Amazon Relational Database Service (Amazon RDS) for Oracle now supports the Spatial Patch Bundle (SPB) for the January 2025 Release Update (RU) for Oracle Database version 19c. This update delivers important fixes for Oracle Spatial and Graph functionality, helping ensure reliable and optimal performance for your spatial operations.
You can now create new DB instances or upgrade existing ones to engine version ‘19.0.0.0.ru-2025-01.spb-1.r1’. The SPB engine version will be visible in the AWS Console by selecting the «Spatial Patch Bundle Engine Versions» checkbox in the engine version selector, making it simple to identify and implement the latest spatial patches for your database environment.
To learn more about Oracle SPBs supported on Amazon RDS for each engine version, see the Amazon RDS for Oracle Release notes. For more information about the AWS Regions where Amazon RDS for Oracle is available, see the AWS Region table.
Amazon Relational Database Service (Amazon RDS) for Oracle now supports the Spatial Patch Bundle (SPB) for the January 2025 Release Update (RU) for Oracle Database version 19c. This update delivers important fixes for Oracle Spatial and Graph functionality, helping ensure reliable and optimal performance for your spatial operations. You can now create new DB instances or upgrade existing ones to engine version ‘19.0.0.0.ru-2025-01.spb-1.r1’. The SPB engine version will be visible in the AWS Console by selecting the «Spatial Patch Bundle Engine Versions» checkbox in the engine version selector, making it simple to identify and implement the latest spatial patches for your database environment. To learn more about Oracle SPBs supported on Amazon RDS for each engine version, see the Amazon RDS for Oracle Release notes. For more information about the AWS Regions where Amazon RDS for Oracle is available, see the AWS Region table.
Amazon Bedrock Guardrails announces an increase in default service quota limits enabling you to scale your generative AI applications for higher traffic. Bedrock Guardrails provides configurable safeguards to filter undesirable and harmful content across different categories and prompt attacks, topic filters to define and disallow specific topics, sensitive information filters to redact personally identifiable information (PII), word filters to block specific words, and detect model hallucinations by detecting grounding and relevance of model responses as well as identify, correct, and explain factual claims in model responses using Automated Reasoning . These policies can be tailored to your specific use cases and responsible AI policies. Guardrails can be applied across any foundation model including those hosted with Amazon Bedrock, self-hosted models, and third-party models using the ApplyGuardrail API, providing a consistent user experience and standardizing safety and privacy controls.
Starting today, Bedrock Guardrails enables you to scale your generative AI applications for higher traffic loads with increased service quota limits that help process higher transactions per second (TPS) and higher text units per second (TUPS). With this increase, you can now process up to 50 calls per second using the ApplyGuardrail API, a 2x increase from the previous limit of 25 calls per second. Content filters, sensitive information filters, and word filters can now process up to 200 TUPS, a 8x increase from the previous limits of 25 TUPS.
These limits are available in US East (N. Virginia) and US West (Oregon) AWS regions.
Amazon Bedrock Guardrails announces an increase in default service quota limits enabling you to scale your generative AI applications for higher traffic. Bedrock Guardrails provides configurable safeguards to filter undesirable and harmful content across different categories and prompt attacks, topic filters to define and disallow specific topics, sensitive information filters to redact personally identifiable information (PII), word filters to block specific words, and detect model hallucinations by detecting grounding and relevance of model responses as well as identify, correct, and explain factual claims in model responses using Automated Reasoning . These policies can be tailored to your specific use cases and responsible AI policies. Guardrails can be applied across any foundation model including those hosted with Amazon Bedrock, self-hosted models, and third-party models using the ApplyGuardrail API, providing a consistent user experience and standardizing safety and privacy controls. Starting today, Bedrock Guardrails enables you to scale your generative AI applications for higher traffic loads with increased service quota limits that help process higher transactions per second (TPS) and higher text units per second (TUPS). With this increase, you can now process up to 50 calls per second using the ApplyGuardrail API, a 2x increase from the previous limit of 25 calls per second. Content filters, sensitive information filters, and word filters can now process up to 200 TUPS, a 8x increase from the previous limits of 25 TUPS. These limits are available in US East (N. Virginia) and US West (Oregon) AWS regions. To learn more, see the technical documentation and the Bedrock Guardrails product page.
