Best AI Governance Tools for Mid Size Business

Vertex AI provides a framework for AI governance that prioritizes responsible, ethical development, deployment, and management of machine learning models while adhering to industry standards. The platform equips users with various tools for monitoring, auditing, and regulating model performance throughout the entire AI lifecycle, fostering transparency and accountability. Adopting effective AI governance strategies is crucial for reducing risks related to biases, fairness, and security in AI systems. New users can take advantage of $300 in complimentary credits to explore the governance features within Vertex AI and establish strong governance structures for their AI initiatives. With ongoing monitoring and thorough controls in place, organizations can ensure they remain compliant with regulations and build trust in their AI solutions.

Dataiku serves as a sophisticated platform for data science and machine learning, aimed at facilitating teams in the construction, deployment, and management of AI and analytics projects on a large scale. It enables a diverse range of users, including data scientists and business analysts, to work together in developing data pipelines, crafting machine learning models, and preparing data through various visual and coding interfaces. Supporting the complete AI lifecycle, Dataiku provides essential tools for data preparation, model training, deployment, and ongoing monitoring of projects. Additionally, the platform incorporates integrations that enhance its capabilities, such as generative AI, thereby allowing organizations to innovate and implement AI solutions across various sectors. This adaptability positions Dataiku as a valuable asset for teams looking to harness the power of AI effectively.

Transparency, choice and control are key to trust. Organizations have the opportunity to leverage these moments to build trust, and provide more valuable experiences. People expect greater control over their data. We offer privacy and data governance automation to help organizations better understand and comply with regulatory requirements. We also operationalize risk mitigation to ensure transparency and choice for individuals. Your organization will be able to achieve data privacy compliance quicker and build trust. Our platform helps to break down silos between processes, workflows, teams, and people to operationalize regulatory compliance. It also allows for trusted data use. Building proactive privacy programs that are rooted in global best practice and not just reacting to individual regulations is possible. To drive mitigation and risk-based decision-making, gain visibility into unknown risks. Respect individual choice and integrate privacy and security by default in the data lifecycle.

We are builders on a mission. We're obsessed with building products that make the world a more secure place. Over the course of our careers we've built countless enterprise products at both startups and companies like Splunk, Cisco, Symantec, and McAfee. In every case we had to write security features from scratch. Pangea offers the first Security Platform as a Service (SPaaS) which unifies the fragmented world of security into a simple set of APIs for developers to call directly into their apps.

Amazon SageMaker is a comprehensive service that empowers developers and data scientists to efficiently create, train, and deploy machine learning (ML) models with ease. By alleviating the burdens associated with the various stages of ML processes, SageMaker simplifies the journey towards producing high-quality models. In contrast, conventional ML development tends to be a complicated, costly, and iterative undertaking, often compounded by the lack of integrated tools that support the entire machine learning pipeline. As a result, practitioners are forced to piece together disparate tools and workflows, leading to potential errors and wasted time. Amazon SageMaker addresses this issue by offering an all-in-one toolkit that encompasses every necessary component for machine learning, enabling quicker production times while significantly reducing effort and expenses. Additionally, Amazon SageMaker Studio serves as a unified, web-based visual platform that facilitates all aspects of ML development, granting users comprehensive access, control, and insight into every required procedure. This streamlined approach not only enhances productivity but also fosters innovation within the field of machine learning.

Streamlining quality assurance for machine learning, Snitch cuts through the clutter to highlight the most valuable insights for enhancing your models. It allows you to monitor performance metrics that extend beyond mere accuracy through comprehensive dashboards and analytical tools. You can pinpoint issues within your data pipeline and recognize distribution changes before they impact your predictions. Once deployed, maintain your model in production while gaining insight into its performance and data throughout its lifecycle. Enjoy flexibility with your data security, whether in the cloud, on-premises, private cloud, or hybrid environments, while choosing your preferred installation method for Snitch. Seamlessly integrate Snitch into your existing MLops framework and continue using your favorite tools! Our installation process is designed for quick setup, ensuring that learning and operating the product are straightforward and efficient. Remember, accuracy alone can be deceptive; therefore, it’s crucial to assess your models for robustness and feature significance before launch. Obtain actionable insights that will help refine your models, and make comparisons with historical metrics and your models' established baselines to drive continuous improvement. This comprehensive approach not only bolsters performance but also fosters a deeper understanding of your machine learning processes.

