Public Tenders · Bolivia

Bolivia's public spending, out in the open.

We opened a protected procurement portal and turned two decades of public tenders into a clean, ready-to-analyse dataset for investors, researchers and journalists.

Coverage
2006–2024
Tenders
10 M
Security layers
3
Status
Ready to use
Executive summary

The problem, the solution and the result

01 · The problem

Public data, locked away

The official tenders website restricts large-scale access and hides its data behind several security layers, which keeps investors, researchers and analysts in the dark.

02 · The solution

Scraping, reverse engineering and AI

We combined advanced web scraping, API reverse engineering and a neural network that reads the CAPTCHA, to retrieve structured data programmatically.

03 · The result

A dataset ready to analyse

Ten million historical tenders, from 2006 to 2024, structured for market research, forecasting and academic studies.

Technical approach

Four steps from a closed portal to a clean dataset.

The project automates the extraction of Bolivia's public tender data, overcoming each barrier of the official website with a different technique.

  1. 01

    Identifying the data source and its security

    The portal gives no direct access to structured data. It is protected by hidden API endpoints, session-based secret tokens and CAPTCHA verification.

  2. 02

    API reverse engineering

    The website generates unique secret tokens and injects them with JavaScript before the page finishes loading, which hides them from ordinary scrapers. Our scraper intercepts the scripts, extracts the tokens and rebuilds the requests to reach the data programmatically.

  3. 03

    CAPTCHA solving with a neural network

    Every request for more information requires a CAPTCHA. We trained a Convolutional Neural Network (CNN) to decode the images, and used data augmentation to expand the training set without extensive manual labelling. The model reaches high accuracy on this security layer.

  4. 04

    Data retrieval and pipeline

    Because the OCR model is lightweight, we chose multiprocessing over asynchronous requests: one worker per CPU core runs the whole extraction in parallel.

Dataset

Bolivia Public Tenders

Historical, ready-to-use data from 2006 to 2024. Ideal for researchers and businesses: use it for in-depth analysis, market research, forecasting or academic studies, and gain actionable insight into Bolivia.

The data was gathered and is ready for analysis, giving a comprehensive snapshot of the public tenders of Bolivia.

10 MPublic tenders

Extraction pipeline: tokens, CAPTCHA decoding and parallel data retrieval
Purpose and impact
Transparency in public spending matters most in a crisis.

This project was born from a national financial crisis. Unlike in most countries, public tenders in Bolivia sit behind security barriers that limit access for investors, journalists and citizens. The next step is a deep analysis of the extracted data, with insights into this issue.

More about this

Want the dataset or a deeper analysis?

To access this dataset or learn more about the project, contact us.

BS Bartor S.Founder