We are excited to announce that Amazon Location Service now supports AWS PrivateLink integration, enabling customers to establish private connectivity between their VPCs and Amazon Location Service without data ever traversing the public internet.
With this new capability, customers can now access Amazon Location Service APIs through private IP addresses within their VPC, significantly enhancing their security posture. This integration simplifies network architecture by eliminating the need for internet gateways, NAT devices, or public IP addresses, while helping customers meet strict regulatory and compliance requirements by keeping all traffic within the AWS network.
Setting up AWS PrivateLink for Amazon Location Service is straightforward. Customers can create interface VPC endpoints through the AWS Management Console or AWS Command Line Interface (AWS CLI) commands. Once configured, applications can immediately begin accessing Amazon Location Service APIs using private IP addresses, with all traffic remaining secure within the AWS network.
We are excited to announce that Amazon Location Service now supports AWS PrivateLink integration, enabling customers to establish private connectivity between their VPCs and Amazon Location Service without data ever traversing the public internet. With this new capability, customers can now access Amazon Location Service APIs through private IP addresses within their VPC, significantly enhancing their security posture. This integration simplifies network architecture by eliminating the need for internet gateways, NAT devices, or public IP addresses, while helping customers meet strict regulatory and compliance requirements by keeping all traffic within the AWS network. Setting up AWS PrivateLink for Amazon Location Service is straightforward. Customers can create interface VPC endpoints through the AWS Management Console or AWS Command Line Interface (AWS CLI) commands. Once configured, applications can immediately begin accessing Amazon Location Service APIs using private IP addresses, with all traffic remaining secure within the AWS network. To learn more about using AWS PrivateLink with Amazon Location, see the Amazon Location Service developer guide.
Starting today, Amazon EC2 High Memory instances with 3TiB of memory (u-3tb1.56xlarge) is available in the Europe (Zurich) region. Customers can start using these new High Memory instances with On-Demand (OD) and Savings Plan purchase options.
Amazon EC2 High Memory instances are certified by SAP for running Business Suite on HANA, SAP S/4HANA, Data Mart Solutions on HANA, Business Warehouse on HANA, and SAP BW/4HANA in production environments. For details, see the Certified and Supported SAP HANA Hardware Directory.
For information on how to get started with your SAP HANA migration to EC2 High Memory instances, view the Migrating SAP HANA on AWS to an EC2 High Memory Instance documentation. To hear from Steven Jones, GM for SAP on AWS on what this launch means for our SAP customers, you can read his launch blog.
Starting today, Amazon EC2 High Memory instances with 3TiB of memory (u-3tb1.56xlarge) is available in the Europe (Zurich) region. Customers can start using these new High Memory instances with On-Demand (OD) and Savings Plan purchase options. Amazon EC2 High Memory instances are certified by SAP for running Business Suite on HANA, SAP S/4HANA, Data Mart Solutions on HANA, Business Warehouse on HANA, and SAP BW/4HANA in production environments. For details, see the Certified and Supported SAP HANA Hardware Directory. For information on how to get started with your SAP HANA migration to EC2 High Memory instances, view the Migrating SAP HANA on AWS to an EC2 High Memory Instance documentation. To hear from Steven Jones, GM for SAP on AWS on what this launch means for our SAP customers, you can read his launch blog.
CloudWatch Database Insights announces support of databases hosted on Amazon Relational Database Service (RDS). Database Insights is a database observability solution that provides a curated experience designed for DevOps engineers, application developers, and database administrators (DBAs) to expedite database troubleshooting and gain a holistic view into their database fleet health.
Database Insights consolidates logs and metrics from your applications, your databases, and the operating systems on which they run into a unified view in the console. Using its pre-built dashboards, recommended alarms, and automated telemetry collection, you can monitor the health of your database fleets and use a guided troubleshooting experience to drill down to individual instances for root-cause analysis. Application developers can correlate the impact of database dependencies with the performance and availability of their business-critical applications. This is because they can drill down from the context of their application performance view in Amazon CloudWatch Application Signals to the specific dependent database in Database Insights.