Achieve in minutes what previously took years to develop with our straightforward, adaptable, scalable, and secure machine learning monitoring solution. You’ll find all the tools necessary to deploy, sustain, and enhance machine learning in a production environment. Superwise offers an open platform that seamlessly integrates with any machine learning infrastructure and connects with your preferred communication tools. If you wish to explore further, Superwise is designed with an API-first approach, ensuring that every feature is available through our APIs, all accessible from the cloud platform of your choice. With Superwise, you gain complete self-service control over your machine learning monitoring. You can configure metrics and policies via our APIs and SDK, or you can simply choose from a variety of monitoring templates to set sensitivity levels, conditions, and alert channels that suit your needs. Experience the benefits of Superwise for yourself, or reach out to us for more information. Effortlessly create alerts using Superwise’s policy templates and monitoring builder, selecting from numerous pre-configured monitors that address issues like data drift and fairness, or tailor policies to reflect your specialized knowledge and insights. The flexibility and ease of use provided by Superwise empower users to effectively manage their machine learning models.

Safeguard data security and manage risk throughout your entire infrastructure. The assets that interact with customers are crucial for data collection and organization. This includes source code, data flows, and various third-party components. Public distrust in how companies manage data has grown, primarily due to incidents of data breaches, the unauthorized sharing or selling of personal data, and targeted advertising practices that lack consent, all of which diminish the relationship between businesses and their clients. It is vital to maintain your customers' trust by preventing their exposure to privacy threats. By implementing our data protection strategies, you can ensure both individual privacy for your clients and the safeguarding of your organization's sensitive data. Our comprehensive privacy program is designed to protect all the data your company manages. Furthermore, our privacy compliance software will help you avoid costly penalties associated with security policy violations, thus ensuring business continuity. With Zendata's no-code platform, you can effectively protect personal information while ensuring adherence to global privacy regulations, ultimately fostering a stronger bond with your customers. Trust in our solutions to secure your enterprise and enhance your reputation in the market.

Although not every model possesses the same quality, it is crucial for all models to have governance in place to promote responsible and ethical decision-making within an organization. The IBM® watsonx.governance™ toolkit for AI governance empowers you to oversee, manage, and track your organization's AI initiatives effectively. By utilizing software automation, it enhances your capacity to address risks, fulfill regulatory obligations, and tackle ethical issues related to both generative AI and machine learning (ML) models. This toolkit provides access to automated and scalable governance, risk, and compliance instruments that encompass aspects such as operational risk, policy management, compliance, financial oversight, IT governance, and both internal and external audits. You can proactively identify and mitigate model risks while converting AI regulations into actionable policies that can be enforced automatically, ensuring that your organization remains compliant and ethically sound in its AI endeavors. Furthermore, this comprehensive approach not only safeguards your operations but also fosters trust among stakeholders in the integrity of your AI systems.

Modulos AG, established in 2018, stands as a Swiss leader in Responsible AI Governance and is the inaugural AI Governance platform to receive ISO 42001 certification. The organization is dedicated to equipping businesses with the tools necessary to manage AI products and services responsibly within regulated settings, thereby enhancing and expediting the AI compliance process. The platform allows organizations to effectively oversee risks and adhere to essential regulatory frameworks, including the EU AI Act, NIST AI RMF, ISO 42001, among others. Consequently, Modulos aids its clients in mitigating economic, legal, and reputational risks, thereby promoting trust and ensuring long-term success in their AI initiatives.

Google Cloud's Dataplex serves as an advanced data fabric that empowers organizations to efficiently discover, manage, monitor, and govern their data across various platforms, including data lakes, warehouses, and marts, while maintaining uniform controls that ensure access to reliable data and facilitate large-scale analytics and AI initiatives. By offering a cohesive interface for data management, Dataplex streamlines processes like data discovery, classification, and metadata enhancement for diverse data types, whether structured, semi-structured, or unstructured, both within Google Cloud and external environments. It organizes data logically into business-relevant domains through lakes and data zones, making data curation, tiering, and archiving more straightforward. With its centralized security and governance features, Dataplex supports effective policy management, robust monitoring, and thorough auditing across fragmented data silos, thereby promoting distributed data ownership while ensuring global oversight. Furthermore, the platform includes automated data quality assessments and lineage tracking, which enhance the reliability and traceability of data, ensuring organizations can trust their data-driven decisions. By integrating these functionalities, Dataplex not only simplifies data management but also enhances collaboration within teams focused on analytics and AI.

