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03, 2026","image":{"id":"image-bfb3514e26","src":"https://www.snowflake.com/adobe/dynamicmedia/deliver/dm-aid--b384bf8b-6fb8-4ea1-9c2e-a64ff32c7acf/build-london-blog-rollup3-ai-1680x720.png?quality=85&preferwebp=true","lazyEnabled":true,"height":"720","width":"1680",":type":"snowflake-site/components/image"},"authors":[{"authorImage":{"id":"image-e71efd75ac","src":"https://www.snowflake.com/adobe/dynamicmedia/deliver/dm-aid--8049a19c-6f69-400d-9f50-c2ee72ba1d88/arun-agarwal.jpg?quality=85&preferwebp=true","alt":"Arun Agarwal","lazyEnabled":true,"height":"653","width":"720",":type":"snowflake-site/components/image"},"authorCta":{"id":"button-deea156628","showOutboundIcon":false,"buttonLink":{"valid":true,"url":"/en/blog/authors/arun-agarwal/"},"linkTargetContentType":"DOCUMENT_LEARN","linkType":"SNOWFLAKE_INTERNAL",":type":"snowflake-site/components/button","text":"Arun Agarwal"}},{"authorImage":{"id":"image-5d24bb7156","src":"https://www.snowflake.com/adobe/dynamicmedia/deliver/dm-aid--3355b0f8-99db-4491-a7ae-7d4dc6d36aa8/official-baris-headshot-cropped-snowflake-wall-2.png?quality=85&preferwebp=true","alt":"Baris Gultekin","lazyEnabled":true,"height":"288","width":"288",":type":"snowflake-site/components/image"},"authorCta":{"id":"button-84efbbcac9","showOutboundIcon":false,"buttonLink":{"valid":true,"url":"/en/blog/authors/baris-gultekin/"},"linkTargetContentType":"DOCUMENT_LEARN","linkType":"SNOWFLAKE_INTERNAL",":type":"snowflake-site/components/button","text":"Baris Gultekin"}},{"authorImage":{"id":"image-e703946681","src":"https://www.snowflake.com/adobe/dynamicmedia/deliver/dm-aid--324f6b3f-a7d1-47b3-bf63-04a6db8f22ac/santiago-giraldo.jpg?quality=85&preferwebp=true","alt":"Headshot style photo of Santiago Giraldo of Snowflake","lazyEnabled":true,"height":"200","width":"200",":type":"snowflake-site/components/image"},"authorCta":{"id":"button-92b993343c","showOutboundIcon":false,"buttonLink":{"valid":true,"url":"/en/blog/authors/santiago-giraldo/"},"linkTargetContentType":"DOCUMENT_LEARN","linkType":"SNOWFLAKE_INTERNAL",":type":"snowflake-site/components/button","text":"Santiago Giraldo"}}],"tag":{"tagText":"Produto e tecnologia","tagColor":"#3F808A"},"title":{"lines":["Transformando a inovação em IA em aplicações confiáveis e prontas para produção com o Snowflake"],"type":"heading2",":type":"snowflake-site/components/title-v2"},":type":"snowflake-site/components/blog/blog-hero"}},":itemsOrder":["blog_hero"]},"responsivegrid_content":{"columnClassNames":{"blog_text":"aem-GridColumn aem-GridColumn--default--12","blog_premium_content":"aem-GridColumn aem-GridColumn--default--12"},"gridClassNames":"aem-Grid aem-Grid--12 aem-Grid--default--12","columnCount":12,"appliedCssClassNames":"snowflake-layout-container-inner-padding-small",":items":{"blog_text":{"id":"blog-text-713370e834","text":"\u003Cp\u003EAs inovações em IA continuam a transformar aplicações e experiências em todos os setores e empresas. O foco das empresas tem sido cada vez mais produzir resultados mensuráveis para seus usuários finais. Para alcançar esses resultados, é preciso contar com uma IA com escala ajustável, segura e fortemente conectada aos dados corporativos.\u003C/p\u003E\r\n\u003Cp\u003ENa Snowflake, estamos empenhados em ajudar os clientes a transformar essas expectativas em relação à \u003Ca href=\"https://www.snowflake.com/en/product/ai/\" target=\"_blank\" rel=\"nofollow noopener noreferrer\"\u003Einteligência artificial (IA)\u003C/a\u003E e ao \u003Ca href=\"http://www.snowflake.com/ml\" target=\"_blank\" rel=\"nofollow noopener noreferrer\"\u003Eaprendizado de máquina (machine learning, ML)\u003C/a\u003E em um resultado concreto. Isso significa colocar os desenvolvedores em posição de liderança com ferramentas que facilitam a criação de agentes confiáveis, agilizam as cargas de trabalho de IA/ML em produção e controlam essas cargas de forma confiante à medida que há uma ajuste de escala.