You name one platform, I will take a few sellers and show you a ready table with the real fields that I managed to collect. This way, you will immediately see if automation is possible and what specific data can be obtained, even before starting the main work. This directly answers your question about the possibility of collection.

Please let me know which marketplaces are a priority, and we will get started. Expand

Budget: 1500 UAH Deadline: 4 days

Hello! I am a Python developer specializing in automation and data parsing. Honestly, I haven't gained specific experience with marketplaces yet, but I understand the technical task — collecting public data (name, link, category, rating, number of products) using requests/BeautifulSoup or Selenium if the site has dynamic loading (JS). To ensure you don't take any risks and can evaluate the result before payment, I am ready to collect data for 1-2 sellers from the marketplace you need for free in a few hours and show what can actually be obtained. If you are satisfied, I can complete the entire project.

Budget: 1000 UAH Deadline: 1 day

Good day, I am writing on behalf of the company Devoxen. We specialize in developing parsers and automating data collection. We have extensive experience working with marketplaces and implementing solutions for automated collection and structuring of open information. We can obtain the seller's name, store link, categories, rating, number of products, contact and other available public data, as well as create a structured database with the possibility of further updates. We will do this without unnecessary questions and wasting time. We also provide a guarantee and, if desired, further support. We can start working on your project immediately after discussing the technical specifications.

I suggest we move to private messages for a more detailed conversation.

Budget: 8000 UAH Deadline: 4 days

Good day!

I create parsers for data collection, so straight to the point — the main thing here is not to "scrape," but how consistently a specific marketplace allows this to be done.

Regarding the data: seller name, profile link, categories, rating, number of products and reviews, registration date, sometimes contacts/location — everything that is publicly available on the seller's page can be collected and structured (CSV / Google Sheets / database).

What determines the "possibility of automation" is the protection of the specific platform. Some provide data freely, while others have captchas and limits on each request. Therefore, my approach is protective by default: controlled request pace, retries with backoff, deduplication on record — to ensure the collection lasts long and doesn't fail after 10 minutes due to a ban. An example of this logic (throttling, retries, dedup) in code: github.com/novellocaitlin13-ui/async-scraper.

Regarding experience with platforms — I have worked with scraping marketplaces and classifieds. But to be more honest: name your target marketplace and approximate number of sellers — and I will respond with which fields can realistically be obtained, how complete the coverage will be, and whether there is protection that complicates things. Which one shall we start with?

Budget: 5000 UAH Deadline: 5 days

It is necessary to gather a database of sellers from marketplaces in a structured format. Approach: Python + Playwright or requests depending on whether the page is rendered by the client; parsing fields such as name, link, categories, rating, number of products, and everything that is publicly available; output in Excel/CSV or directly into a database. Key risk: anti-bot protection on Rozetka, Prom, Amazon, etc., so implement proxy rotation and bypass rate limits to prevent the parser from breaking silently.

Which specific marketplaces are you interested in and approximately how many sellers need to be gathered?

Budget: 15000 UAH Deadline: 7 days

Good day! We have experience in developing parsers for Prom, Rozetka, and Amazon. We implement this through Python using Playwright to bypass protection and subsequently structure the data in a format convenient for you. We are ready to set up automatic updates of the seller database and ensure the stability of information collection.

Budget: 5500 UAH Deadline: 7 days

Good day!

I have reviewed the task description. I have experience in developing parsers and collecting public data (API / GraphQL / HTML), as well as structuring large volumes of information.

Preliminarily, the task seems technically feasible. I can do:
- analysis of marketplaces and data sources
- implementation of data collection about sellers
- structuring and cleaning data
- export to CSV / JSON or any other required format

I suggest starting with a brief technical analysis of 1–2 marketplaces to accurately determine the scope of work and data sources.

After that, I will provide exact deadlines and a final estimate. Expand

Budget: 4000 UAH Deadline: 3 days

Hello! Parsing, cleaning, and structuring large datasets is my specialty as a Python engineer. I implement stable, fast, and fully automated data collection solutions "turnkey."

Clear answers to your questions:

Experience with marketplaces: I have successful experience in parsing large e-commerce and classified platforms (including Rozetka, Prom, OLX). I can bypass content scraping protection (Cloudflare, CAPTCHAs, IP blocking) using proxy rotation and simulating real user actions.