DataHub is a versatile open-source metadata platform crafted to enhance data discovery, observability, and governance within various data environments. It empowers organizations to easily find reliable data, providing customized experiences for users while avoiding disruptions through precise lineage tracking at both the cross-platform and column levels. By offering a holistic view of business, operational, and technical contexts, DataHub instills trust in your data repository. The platform features automated data quality assessments along with AI-driven anomaly detection, alerting teams to emerging issues and consolidating incident management. With comprehensive lineage information, documentation, and ownership details, DataHub streamlines the resolution of problems. Furthermore, it automates governance processes by classifying evolving assets, significantly reducing manual effort with GenAI documentation, AI-based classification, and intelligent propagation mechanisms. Additionally, DataHub's flexible architecture accommodates more than 70 native integrations, making it a robust choice for organizations seeking to optimize their data ecosystems. This makes it an invaluable tool for any organization looking to enhance their data management capabilities.

Overseer AI serves as a sophisticated platform aimed at ensuring that content generated by artificial intelligence is not only safe but also accurate and in harmony with user-defined guidelines. The platform automates the enforcement of compliance by adhering to regulatory standards through customizable policy rules, while its real-time content moderation feature actively prevents the dissemination of harmful, toxic, or biased AI outputs. Additionally, Overseer AI supports the debugging of AI-generated content by rigorously testing and monitoring responses in accordance with custom safety policies. It promotes policy-driven governance by implementing centralized safety regulations across all AI interactions and fosters trust in AI systems by ensuring that outputs are safe, accurate, and consistent with brand standards. Catering to a diverse array of sectors such as healthcare, finance, legal technology, customer support, education technology, and ecommerce & retail, Overseer AI delivers tailored solutions that align AI responses with the specific regulations and standards pertinent to each industry. Furthermore, developers benefit from extensive guides and API references, facilitating the seamless integration of Overseer AI into their applications while enhancing the overall user experience. This comprehensive approach not only safeguards users but also empowers businesses to leverage AI technologies confidently.

Create, execute, and oversee AI models while enhancing decision-making at scale across any cloud infrastructure. IBM Watson Studio enables you to implement AI seamlessly anywhere as part of the IBM Cloud Pak® for Data, which is the comprehensive data and AI platform from IBM. Collaborate across teams, streamline the management of the AI lifecycle, and hasten the realization of value with a versatile multicloud framework. You can automate the AI lifecycles using ModelOps pipelines and expedite data science development through AutoAI. Whether preparing or constructing models, you have the option to do so visually or programmatically. Deploying and operating models is made simple with one-click integration. Additionally, promote responsible AI governance by ensuring your models are fair and explainable to strengthen business strategies. Leverage open-source frameworks such as PyTorch, TensorFlow, and scikit-learn to enhance your projects. Consolidate development tools, including leading IDEs, Jupyter notebooks, JupyterLab, and command-line interfaces, along with programming languages like Python, R, and Scala. Through the automation of AI lifecycle management, IBM Watson Studio empowers you to build and scale AI solutions with an emphasis on trust and transparency, ultimately leading to improved organizational performance and innovation.

The primary obstacle in expanding AI-driven decision-making lies in the underutilization of data. IBM Cloud Pak® for Data provides a cohesive platform that integrates a data fabric, enabling seamless connection and access to isolated data, whether it resides on-premises or in various cloud environments, without necessitating data relocation. It streamlines data accessibility by automatically identifying and organizing data to present actionable knowledge assets to users, while simultaneously implementing automated policy enforcement to ensure secure usage. To further enhance the speed of insights, this platform incorporates a modern cloud data warehouse that works in harmony with existing systems. It universally enforces data privacy and usage policies across all datasets, ensuring compliance is maintained. By leveraging a high-performance cloud data warehouse, organizations can obtain insights more rapidly. Additionally, the platform empowers data scientists, developers, and analysts with a comprehensive interface to construct, deploy, and manage reliable AI models across any cloud infrastructure. Moreover, enhance your analytics capabilities with Netezza, a robust data warehouse designed for high performance and efficiency. This comprehensive approach not only accelerates decision-making but also fosters innovation across various sectors.