\u003C/p\u003E\r\n\u003Cp\u003ENossas inovações mais recentes de produtos têm capacitado os clientes a criar aplicações confiáveis e de nível empresarial com o Snowflake. O resultado é uma performance mais rápida, operações mais fáceis e ferramentas de IA em que as empresas podem implementar com confiança em produção.\u003C/p\u003E\r\n\u003Ch2\u003ESnowflake Intelligence como um agente de inteligência empresarial, prontamente disponível\u003C/h2\u003E\r\n\u003Cp\u003EO Snowflake Intelligence reúne um conjunto de recursos desenvolvidos para ajudar os usuários empresariais a obter valor da IA de forma rápida, segura e independente. Essas atualizações se concentram em três necessidades principais:\u003C/p\u003E\r\n\u003Cul\u003E\r\n\u003Cli\u003EPossibilitar que os usuários obtenham resultados valiosos a partir de conversas como artefatos e compartilhem esses artefatos com outros stakeholders para tomar decisões de negócios (em breve).\u003C/li\u003E\r\n\u003Cli\u003EAtender às necessidades dos usuários empresariais onde quer que eles estejam no processo, com acesso seguro e nativo a dispositivos móveis (em breve).\u003C/li\u003E\r\n\u003Cli\u003EAgora, os clientes podem trazer usuários empresariais para o Snowflake Intelligence, mantendo as ferramentas de SQL e de dados fora dos limites. Todas as políticas de segurança existentes são aplicáveis e os administradores utilizam tudo isso com uma única propriedade de usuário.\u003C/li\u003E\r\n\u003C/ul\u003E\r\n\u003Cp\u003EO \u003Ca href=\"https://www.snowflake.com/en/product/snowflake-intelligence/\" target=\"_blank\" rel=\"nofollow noopener noreferrer\"\u003ESnowflake Intelligence\u003C/a\u003E foi projetado para fornecer insights confiáveis onde quer que o trabalho ocorra. Sua interface de linguagem natural permite que todos os funcionários façam perguntas, descubram o "porquê" por trás do "o quê", possibilitando ações no tempo certo e baseadas em dados, tudo na plataforma Snowflake, segura e governada.\u003C/p\u003E\r\n\u003Cp\u003EJuntos, esses recursos tornam o Snowflake Intelligence um agente de inteligência empresarial confiável capaz de fornecer insights quando e onde os usuários precisam deles, apoiando o processo decisório no tempo certo e baseado em dados por toda a organização.\u003C/p\u003E\r\n\u003Ch3\u003EArtifacts: transformando conversas em resultados de negócios\u003C/h3\u003E\r\n\u003Cp\u003E\u003Cb\u003EArtifacts (em breve, em versão preliminar pública)\u003C/b\u003E representa uma mudança fundamental na forma como o Snowflake Intelligence oferece suporte aos usuários empresariais. Artifacts transformará as conversas do Snowflake Intelligence em resultados armazenáveis e compartilháveis, como tabelas e gráficos que preservam a visualização, SQL subjacente e metadados contextuais.\u003C/p\u003E\r\n\u003Cp\u003EOs artefatos são as unidades centrais através das quais o conhecimento corporativo é capturado, compartilhado e utilizado no Snowflake Intelligence. Os usuários podem salvar artefatos para evitar recriar análises, compartilhar referências ao vivo com segurança com colegas de equipe e explorar questões subsequentes sobre o contexto. Os artefatos vão permitir que os usuários retornem ao que já criaram, compartilhem com outras pessoas e colaborem diretamente com base em dados corporativos confiáveis.\u003C/p\u003E\r\n\u003Cp\u003EDe forma mais ampla, os artefatos são a base para a capacidade do Snowflake Intelligence de fornecer insights de negócios aos usuários finais. Em vez de usar o Snowflake Intelligence principalmente para questões isoladas ou de acompanhamento, os artefatos ajudam a torná-lo o ponto de partida para conduzir os negócios. Com os artefatos, estamos tornando o Snowflake Intelligence o destino para tomada de decisão consistente e confiável de uma única fonte para toda a organização.