Alternatives to SolasAI

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.

Fully managed ML tools allow you to build, deploy and scale machine-learning (ML) models quickly, for any use case. Vertex AI Workbench is natively integrated with BigQuery Dataproc and Spark. You can use BigQuery to create and execute machine-learning models in BigQuery by using standard SQL queries and spreadsheets or you can export datasets directly from BigQuery into Vertex AI Workbench to run your models there. Vertex Data Labeling can be used to create highly accurate labels for data collection. Vertex AI Agent Builder empowers developers to design and deploy advanced generative AI applications for enterprise use. It supports both no-code and code-driven development, enabling users to create AI agents through natural language prompts or by integrating with frameworks like LangChain and LlamaIndex.

Accelerate the entire machine learning lifecycle. Developers and data scientists can have more productive experiences building, training, and deploying machine-learning models faster by empowering them. Accelerate time-to-market and foster collaboration with industry-leading MLOps -DevOps machine learning. Innovate on a trusted platform that is secure and trustworthy, which is designed for responsible ML. Productivity for all levels, code-first and drag and drop designer, and automated machine-learning. Robust MLOps capabilities integrate with existing DevOps processes to help manage the entire ML lifecycle. Responsible ML capabilities – understand models with interpretability, fairness, and protect data with differential privacy, confidential computing, as well as control the ML cycle with datasheets and audit trials. Open-source languages and frameworks supported by the best in class, including MLflow and Kubeflow, ONNX and PyTorch. TensorFlow and Python are also supported.

Amazon SageMaker, a fully managed service, provides data scientists and developers with the ability to quickly build, train, deploy, and deploy machine-learning (ML) models. SageMaker takes the hard work out of each step in the machine learning process, making it easier to create high-quality models. Traditional ML development can be complex, costly, and iterative. This is made worse by the lack of integrated tools to support the entire machine learning workflow. It is tedious and error-prone to combine tools and workflows. SageMaker solves the problem by combining all components needed for machine learning into a single toolset. This allows models to be produced faster and with less effort. Amazon SageMaker Studio is a web-based visual interface that allows you to perform all ML development tasks. SageMaker Studio allows you to have complete control over each step and gives you visibility.

You can build, run, and manage AI models and optimize decisions across any cloud. IBM Watson Studio allows you to deploy AI anywhere with IBM Cloud Pak®, the IBM data and AI platform. Open, flexible, multicloud architecture allows you to unite teams, simplify the AI lifecycle management, and accelerate time-to-value. ModelOps pipelines automate the AI lifecycle. AutoAI accelerates data science development. AutoAI allows you to create and programmatically build models. One-click integration allows you to deploy and run models. Promoting AI governance through fair and explicable AI. Optimizing decisions can improve business results. Open source frameworks such as PyTorch and TensorFlow can be used, as well as scikit-learn. You can combine the development tools, including popular IDEs and Jupyter notebooks. JupterLab and CLIs. This includes languages like Python, R, and Scala. IBM Watson Studio automates the management of the AI lifecycle to help you build and scale AI with trust.

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.

FairNow provides organizations with the AI governance tools needed to ensure global compliance, and manage AI risks. FairNow's features, which are centralized, simplified, and empower the entire team, are loved by CPOs and CAIOs. FairNow's platform constantly monitors AI models in order to ensure that each model is fair, audit-ready, and compliant. Top features include: - Intelligent AI risk assessments: Conduct real-time assessment of AI models using their deployment locations in order to highlight potential reputational, financial and operational risks. - Hallucination Detection : Detect errors and unexpected responses. Automated bias evaluations: Automate bias assessments and mitigate algorithmic biased as they happen. Plus: - AI Inventory Centralized Policy Center - Roles & Controls FairNow's AI Governance Platform helps organizations build, purchase, and deploy AI with confidence.

Unutilized data is the biggest obstacle to scaling AI-powered decision making. IBM Cloud Pak®, for Data is a unified platform that provides a data fabric to connect, access and move siloed data across multiple clouds or on premises. Automate policy enforcement and discovery to simplify access to data. A modern cloud data warehouse integrates to accelerate insights. All data can be protected with privacy and usage policy enforcement. To gain faster insights, use a modern, high-performance cloud storage data warehouse. Data scientists, analysts, and developers can use a single platform to create, deploy, and manage trusted AI models in any cloud.

