Freelancers using Python in State of São Paulo

Freelancers using Python in State of São PauloFreelancers using Python in State of São Paulo

Projects People

São Paulo, Brazil

AI Engineer | Agents, Automation & Integrations

5.0: Rating

12: Followers

AI Engineer | Agents, Automation & Integrations

Cover image for I'm currently building Omnicrm.chat (http://OmniCRM.chat).

I'm currently building Omnicrm.chat (http://OmniCRM.chat). A CRM and multichannel communication platform designed to keep customer conversations, sales opportunities, and operational workflows in a single workspace. Most teams still manage WhatsApp, Telegram, email, proposals, tasks, and customer records across multiple disconnected tools. The result is lost context, duplicated work, and a fragmented customer experience. With OmniCRM.chat (http://OmniCRM.chat), conversations can evolve into opportunities, projects, and tasks without manual data entry. The goal is to connect communication, CRM, and execution into one platform, while creating a foundation for future AI-driven automation across the entire customer lifecycle.

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Cover image for App name: WeeklyMind

Category: lifestyle

An AI-powered

App name: WeeklyMind Category: lifestyle An AI-powered weekly planning app that helps users organize routines, goals, habits, and schedules through natural conversations. Users can talk with the AI about work, health, focus sessions, and personal balance, while the assistant automatically creates tasks, goals, and smart weekly plans in a calm and minimal mobile experience. Branch vision ID version test : https://weeklymind.bubbleapps.io/version-test/api/1.1/mobile/preview?debug_mode=true&preview_view=Home

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Cover image for AI-Powered OCR Pipeline for Document Processing

Most OCR systems stop at text extraction. The real value starts after the document is read. In this project, I built an AI-powered OCR pipeline capable of extracting text from invoices, contracts, reports, and forms while also classifying the document type and identifying key information automatically. Instead of returning raw text only, the system structures the data into usable outputs for automation workflows, CRMs, ERPs, and AI agents. This reduces manual processing time and makes documents immediately actionable inside business operations. The stack combines OCR engines with LLM-based processing for contextual understanding, keyword extraction, and intelligent classification. The result is a more reliable document processing flow that can integrate directly with APIs, databases, and automation systems. This is where AI engineering becomes practical: transforming unstructured files into structured business data at scale

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Cover image for Intelligent AI Agent for Business Automation

Most businesses are already experimenting with AI — but very few are using it the right way. A generic chatbot is not enough. What actually drives value is a custom AI agent built around your workflows, capable of calling APIs, automating decisions, and integrating directly with your systems. This is where AI stops being a demo and starts becoming infrastructure. With the right architecture, your AI can handle operations, reduce manual work, and scale processes without increasing costs — from customer support to internal tools, data processing, and beyond. If you're thinking about building a real AI solution tailored to your business, let’s talk.

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Barra Bonita, Brazil

AI Automation Engineer | Python, APIs & Workflow Automation

New to Contra

AI Automation Engineer | Python, APIs & Workflow Automation

Cover image for Web Scraping & Data Extraction

Web Scraping & Data Extraction Solutions | Python & Scrapy Developed automated data extraction solutions to collect, process, and deliver business-critical information from websites and online platforms. Full Description: As part of my work at Cotefácil, I developed web scraping solutions using Python and Scrapy to gather information from partner platforms and e-commerce websites. The extracted data was processed and integrated into internal systems, supporting automation workflows and business operations. The focus was on creating reliable, maintainable, and scalable scraping solutions capable of handling large volumes of information efficiently. Technologies: Python, Scrapy, Data Extraction, Web Crawling, Automation, Data Processing. Key Achievements: ✔ Developed scalable web scraping solutions using Scrapy ✔ Automated data collection from external platforms ✔ Reduced manual effort through automated extraction workflows ✔ Supported business integrations with high-quality structured data

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Cover image for Pharmacy System Integration Platform |