\u003C/p\u003E\r\n\u003Ch3\u003ESnowflake Intelligence: em breve disponível para dispositivos móveis\u003C/h3\u003E\r\n\u003Cp\u003EEm breve, o Snowflake Intelligence estará \u003Cb\u003Edisponível como um app móvel para iOS (breve em versão preliminar pública)\u003C/b\u003E, oferecendo uma melhor experiência para dispositivos móveis nativos. O acesso à plataforma móvel garante que os líderes e usuários empresariais possam permanecer conectados ao seu conhecimento corporativo durante todo o dia, estejam eles analisando métricas importantes, monitorando tendências ou acompanhando questões importantes, conforme as decisões se desenvolvem.\u003C/p\u003E\r\n\u003Cp\u003EPara uma experiência segura e fácil de usar, o Snowflake Intelligence oferecerá suporte à \u003Cb\u003Erenovação de sessão baseada em FaceID no app móvel (breve em versão preliminar pública).\u003C/b\u003E Os usuários poderão fazer a autenticação usando o FaceID, e os tokens serão atualizados automaticamente em segundo plano. Os tokens de atualização permanecem protegidos, vinculados a dispositivos e rotacionados regularmente, possibilitando controles de segurança de nível empresarial e, ao mesmo tempo, oferecendo uma experiência móvel contínua e em estilo de consumidor.\u003C/p\u003E\r\n\u003Ch3\u003EAmpliando o acesso com login restrito e usuários "Snowflake Intelligence-only"\u003C/h3\u003E\r\n\u003Cp\u003EO Snowflake Intelligence agora oferece suporte ao login direto do usuário, para que usuários empresariais possam fazer login e fazer perguntas sem precisar conhecer o Snowflake ou navegar pelo Snowsight.\u003C/p\u003E\r\n\u003Cp\u003EPara os clientes que desejam um controle mais rigoroso, há a opção de usuários com acesso apenas ao Snowflake Intelligence, dando aos usuários empresariais acesso ao Snowflake Intelligence e nada mais. Eles não podem acessar o Snowsight, as interfaces SQL ou outras ferramentas de dados. Isso mantém os usuários empresariais em uma interface criada para eles e, ao mesmo tempo, ajuda as organizações a controlar o uso, controlar os custos e a implementar todas as políticas de segurança existentes de forma automática.\u003C/p\u003E\r\n\u003Cp\u003EO Snowflake Intelligence também oferece suporte ao redirecionamento do provedor de identidade, para que os usuários que se autenticam por meio de uma IdP configurada (por exemplo, Okta ou Entra ID) tenham uma experiência simplificada de login no Snowflake Intelligence. Juntos, esses recursos facilitam a ampliação do acesso por toda a organização, mantendo os controles de governança centralizados.\u003C/p\u003E\r\n\u003Ch2\u003ECrie, implemente e reitere a experiência com agentes, de modo fácil\u003C/h2\u003E\r\n\u003Cp\u003EHoje em dia, os agentes de IA são fundamentais para os fluxos de trabalho de negócios. As empresas precisam de um stack de dados seguro e confiável para oferecer experiências consistentes e precisas em um ambiente governado, cuja escala possa ser ajustada entre equipes e aplicações. Ficamos felizes de compartilhar as principais novidades do Snowflake que ajudam os clientes a criar e ajustar a escala dos agentes no nível da produção com confiança.\u003C/p\u003E\r\n\u003Cp\u003E\u003Cb\u003ECortex Code (agora disponível ao público)\u003C/b\u003E: apoia essa jornada, permitindo que todos os desenvolvedores, desde engenheiros experientes até equipes não técnicas, criem e otimizem agentes usando interações em linguagem natural. Com facilidade, ele ajuda as equipes a gerar dados sintéticos, criar e depurar visualizações semânticas e a criar e depurar rapidamente o comportamento do agente, agilizando o tempo de produção no Snowflake AI Data Cloud. \u003C/p\u003E\r\n\u003Cp\u003E\u003Cb\u003ESemantic View Autopilot (em breve, disponível ao público)\u003C/b\u003E: com ele, as equipes podem criar e implementar automaticamente visualizações semânticas prontas para produção. Ao aprender com o histórico de consultas, o Semantic View Autopilot simplifica os fluxos de trabalho de modelagem e ajuda as organizações a integrar com mais rapidez novos casos de uso, ao mesmo tempo que fornece insights consistentes às equipes.