You can get started with Database Insights by enabling it on your RDS databases using the RDS service console, AWS APIs, and SDKs. Database Insights delivers database health monitoring aggregated at the fleet level, as well as instance-level dashboards for detailed database and SQL query analysis.
CloudWatch Database Insights announces support of databases hosted on Amazon Relational Database Service (RDS). Database Insights is a database observability solution that provides a curated experience designed for DevOps engineers, application developers, and database administrators (DBAs) to expedite database troubleshooting and gain a holistic view into their database fleet health. Database Insights consolidates logs and metrics from your applications, your databases, and the operating systems on which they run into a unified view in the console. Using its pre-built dashboards, recommended alarms, and automated telemetry collection, you can monitor the health of your database fleets and use a guided troubleshooting experience to drill down to individual instances for root-cause analysis. Application developers can correlate the impact of database dependencies with the performance and availability of their business-critical applications. This is because they can drill down from the context of their application performance view in Amazon CloudWatch Application Signals to the specific dependent database in Database Insights. You can get started with Database Insights by enabling it on your RDS databases using the RDS service console, AWS APIs, and SDKs. Database Insights delivers database health monitoring aggregated at the fleet level, as well as instance-level dashboards for detailed database and SQL query analysis. Database Insights is available in all public AWS Regions and applies a new vCPU-based pricing – see pricing page for details. For further information, visit the Database Insights documentation.
Starting today, Amazon Elastic Compute Cloud (Amazon EC2) C7gd instances with up to 3.8 TB of local NVMe-based SSD block-level storage are available in the AWS GovCloud (US-East) Region.
These Graviton3-based instances with DDR5 memory are built on the AWS Nitro System and are a great fit for applications that need access to high-speed, low latency local storage, including those that need temporary storage of data for scratch space, temporary files, and caches. They have up to 45% improved real-time NVMe storage performance than comparable Graviton2-based instances. Graviton3-based instances also use up to 60% less energy for the same performance than comparable EC2 instances, enabling you to reduce your carbon footprint in the cloud.
C7gd instances are now available in the following AWS regions: US East (N. Virginia, Ohio), US West (Oregon, N. California), Europe (Spain, Stockholm, Ireland, Frankfurt), Asia Pacific (Tokyo, Mumbai, Singapore, Sydney, Malaysia) and AWS GovCloud (US-East).
Starting today, Amazon Elastic Compute Cloud (Amazon EC2) C7gd instances with up to 3.8 TB of local NVMe-based SSD block-level storage are available in the AWS GovCloud (US-East) Region. These Graviton3-based instances with DDR5 memory are built on the AWS Nitro System and are a great fit for applications that need access to high-speed, low latency local storage, including those that need temporary storage of data for scratch space, temporary files, and caches. They have up to 45% improved real-time NVMe storage performance than comparable Graviton2-based instances. Graviton3-based instances also use up to 60% less energy for the same performance than comparable EC2 instances, enabling you to reduce your carbon footprint in the cloud. C7gd instances are now available in the following AWS regions: US East (N. Virginia, Ohio), US West (Oregon, N. California), Europe (Spain, Stockholm, Ireland, Frankfurt), Asia Pacific (Tokyo, Mumbai, Singapore, Sydney, Malaysia) and AWS GovCloud (US-East).
AWS WAF enhances Service Quotas capabilities, enabling organizations to proactively monitor and manage quotas for their cloud deployments.
AWS WAF is a web application firewall that helps protect your web applications or APIs against common web exploits and bots that may affect availability, compromise security, or consume excessive resources. By leveraging AWS Service Quotas, you can quickly understand your applied service quota values for these WAF resources and request increases when needed. This enhanced integration brings three key benefits. First, you can now monitor the current utilization of your account-level quotas for WAF resources such as web ACLs, rule groups, and IP sets in the Service Quotas console. Second, certain service quota increase requests will now be auto-approved, enabling customers to access higher quotas faster. For example, smaller increases are usually automatically approved while larger requests are submitted to AWS Support. Lastly, you can now create Amazon CloudWatch alarms to notify you when your utilization of a given quota exceeds a configurable threshold. This enables you to better adapt your utilization based on your applied quota values and automate your quota increase requests.