Pharmacy System Integration Platform | Python, APIs, AWS & Automation Developed integration solutions connecting pharmacy management systems with partner distributors, enabling automated data exchange and improving operational efficiency. At Cotefácil, I worked on the development and maintenance of backend systems responsible for integrating pharmacy software with partner distributors. The project involved designing and implementing Python-based API solutions, automating data synchronization processes, and building cloud infrastructure to support reliable and scalable operations. I also contributed to deployment automation and infrastructure management, helping the team deliver consistent and maintainable solutions. Technologies: Python, REST APIs, Docker, AWS, Terraform, CI/CD. Key Achievements: ✔ Built scalable API integrations between pharmacy and distributor systems ✔ Automated business-critical data synchronization processes ✔ Developed cloud infrastructure using AWS and Terraform ✔ Improved deployment reliability through Docker and CI/CD practices

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Cover image for AI-Powered Payment Processing Automation (Thoughtful

AI-Powered Payment Processing Automation (Thoughtful AI) Developed AI-driven automation workflows for healthcare payment processing, significantly reducing manual effort and improving operational efficiency through Python-based RPA solutions. One of the key challenges involved processing payment information from websites where payment details were only available as images rather than structured data. To overcome this limitation, I researched, implemented, and integrated OCR technology into the automation workflow, enabling the system to accurately extract payment information from images and automatically enter the data into downstream systems. This solution improved data processing reliability, reduced manual intervention, and expanded the automation's ability to handle previously unsupported payment scenarios. Skills: Python, RPA, AI Automation, Process Automation

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Cover image for Healthcare Eligibility Verification Automation (Thoughtful

Healthcare Eligibility Verification Automation (Thoughtful AI) Designed and delivered an automation solution that achieved 100% verification accuracy while reducing processing time by 99% through API integrations, portal automation, and voice automation technologies. Skills: Python, API Integration, Automation, AI, Healthcare

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Guilherme Farinassi

São Paulo, Brazil

Penetration Tester & Security Researcher | Web, Mobile & API

New to Contra

Penetration Tester & Security Researcher | Web, Mobile & API

Cover image for Bug Bounty Research - Web

Bug Bounty Research - Web Vulnerability Discovery Conducted independent bug bounty research on public VDP and paid programs (Bugcrowd/HackerOne). Discovered and reported multiple valid vulnerabilities including IDOR exposing PII, stored XSS in user-controlled fields, SSRF via internal metadata endpoint, authentication bypass via JWT manipulation, and sensitive data exposure through misconfigured S3 buckets. Findings spanned government agencies, SaaS platforms, and financial services targets. Documented all findings with full reproduction steps, CVSS scoring, and business impact analysis following responsible disclosure guidelines.

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Cover image for API Security Assessment - REST

API Security Assessment - REST and GraphQL Endpoints Performed a black-box API security assessment covering REST and GraphQL endpoints for a fintech platform. Identified BOLA/IDOR vulnerabilities allowing unauthorized access to other users financial data, mass assignment flaws exposing admin-only fields, broken function-level authorization on privileged endpoints, and GraphQL introspection exposing internal schema. Also found SSRF via webhook URL parameter and JWT algorithm confusion (RS256 to HS256). Delivered OWASP API Top 10 aligned report with curl-based PoC for each finding and remediation guidance.

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Cover image for Mobile Application Pentest - Android

Mobile Application Pentest - Android Banking App Conducted a full black-box mobile penetration test on an Android banking application following OWASP MASTG methodology. Identified 17 vulnerabilities including 5 critical findings: hardcoded AES encryption keys in SharedPreferences, SSL pinning bypass via Frida instrumentation, root detection bypass via LIEF binary patching, exported Activities without permission checks, and sensitive data exposed in Logcat. Delivered MASTG-aligned report with CVSS scoring and PoC code for all critical findings.

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Cover image for Web Application Pentest — Insurance

Web Application Pentest — Insurance Portal Conducted a full black-box web application penetration test on an insurance client portal. Identified 11 vulnerabilities including 3 critical findings: unauthenticated access to customer PII (CPF, phone, address), broken authentication allowing account takeover, and exposed debug endpoints with Facelets stack traces. Delivered a structured report with CVSS scoring, PoC for each finding, and prioritized remediation guidance. All critical findings were reproduced and confirmed in a retest cycle. Stack targeted: Java EE, REST APIs, JWT auth, LGPD-sensitive data.