What data I will collect and structure: A complete range of open markers: seller/store name, direct link to the profile, category/niche of products, current rating, number of reviews (positive/negative), total number of products available, as well as contact details (phone, email, social media), if they are publicly available.

Technical stack and format: I write scripts in pure Python using asynchronous libraries (for maximum collection speed). I clean and structure data using Pandas. I will provide the final database in any format convenient for you: Excel (XLSX), CSV, or I can directly integrate it into a database (PostgreSQL/SQLite).

I am ready to discuss a specific list of marketplaces in the chat and conduct a free test collection of the first 10–20 items so you can check the quality of the data structure before we start collaborating! Expand

Budget: 2000 UAH Deadline: 2 days

Hello! I am currently creating a parser for myself, but not only for collecting information from the page, but also for searching for all possible data (I currently need all social networks, contacts, and websites). The search for companies based on specified parameters from Google Maps, Instagram, and Prom is already working, and I plan to add other directions. Right now, I am fine-tuning the data search process. I can expand it according to your requests, and we can agree on payment terms that are beneficial for both of us. Alternatively, I can simply gather the necessary information for you once. Or a full-fledged tool. Whatever you choose, the price and deadlines will be accordingly 😉
In general, message me privately - we will discuss the most advantageous option.

Budget: 2500 UAH Deadline: 3 days

Good day. The task is clear: to gather and structure open information about sellers from marketplaces and to form a database from this, and first to assess whether this can be automated for specific platforms.

Data collection is my main area. I have worked with scraping in Python (Selenium, Playwright, requests plus parsing), with proxies and bypassing simple anti-bot protection, and with structuring the results into a clean database or table. Typically, I can reliably extract: seller name, profile link, categories, rating and number of reviews, number or assortment of products, registration date, and contacts if they are available in the public profile. What can be extracted depends on the specific marketplace, so as a first step, I will look at one or two of your target platforms and tell you exactly which fields are consistently available and where protection will make data collection more expensive.

Which specific marketplaces are we working with and what approximate volume of sellers is needed in the database? This will affect both the approach to data collection and the timelines.

Budget: 2500 UAH Deadline: 1 day

Hello!
There are ready-made promo and socket databases collected in May-June.
Write in private.

Budget: 1000 UAH Deadline: 1 day

Good day. I can compile a database of sellers with all their open data. An example of parsing from Prom.ua - https://docs.google.com/spreadsheets/d/1ZO_SadmdwQUbsk409n2IF247es-lLNbq/edit?usp=sharing&ouid=114223714505988358220&rtpof=true&sd=true. Which marketplaces are you interested in? This will affect the price and the completion time.

Budget: 18000 UAH Deadline: 7 days

We already have a practically ready similar solution for collecting open data from marketplaces, which can be quickly adapted to your sources and launched =)
We can discuss the details here; I am available.
I see the initial phase lasting 7 days and costing 18,000 UAH - checking 1-2 marketplaces, collecting a prototype, structuring the database, exporting to a table or database, and a brief conclusion regarding scaling.
We have worked with Rozetka, Prom, Shopify, WooCommerce, OpenCart, XML and YML product feeds, price synchronization, stock levels, categories, and product cards.
From open fields, we can usually obtain the seller's name, link, categories, rating, number of products, reviews, city or region, public contacts if available on the page, collection date, and technical status of the check.
The implementation scheme is simple - first, we check data availability and platform limitations, then we perform collection, cleaning, deduplication, storage, and quality control.
Next, we can add AI for classifying sellers, searching for potentially interesting niches, and prioritizing leads - it seems to fit well with your task.
First question - which marketplaces and categories are a priority for you?
Second question - do you need a one-time database or regular updates?
Relevant examples - https://business.ingello.com/prime-eva - e-commerce and retail, where structured work with products and data is important.
Another example - https://business.ingello.com/eva - about systematic automation of processes in retail.
A related example with AI and automation - https://business.ingello.com/vorfahr - there is a similar logic of quick collection, structuring, and use of data in the business process.
Main page of Ingello for the exchange - https://systems-fl.ingello.com/ua Expand

Budget: 1000 UAH Deadline: 1 day

Hello. I am a specialist in collecting contacts from OLX. I have my own parser.
I can parse the Business section (paid ad packages, stores).
Example database https://tinyurl.com/36vfc3tw
The price depends on the categories and quantity.

