BotCity

🚀 We’re hiring: Finance Manager - FP&A | BotCity BotCity, a governance platform for Python and AI automation, is looking for a leader to head its finance function during a period of rapid growth (US$ 12M Series A, 1,000+ customers across 70+ countries). 📌 Profile we’re looking for: - 4+ years of experience in accounting and treasury (accounts payable/receivable, financial close) - Audit experience (Big 4 or equivalent) - Knowledge of IFRS/GAAP - Experience in high-growth startups - Analytical mindset, focused on automation and process improvement - Advanced English and fluent Portuguese 🌎 100% remote | Distributed team across the US and LATAM If this sounds like you, check out the full job description and apply! 👇 https://hubs.la/Q04pF7KL0 #JobOpening #FP&A #RemoteWork #Finance #BotCity

🚀 BotCity is hiring! We are expanding our team and opening up several opportunities for those who want to build the future of Python governance and AI agents with us. Check out the open roles: - Account Executive (multiple positions) - Mid-level UX Designer - QA Lead - Product Owner - Senior Java Backend Developer (multiple positions) - Frontend Engineer - Specialist Java Backend Developer (multiple positions) - Controller & FP&A - Python Developer Interested in a role? Apply here: https://hubs.la/Q04p9v9N0 Check out all open positions on our careers page! 👊 #BotCity #JobOpenings #Hiring #Careers #Technology

Your team is delivering AI at record speed. 🚀 But every new deployment creates another blind spot in your observability stack. Undocumented Python runtime environments. Active dependencies that exist only in someone's head. Production versions changing faster than the team can track. The result? Hours of engineering time spent trying to answer questions that should be answered automatically. You can't scale AI in the enterprise without full visibility into what is running, where, and how. That is exactly the problem Sentinel solves: automatic runtime mapping, without requiring any changes to your code. Find out how BotCity Sentinel delivers automatic observability for production environments: https://bit.ly/4p4NhMO [PT/BR] Sua equipe está entregando IA em velocidade recorde. 🚀 Mas cada deploy novo é mais um ponto cego na sua stack de observabilidade. Ambientes de execução Python que ninguém documentou. Dependências ativas que só alguém "sabe de cabeça". Versões em produção que mudam mais rápido do que a equipe consegue rastrear. O resultado? Horas de engenharia gastas tentando responder perguntas que deveriam ser automáticas. Não dá pra escalar IA no enterprise sem visibilidade total sobre o que está rodando, onde e como. É exatamente esse o problema que o Sentinel resolve: mapeamento automático de runtime, sem exigir nenhuma mudança no seu código. Saiba como a BotCity Sentinel oferece observabilidade automática para ambientes de produção: https://bit.ly/4vCSca0

Why are you paying agent licenses to run Python? The usual answer: "I need governance!", but... But here is the problem: you are using a governance platform that was not designed for Python. Python usage skyrocketed as it became the most popular programming language, making it the first choice for AI to generate automation scripts. Low-code automation platforms started supporting Python because users kept requesting the feature. As Python became powerful and easy to code with AI support, it is now common to find processes whose entire logic sits inside Python scripts, with low-code used only to invoke them. But: - Instead of running Python natively, it is invoked inside a proprietary execution agent. - Instead of running dozens of Python scripts simultaneously, you are restricted by the number of execution licenses. - Instead of a solid CI/CD pipeline for security and deployment, Python is linked in a low-code XML artifact. - Instead of market-standard virtual environment management, you run into environment problems in many situations. --- Try a governance platform designed for Python automation, and get both governance and the freedom of Python.

🚨 8 out of 10 leaders in Brazil fear the use of unauthorized AI within their companies. This is known as "Shadow AI": employees using AI tools without IT's knowledge, not out of malice, but for the sake of efficiency. Some eye-opening figures: 📊 75% of professionals already use AI at work 📊 66% of Brazilian companies admit to the frequent use of Shadow AI 📊 70% doubt their own ability to protect data The biggest risk? Pasting code or a strategy into a public chatbot could mean training a competitor's model. Blocking doesn't work. The solution is active governance: visibility, monitoring, and clear policies, without stifling innovation 🔗 Read the full article on the BotCity blog: https://lnkd.in/ex_riHw2 [PT/BR] 🚨 8 em cada 10 líderes no Brasil temem o uso de IA não autorizada nas suas empresas. O nome disso é Shadow AI: colaboradores usando ferramentas de IA sem o conhecimento da TI, não por má-fé, mas por eficiência. Alguns números que chamam atenção: 📊 75% dos profissionais já usam IA no trabalho 📊 66% das empresas brasileiras admitem uso frequente de Shadow AI 📊 70% desconfiam da própria capacidade de proteger os dados O risco maior? Colar um código ou uma estratégia num chatbot público pode significar treinar o modelo do concorrente. Bloquear não funciona. A saída é governança ativa: visibilidade, monitoramento e políticas claras, sem travar a inovação. Leia o artigo completo no Blog! #AIGovernance #ShadowAI #Cybersecurity #LGPD #AI