\u003C/p\u003E\r\n\u003Cp\u003EPara ampliar a adoção de agentes em toda a organização, o \u003Cb\u003ECortex Agent Sharing (em breve, disponível ao público)\u003C/b\u003E facilita a descoberta, a reutilização e a operacionalização de agentes criados por equipes ou parceiros internos. Ele permite que as organizações padronizem os recursos de agentes, evitem a duplicação de esforços e ajustem a escala dos agentes testados entre as equipes, em vez de reconstruí-los para cada caso de uso. As equipes podem acessar as ofertas do Snowflake Marketplace e usar os agentes criados por parceiros para acelerar o tempo de retorno.\u003C/p\u003E\r\n\u003Cp\u003E\u003Cb\u003EAgent Evaluations (em breve disponível ao público)\u003C/b\u003E: com ele, os clientes conseguem uma visibilidade mais detalhada de como os agentes raciocinam, selecionam ferramentas e geram respostas. Dessa forma, é possível refinar o comportamento dos agentes e melhorar continuamente a precisão à medida que eles evoluem. Essa transparência ajuda as equipes a desenvolver confiança na qualidade do agente, validando facilmente a precisão e a consistência lógica para garantir que estejam prontos para cargas de trabalho de produção. Ao fornecer visibilidade total do "processo de raciocínio" de um agente, o Agent Evaluations reduz o trabalho de depuração, permitindo que as equipes identifiquem e corrijam instantaneamente erros ou gargalos de performance. Por fim, validando as respostas, a lógica e o uso das ferramentas, as organizações podem avançar confiando nos agentes desde as etapas iniciais de testes até os sistemas prontos para produção, contando com a confiança das equipes.\u003C/p\u003E\r\n\u003Ch2\u003EModel Context Protocol para acesso a dados corporativos\u003C/h2\u003E\r\n\u003Cp\u003EO Snowflake Intelligence oferece suporte ao protocolo de contexto modelo (model context protocol, MCP) para simplificar a integração com ferramentas e serviços de terceiros. Lançamos um \u003Ca href=\"https://www.snowflake.com/en/blog/managed-mcp-servers-secure-data-agents/\" target=\"_blank\" rel=\"nofollow noopener noreferrer\"\u003Eservidor MCP gerenciado pela Snowflake em outubro de 2025\u003C/a\u003E e agora estamos adicionando um \u003Cb\u003ESnowflake MCP Client (em breve, disponível ao público)\u003C/b\u003E para que os clientes possam se conectar com facilidade e confiança a fontes externas de dados.\u003C/p\u003E\r\n\u003Cp\u003ECom o Snowflake MCP Client, os administradores de contas podem registrar servidores MCP pré-criados ou personalizados, como Atlassian, Salesforce ou Workday, e transferir diretamente para os Cortex Agents. Os desenvolvedores podem usar servidores MCP com agentes, possibilitando a pesquisa e o uso contínuo das ferramentas durante a orquestração. O Snowflake gerencia a autenticação, incluindo o gerenciamento de tokens, e fornece observabilidade para manter as integrações seguras e governadas. Durante o lançamento, o Snowflake oferece suporte à descoberta completa de ferramentas de MCP durante o oso de agente, além de monitoramento e gerenciamento de tokens, permitindo que os clientes acessem e utilizem com segurança os dados corporativos de todos os sistemas.\u003C/p\u003E\r\n\u003Ch2\u003EAlta qualidade e baixa latência para agentes de nível empresarial\u003C/h2\u003E\r\n\u003Cp\u003EEm ambientes de produção, consistência e precisão desempenham um papel fundamental para a experiência e a adoção por parte do usuário. A Snowflake continua a investir em todo o stack de agentes para oferecer experiências com tecnologia de IA mais rápidas, precisas e previsíveis em escala.