Standardize your AI governance efforts across different stakeholders, ensure regulatory readiness for your governance processes, and manage and measure your AI compliance and risks. You can transform your AI/ML projects from being managed by a variety of teams and processes into a centralized repository for trusted governance. Keep up-to-date on the latest regulations and standards by downloading AI Policy Packs. These packs meet all current and future regulations. Credo AI is an intelligence layer which sits on top your AI infrastructure and converts technical artifacts to actionable risk and compliance insights for product leaders and data scientists as well as governance teams. Credo AI is an intelligence layer which sits on top your technical and business infrastructure. It converts technical artifacts into compliance scores and risk scores.

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.

Databricks Unity Catalog, the only open and unified governance solution in the industry for data and AI that is built into the Databricks Data Intelligence Platform, is the only one of its kind. Unity Catalog allows organizations to seamlessly govern structured and unstructured information in any format. This includes machine learning models, notebooks and dashboards as well as files and files stored on any cloud or platform. Data scientists, analysts, engineers, and other professionals can securely discover, access and collaborate on trusted AI assets across platforms. This will boost productivity and unlock full potential of the Lakehouse environment. This open and unified approach to governance accelerates data and AI projects and simplifies regulatory compliance. Discover and classify structured and unstructured information in any format including machine learning models and notebooks.

Data analysts, engineers, scientists, and other scientists can be brought together. Automate self-service analytics and machine learning operations. Get results today, build for tomorrow. Dataiku DSS is a collaborative data science platform that allows data scientists, engineers, and data analysts to create, prototype, build, then deliver their data products more efficiently. Use notebooks (Python, R, Spark, Scala, Hive, etc.) You can also use a drag-and-drop visual interface or Python, R, Spark, Scala, Hive notebooks at every step of the predictive dataflow prototyping procedure - from wrangling to analysis and modeling. Visually profile the data at each stage of the analysis. Interactively explore your data and chart it using 25+ built in charts. Use 80+ built-in functions to prepare, enrich, blend, clean, and clean your data. Make use of Machine Learning technologies such as Scikit-Learn (MLlib), TensorFlow and Keras. In a visual UI. You can build and optimize models in Python or R, and integrate any external library of ML through code APIs.

Mind Foundry is an artificial Intelligence company that combines research, innovation, usability, and usability to empower teams using AI that is built for people. Mind Foundry was founded by world-leading academics. It develops AI solutions to help public and private sector organisations tackle high-stakes issues. Mind Foundry focuses on human outcomes and long-term impacts of AI interventions. Our platform is intrinsically collaborative and powers AI design, testing, and deployment. It enables stakeholders to responsibly manage their AI investments with a key focus on performance and efficiency as well as ethical impact. It is based on scientific principles and the understanding that ethics and transparency can only be added after the fact. The combination of quantitative and experience design makes collaboration between humans, AI and AI easier, more efficient, and more powerful.

Our platform dynamically evaluates and mitigates AI risk in models and datasets relating to bias, proxy bias, and fairness. Our Responsible AI technology provides greater visibility into AI models, and makes them more understandable and interpretable. Our AI robustness assurance algorithms are based on research and identify and mitigate risk related to lack robustness. Our platform provides a comprehensive review of the AI landscape, including MRM and AI regulations, and provides a deeper risk analysis. AI risks in both internal AI systems and AI systems provided by a third party need to be assessed, and remedied. SigmaRed platform allows comprehensive third-party AI Risk Management (AI TPRM). It reduces cycle time for AI risk assessments and provides deep visibility, control and stakeholder-based reports.

Sekura.ai provides AI-based cybersecurity solutions that enhance threat detection and response. Their solutions use advanced artificial intelligence to identify security risks and mitigate them in real-time, protecting organizations against cyber threats. You can harness AI while protecting sensitive data and maintaining compliance. Your engineering team can focus on your core products. Use advanced LLMs to improve internal operations and customer experience. Detect and redact sensitive data instantly during all LLM operations - from training to inference. Control access to sensitive data and prompts. Use external models to avoid revealing private information. Set time-based controls for data access. Confidence in meeting evolving privacy standards. Use public LLMs without wasting time and money on internal models.