Datatron provides tools and features that are built from scratch to help you make machine learning in production a reality. Many teams realize that there is more to deploying models than just the manual task. Datatron provides a single platform that manages all your ML, AI and Data Science models in production. We can help you automate, optimize and accelerate your ML model production to ensure they run smoothly and efficiently. Data Scientists can use a variety frameworks to create the best models. We support any framework you use to build a model (e.g. TensorFlow and H2O, Scikit-Learn and SAS are supported. Explore models that were created and uploaded by your data scientists, all from one central repository. In just a few clicks, you can create scalable model deployments. You can deploy models using any language or framework. Your model performance will help you make better decisions.

LMOps is a stack that allows you to launch production-ready applications for monitoring, model management and more. Portkey is a replacement for OpenAI or any other provider APIs. Portkey allows you to manage engines, parameters and versions. Switch, upgrade, and test models with confidence. View aggregate metrics for your app and users to optimize usage and API costs Protect your user data from malicious attacks and accidental exposure. Receive proactive alerts if things go wrong. Test your models in real-world conditions and deploy the best performers. We have been building apps on top of LLM's APIs for over 2 1/2 years. While building a PoC only took a weekend, bringing it to production and managing it was a hassle! We built Portkey to help you successfully deploy large language models APIs into your applications. We're happy to help you, regardless of whether or not you try Portkey!

CoComply’s Certification Platform offers a top-down perspective on data and AI criticality. It guides organizations through a four phase process to achieve governance and certification readiness, as well as monetization ready for their data assets and AI assets. The platform is designed to streamline Data and AI Governance. It helps organizations organize, maintain, and certify assets in accordance with regulatory standards and complying with compliance requirements. The platform is powered primarily by two modules: 1) Regulatory Intelligence 2) Certification Management CoComply offers organizations a systematic path to achieve compliance, audit-readiness, and certification for their data and AI assets. Since 2008, more than 200 data and AI usage cases have been certified by our certification framework for compliance and risk.

Aithenticate is a revolutionary tool designed to enhance transparency in AI-generated content, enabling users to clearly indicate the involvement of artificial intelligence and thereby improve their compliance with AI regulations. When website owners install the Aithenticate plugin, they can effortlessly inform their audience whether the content originates from human authors or AI systems, fostering trust and clarity in the information shared. This robust plugin includes a WordPress integration that effectively manages AI transparency on the site, a tailored company profile page that outlines business details along with AI usage, and a disclosure generator that produces succinct statements regarding the AI-assisted creation of content. By utilizing our plugin, you can seamlessly convey to your audience the origins of the content, ensuring that they understand its creation process while fostering a sense of reliability. Additionally, our generator simplifies the task of crafting clear disclosures, highlighting that the website content has been developed with the aid of AI technology, thus promoting ethical standards in content creation. Ultimately, Aithenticate empowers both website owners and users to navigate the evolving landscape of AI-generated information with confidence.

The Databricks Data Intelligence Platform empowers every member of your organization to leverage data and artificial intelligence effectively. Constructed on a lakehouse architecture, it establishes a cohesive and transparent foundation for all aspects of data management and governance, enhanced by a Data Intelligence Engine that recognizes the distinct characteristics of your data. Companies that excel across various sectors will be those that harness the power of data and AI. Covering everything from ETL processes to data warehousing and generative AI, Databricks facilitates the streamlining and acceleration of your data and AI objectives. By merging generative AI with the integrative advantages of a lakehouse, Databricks fuels a Data Intelligence Engine that comprehends the specific semantics of your data. This functionality enables the platform to optimize performance automatically and manage infrastructure in a manner tailored to your organization's needs. Additionally, the Data Intelligence Engine is designed to grasp the unique language of your enterprise, making the search and exploration of new data as straightforward as posing a question to a colleague, thus fostering collaboration and efficiency. Ultimately, this innovative approach transforms the way organizations interact with their data, driving better decision-making and insights.