You can access AWS Service Quotas through the AWS console, AWS APIs, and CLI. Integration with AWS Service Quotas is available in all AWS regions where AWS WAF is offered. You can learn more about AWS WAF by visiting Developer Guide.
AWS WAF enhances Service Quotas capabilities, enabling organizations to proactively monitor and manage quotas for their cloud deployments. AWS WAF is a web application firewall that helps protect your web applications or APIs against common web exploits and bots that may affect availability, compromise security, or consume excessive resources. By leveraging AWS Service Quotas, you can quickly understand your applied service quota values for these WAF resources and request increases when needed. This enhanced integration brings three key benefits. First, you can now monitor the current utilization of your account-level quotas for WAF resources such as web ACLs, rule groups, and IP sets in the Service Quotas console. Second, certain service quota increase requests will now be auto-approved, enabling customers to access higher quotas faster. For example, smaller increases are usually automatically approved while larger requests are submitted to AWS Support. Lastly, you can now create Amazon CloudWatch alarms to notify you when your utilization of a given quota exceeds a configurable threshold. This enables you to better adapt your utilization based on your applied quota values and automate your quota increase requests. You can access AWS Service Quotas through the AWS console, AWS APIs, and CLI. Integration with AWS Service Quotas is available in all AWS regions where AWS WAF is offered. You can learn more about AWS WAF by visiting Developer Guide.
Amazon Verified Permissions now supports the same JSON format for entity and context data, as the Cedar SDK. Developers can use this simpler format for authorization requests. This aligns the Amazon Verified Permissions API more closely with the open source Cedar SDK, and simplifies moving from the SDK to Amazon Verified Permissions or vice versa.
Amazon Verified Permissions is a permissions management and fine-grained authorization service for the applications that you build. Using Cedar, an expressive and analyzable open-source policy language, developers and admins can define policy-based access controls using roles and attributes for more granular, context-aware access control. For example, an HR application might call Amazon Verified Permissions (AVP) to determine if Alice is permitted to access Bob’s performance evaluation, given that she is in the HR Managers group. Customers can use Cedar JSON format to pass entity data describing the principal (Alice) and the resource (Bob’s performance evaluation).
This change is available in all AWS regions supported by Amazon Verified Permissions. The service will continue to support the old format, and so the change does not break existing application integrations. To learn more about using the Cedar JSON format, see Cedar JSON entity in the Cedar user guide and the Verified Permissions user guide. To learn more about Amazon Verified Permissions, visit the product page. For more information visit the Verified Permissions product page.
Amazon Verified Permissions now supports the same JSON format for entity and context data, as the Cedar SDK. Developers can use this simpler format for authorization requests. This aligns the Amazon Verified Permissions API more closely with the open source Cedar SDK, and simplifies moving from the SDK to Amazon Verified Permissions or vice versa. Amazon Verified Permissions is a permissions management and fine-grained authorization service for the applications that you build. Using Cedar, an expressive and analyzable open-source policy language, developers and admins can define policy-based access controls using roles and attributes for more granular, context-aware access control. For example, an HR application might call Amazon Verified Permissions (AVP) to determine if Alice is permitted to access Bob’s performance evaluation, given that she is in the HR Managers group. Customers can use Cedar JSON format to pass entity data describing the principal (Alice) and the resource (Bob’s performance evaluation). This change is available in all AWS regions supported by Amazon Verified Permissions. The service will continue to support the old format, and so the change does not break existing application integrations. To learn more about using the Cedar JSON format, see Cedar JSON entity in the Cedar user guide and the Verified Permissions user guide. To learn more about Amazon Verified Permissions, visit the product page. For more information visit the Verified Permissions product page.
Anthropic’s Claude 3.7 Sonnet hybrid reasoning model, their most intelligent model to date, is now available in Amazon Bedrock. Claude 3.7 Sonnet represents a significant advancement in AI capabilities, offering both quick responses and extended, step-by-step thinking made visible to the user. This new model includes strong improvements in coding and brings enhanced performance across various tasks, like instruction following, math, and physics.