A inteligência artificial generativa criou um problema novo nas empresas: qualquer profissional, com ou sem formação técnica, passou a gerar código Python automaticamente ao usar ferramentas como ChatGPT e Copilot. Sem governança, esse código roda sem controle nas redes corporativas. É esse problema que a BotCity, de Campinas, tenta resolver. A empresa captou R$ 65 milhões em rodada Série A liderada pelo fundo norte-americano Four Rivers, com participação de Y Combinator e Astella, e lançou o Sentinel, camada instalada nas máquinas dos usuários capaz de identificar o que é executado e reportar ao time de TI se aquele processo está dentro dos limites de segurança da companhia. Confira mais no link: https://lnkd.in/dmNKaNpS

The speed at which business units adopt new technologies often outpaces traditional reporting structures. Scaling effectively means turning this decentralized agility into a visible, measurable capability. Monitor the real execution of your portfolio without implementing bureaucratic hurdles that drag down the business. Learn how BotCity provides active governance for the AI era: https://bit.ly/4eVQERg [PT/BR] A velocidade com que as unidades de negócio adotam novas tecnologias frequentemente supera as estruturas tradicionais de reporte. Escalar com eficiência significa transformar essa agilidade descentralizada em uma capacidade visível e mensurável. Monitore a execução real do seu portfólio sem implementar barreiras burocráticas que freiam o negócio. Saiba como a BotCity oferece governança ativa para a era da IA: https://bit.ly/4whpZW5

88% of companies already use AI. Only 8% have governance in place for it. This gap explains why 2026 has become the year of AI governance in organizations. The risk lies not only in "official" models but also in the scripts and automations created by any employee using AI—running on corporate endpoints without approval, auditing, or visibility. Key highlights from the article: - Data governance ≠ AI governance - 4 essential pillars: models, data, access, and execution - Execution is the most neglected pillar and the one where risk is growing fastest - Regulations (EU AI Act, LGPD, AI Legal Framework) already require concrete evidence, not just policies on paper Essential reading for leaders in technology, security, or compliance. Read the full article: https://bit.ly/4vD8Aat #AIGovernance #Compliance #InformationSecurity [PT/BR] 88% das empresas já usam IA. Só 8% têm governança para isso. Esse gap explica por que 2026 virou o ano da governança de IA nas organizações. O risco não está só nos modelos "oficiais". Está nos scripts e automações que qualquer colaborador cria com IA, rodando em endpoints corporativos sem aprovação, auditoria ou visibilidade. Alguns destaques do artigo: - Governança de dados ≠ governança de IA - 4 pilares essenciais: modelos, dados, acesso e execução - Execução é o pilar mais negligenciado e o que mais cresce em risco - Regulação (EU AI Act, LGPD, Marco Legal da IA) já exige evidências concretas, não só política no papel Leitura essencial para quem lidera tecnologia, segurança ou compliance. Leia o artigo completo. #GovernançaDeIA #AIGovernance #Compliance #SegurançaDaInformação

88% of organizations now run AI regularly in at least one function. The more your teams use AI, the more Python runs in your operation. And the harder it gets to see what those scripts are actually doing. Every LLM ships Python by default. Python adoption jumped from 22% to 27% on the TIOBE index in months. Same trend, seen from two angles. At Infosecurity Europe, this was the conversation. Nearly every CISO meeting came back to the same question: who is auditing the Python that AI keeps generating on our endpoints?  #InfosecurityEurope #ShadowPython #CISO #CyberSecurity #PythonGovernance #EndpointSecurity

Three days at Infosecurity Europe. Hundreds of conversations.  One pattern came up in nearly every one of them: companies are not asking how to stop AI. They are asking how to see what AI is already running on their endpoints. The question moved from "should we allow Python" to "we already have it, in volume, and we have no script-level view of what it actually does." Thanks to everyone who stopped by Booth B65. If you missed us in London, the Shadow Python Risk Assessment is still open.  #BotCity #CyberSecurity #AIGovernance #PythonSecurity #AI