Streamline the entire machine learning lifecycle from start to finish. Equip developers and data scientists with diverse, efficient tools for swiftly constructing, training, and deploying machine learning models. Speed up market readiness and enhance team collaboration through top-notch MLOps—akin to DevOps but tailored for machine learning. Foster innovation on a secure and trusted platform that prioritizes responsible machine learning practices. Cater to all skill levels by offering both code-first approaches and user-friendly drag-and-drop designers, alongside automated machine learning options. Leverage comprehensive MLOps functionalities that seamlessly integrate into current DevOps workflows and oversee the entire ML lifecycle effectively. Emphasize responsible ML practices, ensuring model interpretability and fairness, safeguarding data through differential privacy and confidential computing, while maintaining oversight of the ML lifecycle with audit trails and datasheets. Furthermore, provide exceptional support for a variety of open-source frameworks and programming languages, including but not limited to MLflow, Kubeflow, ONNX, PyTorch, TensorFlow, Python, and R, making it easier for teams to adopt best practices in their machine learning projects. With these capabilities, organizations can enhance their operational efficiency and drive innovation more effectively.

Mind Foundry, an innovative artificial intelligence firm, operates at the crossroads of research, practicality, and user-centered design to equip teams with AI solutions tailored for human needs. Established by top-tier academics, the company creates AI tools aimed at assisting both public and private sector organizations in addressing critical challenges, emphasizing human-centered results and the lasting effects of AI applications. Their collaborative platform facilitates the design, testing, and implementation of AI, allowing stakeholders to oversee their AI investments with a strong emphasis on performance, efficiency, and ethical considerations. The foundation of their approach is rooted in scientific principles, underscoring the importance of integrating ethics and transparency from the outset rather than retroactively. By blending experience design with quantitative techniques, they enhance the collaboration between humans and AI, making it more intuitive, effective, and impactful, ultimately leading to better decision-making and outcomes for all involved. This commitment to fostering a responsible AI ecosystem ensures that the technology remains aligned with societal values and priorities.

Design personalized monitoring solutions for your machine learning models using our incredibly user-friendly monitor builder, and receive notifications for potential problems such as concept drift, decline in model efficiency, bias, and more. Aporia offers flawless integration with any machine learning infrastructure, whether you are utilizing a FastAPI server deployed on Kubernetes, an open-source tool like MLFlow, or a cloud-based platform such as AWS Sagemaker. Delve into specific segments of data to observe model performance closely, allowing you to pinpoint any surprising biases, instances of underperformance, shifting features, and issues related to data integrity. When your ML models face challenges in production, having the appropriate tools at your disposal to swiftly identify the underlying issues is crucial. In addition to model monitoring, our investigation toolbox enables a comprehensive examination of model performance, data segments, statistical data, or distribution patterns, ensuring you have a complete understanding of your models' behavior. This robust approach not only enhances your monitoring capabilities but also empowers you to maintain the reliability and accuracy of your machine learning solutions over time.

ClearOPS assists both buyers and sellers in effectively managing their vendors while fulfilling due diligence obligations. As a comprehensive third-party risk management platform, ClearOPS allows users to monitor and track all vendor activities, distribute assessments, upload necessary documentation, and navigate the vendor management processes required by their clients. The burden of vendor security questionnaires can feel overwhelming, but our AI streamlines the initial review, significantly reducing the time required for completion. By serving as a system of record, ClearOPS ensures that critical information about your business remains secure and does not inadvertently leave your organization. After securing a customer, the next challenge is retention, and maintaining a strong trust relationship is central to our mission. ClearOPS simplifies the management of privacy and security operations information, making it readily available and current. Our user-friendly third-party risk management software empowers you to inspire your team while allowing you to assess your vendors at your convenience. Moreover, with ClearOPS, you can foster a culture of accountability and transparency within your organization, further enhancing your vendor relationships.

Fiddler is a pioneer in enterprise Model Performance Management. Data Science, MLOps, and LOB teams use Fiddler to monitor, explain, analyze, and improve their models and build trust into AI. The unified environment provides a common language, centralized controls, and actionable insights to operationalize ML/AI with trust. It addresses the unique challenges of building in-house stable and secure MLOps systems at scale. Unlike observability solutions, Fiddler seamlessly integrates deep XAI and analytics to help you grow into advanced capabilities over time and build a framework for responsible AI practices. Fortune 500 organizations use Fiddler across training and production models to accelerate AI time-to-value and scale and increase revenue.