Claude 3.7 Sonnet introduces a unique approach to AI reasoning by integrating it seamlessly with other capabilities. Unlike traditional models that separate quick responses from those requiring deeper thought, Claude 3.7 Sonnet allows users to toggle between standard and extended thinking modes. In standard mode, it functions as an upgraded version of Claude 3.5 Sonnet. While in extended thinking mode, it employs self-reflection to achieve improved results across a wide range of tasks. Amazon Bedrock users can adjust how long the model thinks, offering a flexible trade-off between speed and answer quality. Additionally, users can control the reasoning budget by specifying a token limit, enabling more precise management of cost.
Anthropic has optimized Claude 3.7 Sonnet for real-world applications that align closely with typical language model use cases, rather than focusing solely on math and computer science competition problems. This approach ensures that the model is well-suited to address the diverse needs of customers across various industries and use cases.
Claude 3.7 Sonnet is now available in Amazon Bedrock in the US East (N. Virginia), US East (Ohio), and US West (Oregon) regions. To get started, visit the Amazon Bedrock console. Integrate it into your applications using the Amazon Bedrock API or SDK. For more information and to learn more read the AWS News Blog and Claude in Bedrock product detail page.
Anthropic’s Claude 3.7 Sonnet hybrid reasoning model, their most intelligent model to date, is now available in Amazon Bedrock. Claude 3.7 Sonnet represents a significant advancement in AI capabilities, offering both quick responses and extended, step-by-step thinking made visible to the user. This new model includes strong improvements in coding and brings enhanced performance across various tasks, like instruction following, math, and physics. Claude 3.7 Sonnet introduces a unique approach to AI reasoning by integrating it seamlessly with other capabilities. Unlike traditional models that separate quick responses from those requiring deeper thought, Claude 3.7 Sonnet allows users to toggle between standard and extended thinking modes. In standard mode, it functions as an upgraded version of Claude 3.5 Sonnet. While in extended thinking mode, it employs self-reflection to achieve improved results across a wide range of tasks. Amazon Bedrock users can adjust how long the model thinks, offering a flexible trade-off between speed and answer quality. Additionally, users can control the reasoning budget by specifying a token limit, enabling more precise management of cost. Anthropic has optimized Claude 3.7 Sonnet for real-world applications that align closely with typical language model use cases, rather than focusing solely on math and computer science competition problems. This approach ensures that the model is well-suited to address the diverse needs of customers across various industries and use cases. Claude 3.7 Sonnet is now available in Amazon Bedrock in the US East (N. Virginia), US East (Ohio), and US West (Oregon) regions. To get started, visit the Amazon Bedrock console. Integrate it into your applications using the Amazon Bedrock API or SDK. For more information and to learn more read the AWS News Blog and Claude in Bedrock product detail page.
3 formas de mejorar el acceso a la justicia a través de la modernización de los tribunales
Por: David Williams, director de seguridad pública y justicia global.
La máxima legal de que «la justicia demorada es justicia denegada» ha sido durante mucho tiempo un grito de guerra para alentar a los jueces y tribunales a operar de manera más eficiente. Si la reparación legal o la reparación justa están, en potencia disponibles para una parte lesionada, pero no se proporcionan o apoyan de inmediato, eso no es un remedio en absoluto. Hoy en día, la necesidad de sistemas judiciales accesibles y justos es al menos tan relevante como cuando William Penn lo expresó en el siglo XVII. Por fortuna, la tecnología desempeña un papel clave para ayudar a hacer realidad la visión y mejorar el acceso a la justicia.
En todo el mundo, los tribunales se enfrentan a presiones cada vez mayores que amenazan con empantanar los procesos judiciales y erosionar la confianza en el poder judicial. Los anticuados sistemas de gestión de casos, los datos críticos atascados en silos y la demanda pública de medios digitales para participar en la justicia contribuyen a la urgencia de encontrar nuevas soluciones que sean rentables y adecuadamente ciberseguras.
Los tribunales innovadores ya están ocupados en modernizar los sistemas y dar los primeros pasos con tecnologías de IA generativa. En Microsoft para la Administración Pública, ayudamos a los tribunales y a las organizaciones judiciales a mantener la confianza dentro de sus comunidades a través de soluciones que transforman las operaciones y ayudan a aumentar la equidad, la responsabilidad y la transparencia. Echemos un vistazo a algunos beneficios importantes de la modernización de los tribunales, incluida una nueva forma para que los tribunales experimenten con la innovación de la IA de manera segura y productiva.