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Gabriel Felix dos Santos

Mirandópolis, Brazil

📈 Data's Tale Needs a Narrator

📈 Data's Tale Needs a Narrator

Cover image for 📊 Dashboard US Stores Sales

📊 Dashboard US Stores Sales

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Cover image for 📁 CSV Analyser

📁 CSV Analyser

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Cover image for 🚀 Space Titanic Competition

🚀 Space Titanic Competition

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Cover image for 🌟 Face, Eye and Motion Detection

🌟 Face, Eye and Motion Detection

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São José dos Campos, Brazil

Data Analyst & Power BI Speciast | Power Query | Excel | SQL

Data Analyst & Power BI Speciast | Power Query | Excel | SQL

Cover image for Project Overview Dashboard

Project Overview Dashboard

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Cover image for Hotel Data Analyses

Hotel Data Analyses

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Cover image for Toman's Bike Share Dashboard

Toman's Bike Share Dashboard

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Henrique Oliveira Dos Santos

São Paulo, Brazil

Certified AWS Architect & DevOps Engineer

Certified AWS Architect & DevOps Engineer

Cover image for HenriqueOs98/sb-backend-challenge

HenriqueOs98/sb-backend-challenge

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Cover image for HenriqueOs98/-Haunted-House-Three.js

HenriqueOs98/-Haunted-House-Three.js

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Cover image for Programe.TECH

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Sorocaba, Brazil

Building AI Agents & SaaS with Next.js

8: Followers

Expert

Building AI Agents & SaaS with Next.js

Cover image for LeadInsights: Data Mining Tool (Developed

LeadInsights: Data Mining Tool (Developed in Replit) A Python-based lead qualification tool. The entire development lifecycle, from initial scripting to final debugging, was executed within the Replit cloud IDE. Replit Development Workflow: Zero-Setup Environment: Leveraged Replit's pre-configured Python environment to immediately start coding complex data processing scripts using pandas and BeautifulSoup without local dependency hell. Interactive Debugging: Utilized the Replit Shell heavily to run ad-hoc data scraping tests and inspect data frames in real-time before integrating them into the main application logic. Package Management: Managed Python dependencies directly through the Replit console, ensuring a reproducible development environment. Stack: Python, Pandas, Web Scraping Libraries (Developed directly in Replit).

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Cover image for SaaS Platform: TENET AI (Built

SaaS Platform: TENET AI (Built on Replit) A multi-tenant AI agent platform developed entirely within the Replit ecosystem. Replit-First Workflow: Cloud IDE: Used Replit as the exclusive environment to build complex Python/FastAPI microservices without local setup. AI Assisted: Leveraged Replit Ghostwriter to accelerate boilerplate generation for the multi-agent orchestration logic. Debugging: Utilized the Replit Shell for real-time testing of WhatsApp API webhooks before pushing to production. Stack: Python, FastAPI, PostgreSQL. (Production deployed via Railway, Development via Replit).

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Cover image for BudgetCalc - Smart Project Estimator

BudgetCalc - Smart Project Estimator

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Cover image for Official Website: TENET AI (High-Conversion

Official Website: TENET AI (High-Conversion Landing Page) The public-facing portal and onboarding flow for the TENET AI ecosystem. Built with Replit: Rapid Prototyping: Used Replit's instant preview environment to iterate on the UI/UX design in real-time without local server setup. Frontend Performance: Optimized assets and code splitting directly within the Replit editor to ensure high Lighthouse scores. Zero-Config Dev: Leveraged Replit's pre-configured templates to jumpstart the development of the responsive layout. Stack: HTML5, Tailwind CSS, JavaScript (Developed in Replit).

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Fernando Freitas

São Bernardo do Campo, Brazil

AI & ML Engineer | Full Stack, data-driven solutions expert

AI & ML Engineer | Full Stack, data-driven solutions expert

Cover image for Insights AI | Web app for auto data analysis

Insights AI | Web app for auto data analysis

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Cover image for Copilot | AI assistant for data exploration

Copilot | AI assistant for data exploration

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Cover image for Gmail AI | AI agent for email auto labeling

Gmail AI | AI agent for email auto labeling

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Cover image for 2048 | Full-stack replica in a web app

2048 | Full-stack replica in a web app

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