Budget: 3500 UAH Deadline: 4 days

Hello! The task is completely clear. I specialize in automated data collection (web scraping) and bypassing marketplace protections.

Collecting such data manually takes weeks of wasted effort, so automation is not just possible here, but the only sensible option. Instead of a static Excel file that will become outdated in a week (as sellers change, add products, or leave the platform), I will develop a personal automatic parser script for you. You will be able to run it at any moment and receive fresh, relevant data in just a few minutes.

Answers to your questions:

1. Experience with marketplaces:
I have successful experience parsing Prom.ua, Rozetka, OLX, Epicenter, Shafa, as well as foreign platforms (Amazon, AliExpress). I know how to bypass their blocking protection systems (Cloudflare, captchas) to ensure stable data collection.

2. What data we can obtain in the final table:
- Company / seller name;
- Link to their store or profile;
- Main and additional product categories;
- Seller rating and percentage of positive reviews;
- Number of products in the assortment;
- Contact details (phones, email, links to social networks), if they are publicly available on the seller's page.

3. Examples of similar projects:
I implemented automatic supplier database collection from Prom.ua with category filtering, as well as monitoring competitor prices on Rozetka with exporting the finished report to Excel.

In the end, you will receive a convenient, structured Excel table with all sellers + the tool (script) for its regular updates.

Please let me know which marketplaces (for example, Prom, Rozetka, or others) you would like to work with first? Message me privately, and we will discuss the details! Expand

Budget: 1500 UAH Deadline: 2 days

Good day! I have reviewed the task — it will be implemented. I have experience in data collection from Rozetka, Prom.ua, OLX, Amazon, and AliExpress. For each seller, I can gather the name, link, categories, rating, number of products, and other available fields — depending on the specific marketplace. Please clarify which marketplaces you are interested in and the approximate number of sellers that need to be collected? I am ready to take it on.

Budget: 2000 UAH Deadline: 3 days

Hello!

I am ready to help you with automated data collection and structuring for sellers. I specialize in web scraping and can find unconventional solutions for complex tasks.

Experience with marketplaces:
I have practical experience working with many platforms, including Prom, Rozetka, and others.

What data can I collect (depends on the specific site):

Seller name and link to the store;

Product categories and total assortment volume;

Seller rating and number of reviews;

Any other open fields on the page (registration dates, contacts, etc.).

Examples of work:
My latest project involved complex scraping of over 20,000 product photos with successful circumvention of website bot protection, as well as subsequent software editing of these photos to meet strict client requirements. You can see feedback on the successful completion of this task in my profile. More scraping examples are available in my portfolio.

I am always available, guarantee good communication, and show initiative in optimizing collection processes.

For an accurate assessment of scraping capabilities and timelines, I need details about the target marketplaces. I am ready to discuss the project in messages! Expand

Budget: 1000 UAH Deadline: 1 day

Hello!

I have extensive experience in developing solutions for parsing and processing data (various sources, protection against blocking, automation). I am ready to complete the assigned task in the shortest possible time.

I suggest we discuss the details in private messages.

Budget: 1500 UAH Deadline: 2 days

Hello, Olga! I am ready to implement automated collection and structuring of data about sellers. I have successful experience in parsing large marketplaces (Rozetka, Prom, OLX, as well as foreign platforms) using my own scripts in Python (BeautifulSoup, Selenium). The script is capable of bypassing basic website protections and collecting all necessary fields: seller name, direct link, category, rating, and number of products in stock. I will format the result as a clean structured database in Excel (or CSV/XML as you wish). I am ready to discuss the details and perform a test collection of a few items to demonstrate the result. I look forward to collaborating through a Secure Agreement!

Budget: 1180 UAH Deadline: 3 days

Hello!

I have reviewed the task. I am ready to implement automated data collection and create a clean, structured database of sellers.

Experience with marketplaces:
I have a great understanding of the architecture and logic of both local and international platforms (specifically Prom, Rozetka, OLX). I have a clear understanding of how to work with their pagination, bypass bot protection, and collect data using AJAX/API or page rendering.