\u003C/p\u003E\r\n\u003Cp\u003EA Snowflake vai lançar o \u003Cb\u003EContinuously Learning Agent Memory (breve em versão preliminar pública)\u003C/b\u003E, uma grande melhoria de qualidade para agentes de inteligência empresarial. Com esse recurso, os agentes poderão aprender continuamente com as respostas anteriores de alta qualidade entre usuários, melhorando a consistência e a confiança. Isso também permitirá que os agentes se lembrem das preferências e dos fatos individuais do usuário ao longo do tempo, oferecendo experiências mais personalizadas do Snowflake Intelligence.\u003C/p\u003E\r\n\u003Cp\u003EAo integrar o uso in-line de text-to-SQL à orquestração de agente, o Snowflake também melhorou a precisão e reduziu a latência dos fluxos de trabalho analíticos. Os usuários podem acessar dados com mais rapidez, visualizar o planejamento do LLM juntamente com a execução do SQL e refinar o comportamento do agente em uma ampla variedade de cargas de trabalho.\u003C/p\u003E\r\n\u003Ch2\u003EGovernança com controle de versão do agente e controle de custos\u003C/h2\u003E\r\n\u003Cp\u003EConforme as aplicações de IA se desenvolvem, as empresas precisam de recursos de governança para se expandirem. O Snowflake realiza esse trabalho por meio do controle de versão do agente e da visibilidade operacional integrada.\u003C/p\u003E\r\n\u003Cp\u003E\u003Cb\u003EO Agent Versioning (breve em versão preliminar pública)\u003C/b\u003E traz suporte CI/CD para o Snowflake Cortex Agents, para que os clientes possam criar, implementar e iterar cargas de trabalho com agentes, de modo confiável. Os desenvolvedores podem fazer snapshots de versões, gerenciar alterações por meio do Git e promover ou reverter implementações com segurança. Além disso, os clientes podem monitorar o uso no Snowflake Intelligence e em agentes por meio de \u003Cb\u003Evisualizações de uso (em breve, disponíveis ao público)\u003C/b\u003E, possibilitando uma melhor supervisão operacional.\u003C/p\u003E\r\n\u003Cp\u003EAlém da visibilidade, o Snowflake permite às equipes controlar ativamente os custos de IA. \u003Cb\u003EO AI_COUNT_TOKENS (disponível ao público)\u003C/b\u003E ajuda a estimar o uso antes da execução, enquanto o \u003Cb\u003EAI Functions Incremental Metering View (em breve disponível ao público)\u003C/b\u003E fornecerá dados de uso e custo de consultas em execução, permitindo que as equipes implementem limites e ativem ações durante o tempo de execução. Isso permite que as organizações ajustem a escala da IA em produção, mantendo os custos previsíveis e o controle operacional.\u003C/p\u003E\r\n\u003Cp\u003EJunto com controles de versão e de custos, as equipes podem agir rapidamente, mantendo a clareza e ajustando a escala das aplicações de alta performance de forma responsável.\u003C/p\u003E\r\n\u003Ch2\u003EAgilize a produção de modelos de ML multimodais online com fluxos de trabalho com agentes\u003C/h2\u003E\r\n\u003Cp\u003ENo cenário atual de IA, o aprendizado de máquina (ML) tradicional continua sendo indispensável. Por isso, estamos felizes de anunciar novos recursos para fluxos de trabalho com agentes, multimodais e em tempo real no \u003Ca href=\"https://www.snowflake.com/pt_br/product/features/end-to-end-ml-workflows/\" target=\"_blank\" rel=\"nofollow noopener noreferrer\"\u003ESnowflake ML\u003C/a\u003E. \u003C/p\u003E\r\n\u003Cp\u003EContinuamos a investir em experiências modernas de desenvolvimento capazes de aumentar a produtividade. A próxima geração do \u003Cb\u003E\u003Ca href=\"https://www.snowflake.com/pt_br/product/features/notebooks/\" target=\"_blank\" rel=\"nofollow noopener noreferrer\"\u003ESnowflake Notebooks\u003C/a\u003E (disponíveis ao público)\u003C/b\u003E agora são componentes de primeira classe dentro dos Snowflake Workspaces, executados em um ambiente baseado em Jupyter com tecnologia do Snowflake Container Runtime. Com o Snowflake Notebooks, os desenvolvedores podem integrar notebooks, scripts e treinamento de modelos existentes baseados em Jupyter à plataforma unificada do Snowflake a fluxos de trabalho avançados de desenvolvimento de modelos. O poder do Snowflake Notebooks para desenvolvimento e iteração mais avançados está agora melhor com a integração com o \u003Cb\u003E\u003Ca href=\"https://docs.snowflake.com/cortex-code\" target=\"_blank\" rel=\"nofollow noopener noreferrer\"\u003ECortex Code no Snowsight\u003C/a\u003E (em breve, disponível ao público).