La adopción de tecnologías en la nube suele tener un impacto casi inmediato en términos de potencia, escalabilidad y flexibilidad. La modernización de las herramientas y los sistemas puede ofrecer nuevas capacidades que ayuden a mejorar el acceso a la justicia. Entre estos:
1. Agilizar las operaciones judiciales
Los tribunales funcionan mejor con una fuerza laboral más empoderada, y la modernización permite obtener, de manera rápida, ganancias significativas en eficiencia. Por ejemplo, con la simple adopción de Microsoft 365 Copilot, el 70% de los usuarios encuestados en todos los sectores informaron ser más productivos y capaces de centrarse más en actividades de alto valor y trabajo creativo.1
Las soluciones en la nube que reúnen grandes cantidades de datos obtienen beneficios aún mayores. Los tribunales a menudo cuentan con el apoyo de sistemas heredados obsoletos que contienen datos en silos desconectados, lo que dificulta, si no imposibilita, integrarlos todos. Por ejemplo, el Tribunal Superior del Condado de Orange (OCSC, por sus siglas en inglés) administraba tres sistemas de gestión de casos dispares (que contenían más de 70 millones de archivos en papel), lo que creaba graves ineficiencias. Por lo tanto, lo integraron todo en un único almacén de datos en Microsoft Azure y se dieron cuenta de nuevos beneficios en la toma de decisiones y una mayor eficiencia operativa, además de sentar las bases para una mayor innovación.
Los sistemas de gestión de casos son transformados de manera especial por la modernización. Los tribunales se alejan de los costosos y limitados sistemas heredados hacia soluciones modernas que aceleran el procesamiento de casos, ayudan a los jueces a acceder más rápido a la información necesaria e incluso aumentan la capacidad de los casos. Los sistemas de gestión de casos basados en la nube también pueden cambiar de manera fundamental la forma en que las personas interactúan con los tribunales. Por ejemplo, el Sistema de Tribunales de Apelación de Alabama desarrolló una solución de nube híbrida que permitió a 6 mil abogados con licencia de Alabama acceder a información y presentar mociones sin necesidad de desplazarse de manera física a ninguno de sus tres tribunales.
2. Mejorar el acceso cotidiano a la justicia
La confianza en los tribunales es fundamental para la justicia, pero para muchas personas, el costo y la fricción que implican los procedimientos legales son altos y los resultados no siempre son satisfactorios. La modernización puede ayudar a aliviar la carga con nuevos servicios y capacidades que sean fáciles de usar y atraigan al público.
El acceso remoto a los procedimientos judiciales es un profundo beneficio de la modernización, ya que hace que sea más rápido, más fácil y menos costoso para las personas participar. Adoptadas de manera amplia durante la pandemia, las audiencias remotas con Microsoft Teams ahora se mejoran con funciones de IA generativa que pueden hacer cosas como generar transcripciones no oficiales o resúmenes de sesiones.
La experiencia de Teams también se puede ampliar para proporcionar servicios adicionales. Por ejemplo, el Tribunal Regional Federal de la 1.ª Región (TRF1) de Brasil mejoró el acceso al tribunal con un nuevo servicio de asistencia virtual, una plataforma de servicios en línea integrada dentro de Teams que ofrece un fácil acceso a servicios judiciales importantes para las personas de todo Brasil. También proporciona un centro de trabajo personalizado para los agentes de servicios judiciales, dándoles acceso a análisis de participación en tiempo real, notificaciones proactivas e indicadores de gobernanza del servicio.
La modernización también ayuda a las personas a navegar mejor por el sistema legal. Las herramientas digitales fáciles de usar pueden proporcionar orientación en los procesos legales, ayudar con la preparación de documentos y ayudar a encontrar recursos importantes. Los asistentes virtuales y los chatbots pueden ayudar a las personas a comprender los términos legales, acceder a la información de casos y representarse a sí mismas en litigios en áreas como el derecho de familia. También se pueden incluir capacidades de traducción y transcripción para que estos servicios sean aún más accesibles.