What data I can obtain: The script collects all open fields on the seller's page: name, full link, main and subcategories of products, rating, reviews, number of products in the assortment, as well as contact details (phone, email), if they are publicly available.

I usually develop parsers in Python (Requests, BeautifulSoup, Selenium/Playwright). I carefully export the data to Excel, CSV, or Google Sheets, cleaning it from HTML junk and duplicates.

Bonus: To ensure you are confident in the result, I offer to do a test collection. Name one marketplace you are interested in, and I will collect the first 20-30 sellers for you in a table for free. If the quality is satisfactory, you can approve me as the executor.

Feel free to message me, I am ready to do the test today! Expand

Budget: 2000 UAH Deadline: 1 day

I offer 50,000 sellers from prom.ua

contacts/ratings/product categories, etc. - maximum data

Budget: 6500 UAH Deadline: 7 days

Olga, it seems you need to gather open data about sellers from marketplaces to create a structured database. I understand that it's important not just to collect, but also to determine what specific information can be reliably obtained automatically.

First, I will analyze the selected marketplaces to identify all available fields for collection: seller name, link, product categories, rating, number of reviews, etc. Then, I will develop a tool for automatic collection and export of this data in a format convenient for you (CSV/Excel). The result will be a ready database that you can use.

Which specific marketplaces and data fields are you primarily interested in so that I can make a more accurate assessment?

Budget: 1000 UAH Deadline: 1 day

Hello, I can help with data collection. I have experience in collecting and processing large datasets from open sources.

I have worked on similar tasks related to marketplaces and catalogs, where it was necessary to clean data, remove duplicates, and normalize the structure for analytics or CRM.

Could you please specify which marketplaces you plan to work with and whether you need a one-time data collection or regular parsing with updates?

Budget: 1000 UAH Deadline: 1 day

Hello! I specialize in parsing, so I can parse any marketplace for you and collect all the necessary data. You can view examples of my work in my portfolio. I would be happy to collaborate with you!!!

Budget: 2000 UAH Deadline: 1 day

Good day! I can provide fresh data on all Prom vendors. There are 43,427 vendors in the database. The file contains the following data: URL, Categories, Status, Store Name, Description, Seller Reviews, Positive Reviews, %, Seller Office, Phones, Email, Website.

Budget: 2000 UAH Deadline: 2 days

Parsing seller data from marketplaces is a familiar task. I have experience working with OLX, Prom, Rozetka: I collected seller profiles, prices, categories, ratings, and the number of products. I use Python (requests + BeautifulSoup / Playwright / Selenium) depending on the website structure. The result can be in Excel/CSV or directly in a database (PostgreSQL/MySQL). Typical fields include: name, profile link, categories, rating, number of reviews, products, registration date. Initially, I will create a test sample of 10–20 records so you can see the actual data format — then we will finalize the structure. Please let me know which marketplace and whether you need a one-time export or regular updates.

Budget: 1111 UAH Deadline: 2 days

Good evening, I am ready to complete your order and would be happy to collaborate further. Write to me here in private messages, and I will send you examples of my work. I can also send you a link to my portfolio.

Budget: 700 UAH Deadline: 3 days

Good day!

I am interested in your project. I have experience in collecting and structuring data from open sources, including marketplaces, online stores, and company directories.

I have worked on gathering information from various marketplaces and trading platforms. I can collect such data if it is publicly available: seller name, link to the store or profile, product categories, rating, number of products, number of reviews, seller description, and other available characteristics.

I also have experience in executing projects for collecting B2B databases, parsing open data, structuring information in Excel and Google Sheets with checks for duplicates and relevance.

I am ready to analyze the possibility of automated data collection for the required marketplaces and propose the optimal implementation option.

I look forward to collaborating! Expand

Budget: 2600 UAH Deadline: 3 days

Hello. I have a very good understanding of the topic of parsing. I am ready to take on your work.

I have worked with marketplaces such as OLX, PROM, Rozetka - I can parse all the necessary information from these platforms and save it in the required format for the client if needed.

Budget: 1000 UAH Deadline: 1 day

Good evening
I am interested in your project.
I would like to discuss everything in more detail.

Budget: 4000 UAH Deadline: 1 day

Hello. I am ready to complete the project turnkey, guaranteeing quality and promptness.

Feel free to message me, I would be happy to collaborate!