\u003C/b\u003E\u003C/p\u003E\r\n\u003Cp\u003EMuitas vezes, os cientistas de dados passam longos ciclos desenvolvendo e resolvendo problemas em seus fluxos de trabalho de ML, o que gera gargalos operacionais e menos modelos de ML chegando à produção. Agora, a Snowflake está trazendo fluxos de trabalho de IA com agentes para ML com a integração dos fluxos de trabalho do Cortex Code for ML no Snowflake Notebooks para a iteração, o ajuste e a geração autônomos de um pipeline de ML totalmente executável a partir de solicitações em simples linguagem natural. \u003C/p\u003E\r\n\u003Cp\u003EModelos de ML em tempo real podem ser facilmente produzidos no Snowflake ML com \u003Ca href=\"https://docs.snowflake.com/developer-guide/snowflake-ml/feature-store/create-and-serve-online-features-python\" target=\"_blank\" rel=\"nofollow noopener noreferrer\"\u003Estore de recursos on-line\u003C/a\u003E e \u003Ca href=\"https://docs.snowflake.com/en/developer-guide/snowflake-ml/model-registry/container\" target=\"_blank\" rel=\"nofollow noopener noreferrer\"\u003Eatendimento de modelo on-line\u003C/a\u003E, ambos em disponibilidade geral. Agora, os desenvolvedores podem disponibilizar recursos em menos de 30 ms e modelos em menos de 100 ms para viabilizar casos de uso on-line de baixa latência, como recomendações personalizadas e detecção de fraudes. Sem precisar de infraestrutura adicional ou configuração complicada. Além disso, a capacidade de executar inferência em grande escala com modelos multimodais de hubs, como Hugging Face, agora está em versão preliminar pública. A inferência com dados não estruturados, como imagens e vídeo, desbloqueia casos de uso de IA, como detecção de objetos, perguntas e respostas visuais e reconhecimento automático de voz no Snowflake, sem pipelines complexos ou movimentação de dados.\u003C/p\u003E\r\n\u003Ch2\u003EO futuro do desenvolvimento da IA\u003C/h2\u003E\r\n\u003Cp\u003EOs atuais lançamentos ajudam a estabelecer o Cortex Agents como a base unificada da IA de nível empresarial.  O Semantic View Autopilot ajuda os desenvolvedores a aumentar a precisão do Cortex Agent e acelera a implementação de casos de uso avançados.  As melhorias mais recentes do \u003Ca href=\"https://www.snowflake.com/en/blog/production-ml-workflows/\" target=\"_blank\" rel=\"nofollow noopener noreferrer\"\u003ESnowflake ML\u003C/a\u003E permitem que os desenvolvedores criem modelos que os Cortex Agents podem usar para fornecer diretamente previsões e recomendações baseadas em ML aos usuários.  E durante a produção, nossas avaliações para Cortex Agents garantem que os resultados de agentes sejam confiáveis e fáceis de monitorar.\u003C/p\u003E\r\n\u003Cp\u003ECom o Snowflake, as empresas passam da fase de testes para a produção com agentes e aplicações de IA que as equipes podem confiar, gerenciados por operadores, capazes de trazer resultados diretos para os negócios.\u003C/p\u003E\r\n\u003Ch2\u003EEntão, por onde começar\u003C/h2\u003E\r\n\u003Cp\u003E1. Comece a criar, salvar e compartilhar artefatos no \u003Ca href=\"https://www.snowflake.com/pt_br/product/snowflake-intelligence/\" target=\"_blank\" rel=\"nofollow noopener noreferrer\"\u003ESnowflake Intelligence para promover a colaboração e a ação\u003C/a\u003E.\u003C/p\u003E\r\n\u003Cp\u003E2. Confira o \u003Ca rel=\"nofollow noopener noreferrer\" href=\"https://www.snowflake.com/en/news/\" target=\"_blank\"\u003Elançamento do Cortex Code\u003C/a\u003E.\u003C/p\u003E\r\n\u003Cp\u003E3. 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