3. Experiencias mejoradas a través de nuevos servicios
La innovación con IA generativa y servicios avanzados en la nube aún está en evolución para los tribunales, pero los primeros beneficios nos dan una idea de qué tanto se transformarán los tribunales de manera significativa en los próximos meses y años.
Muchos de los beneficios enumerados antes se acelerarán de manera importante a medida que más tribunales inviertan en modernización. Para las personas, los portales en línea y las aplicaciones móviles habilitados para IA proporcionarán un acceso más fácil a la información del caso, explicarán las opciones y responderán preguntas sobre los procesos legales, para brindar un apoyo que incluso el personal de los tribunales no siempre puede ofrecer debido a las restricciones legales.
Para los jueces y el personal de los tribunales, la modernización promete un procesamiento más rápido de los casos, con soluciones que agilizan las tareas administrativas, reducen los retrasos causados por errores de papeleo y mejoran la presentación de documentos legales. La IA puede automatizar la extracción, categorización y organización de la información de documentos como facturas, contratos y correos electrónicos.
La IA generativa se integra cada vez más en los flujos de trabajo legales para automatizar tareas como el etiquetado y la clasificación. Esto promete avanzar en una iniciativa clave de la industria llamada SALI (Standards Advancement for the Legal Industry, en la que Microsoft participa), que crea una forma estandarizada de definir y documentar asuntos legales. Al automatizar el etiquetado y la clasificación de documentos (que por lo general se hacen a mano), la IA puede ayudar a SALI a cumplir su misión de beneficiar a los profesionales del derecho y a sus clientes, a través de fomentar la innovación y la eficiencia en los flujos de trabajo jurídicos.
Una forma de bajo riesgo de explorar la innovación de la IA en los tribunales
Es comprensible que muchos tribunales sean cautelosos a la hora de involucrar sus datos y sistemas críticos en la innovación con nuevas tecnologías como la IA. Es por eso que Microsoft respalda una nueva iniciativa importante llamada AI Sandbox, del Centro Nacional de Tribunales Estatales (NCSC, por sus siglas en inglés).
AI Sandbox ayuda a los líderes de las organizaciones judiciales a explorar la IA generativa y aprender cómo puede mejorar la productividad, la eficiencia y el servicio al ciudadano. Diseñado para satisfacer las necesidades de los tribunales en todas las geografías, AI Sandbox permite a los jueces y al personal de los tribunales experimentar con la IA generativa en un entorno de nube privada seguro basado en Azure. Admite el desarrollo de casos de uso, como la redacción de órdenes judiciales, la creación de descripciones de trabajo, el suministro de información legal y mucho más. Lo mejor de todo es que es fácil de usar a través del portal NSCS (no es necesario viajar).
Para comenzar, visiten el sitio web de NCSC AI sandbox.
Avance en su proceso de modernización
Ya sea que se trate de AI Sandbox o de la experimentación temprana con Microsoft 365 Copilot, el camino hacia la modernización es único para cada tribunal. Hay algunos elementos fundamentales que toda organización necesitará para obtener todos los beneficios de la IA:
Una plataforma en la nube como Azure ofrece escalabilidad, seguridad y cumplimiento probados.
Una plataforma de datos e inteligencia artificial como Microsoft Fabric proporciona una forma común de razonar sobre los datos.
Una plataforma de desarrollo como Azure AI Foundry les permite crear aplicaciones nativas de IA de primera clase.
Mejorar el acceso a la justicia a través de la tecnología es un camino a largo plazo, pero que genera beneficios temprano y con frecuencia. Es importante definir sus objetivos, adoptar un enfoque estratégico y elegir un socio tecnológico que los acompañe en cada paso del camino.
Conozcan más
Para ver cómo Microsoft potencia los sistemas judiciales para que sean más ágiles, seguros y accesibles para todos, vean nuestro vídeo. Para obtener más información sobre cómo podemos ayudarlos en el proceso de modernización de su tribunal, visiten nuestro sitio web o pónganse en contacto con su representante de ventas o socio tecnológico de Microsoft.