Every model requires governance to ensure ethical and responsible decision-making in the business. IBM® watsonx.governance™ toolkit for AI governance allows you to direct, manage and monitor your organization's AI activities. It uses software automation to enhance your ability to mitigate risk, manage regulatory requirements, and address ethical concerns when it comes to both generative AI (ML) and machine learning models. Access automated and scalable compliance, governance and risk tools that cover financial management, IT governance, IT governance, operational risk and policy management. Proactively detect model risks and mitigate them while translating AI regulations to enforceable policies that can be enforced automatically.

Responsible AI is a business problem and not a technical problem. We solve the problem by connecting teams to one platform, allowing you to reduce risk, maximize your potential, and put your intentions into action. Cloud-based governance applications can unite every stage of your AI/ML journey. GovernML is the catalyst you need to bring AI/ML systems to the world. We offer user-friendly workflows that track the entire lifecycle of your AI journey. This is good news for your bottom line and risk mitigation. Monitaur offers cloud-based governance solutions that track your AI/ML model from policy to proof. SOC 2 Type II certified, we can enhance your AI governance and provide bespoke solutions through a single platform. GovernML is responsible AI/ML systems that are available to the world. You can now create scalable, user-friendly workflows to document the entire lifecycle of your AI journey from one platform.

A platform for AI governance, designed by lawyers with regulatory experience and tailored to your policies and use cases. Businesses must learn how to navigate and comply new legislation and guidelines. AI failures can lead to a loss of customer trust and a decline in product engagement. Teams are faced with AI systems that are more complex and have a greater number of use cases. Our assessments and live model control will help you monitor compliance with your AI systems. Alert users of potential issues or risk. Implementing good AI Governance practices can take a lot of time. Use the built-in automation for importing model data and artifacts and updating documentation. Understand AI compliance within your organization. Give senior stakeholders a complete picture of their AI to make strategic decisions. Share reports with curated audiences. We provide a comprehensive set of policies to ensure legal and regulatory conformance through pre-configured assessment.

Our easy-to-use monitor builder allows you to create customized monitors for your machinelearning models. Get alerts for issues such as concept drift, model performance degradation and bias. Aporia can seamlessly integrate with any ML infrastructure. It doesn't matter if it's a FastAPI server built on top of Kubernetes or an open-source deployment tool such as MLFlow, or a machine-learning platform like AWS Sagemaker. Zoom in on specific data segments to track the model's behavior. Unexpected biases, underperformance, drifting characteristics, and data integrity issues can be identified. You need the right tools to quickly identify the root cause of problems in your ML models. Our investigation toolbox allows you to go deeper than model monitoring and take a deep look at model performance, data segments or distribution.

AI and non AI models require risk management and oversight. Fairly is a continuous monitoring tool for advanced model governance. With Fairly, data science and cyber-security teams can easily collaborate with risk and compliance teams to ensure that models are reliable and secured. Fairly makes it simple to stay up to date with policies and regulations regarding procurement, validation, and audit of non AI, predictive AI, and generative AI. Fairly simplifies model validation and auditing by providing direct access to ground truth within a controlled environment, for both in-house models and third-party ones, without adding additional overhead to development or IT teams. Fairly's platform guarantees compliant, ethical, and secure models. Fairly helps teams identify compliance, operational, and model risks and mitigate them according to internal policies, external regulations, and monitor, report, and assess them.

Azure AI Content Security is a platform for content moderation that uses AI to ensure your content remains safe. AI models can detect offensive or inappropriate text and images in seconds, allowing you to create better online experiences. Language models analyze multilingual texts, both in short and long form with an understanding of context, semantics, and syntax. Using the latest Florence technology, vision models can recognize images and detect objects. AI content classifiers can identify content that is sexual, violent, hateful, or self-harming with high levels granularity. The severity of content moderation is measured on a scale from low to high.

Simplified quality assurance for machine learning. Snitch eliminates all noise so you can find the most relevant information to improve your models. With powerful dashboards and analysis, you can track your model's performance beyond accuracy. Identify potential problems in your data pipeline or distribution shifts and fix them before they impact your predictions. Once you've deployed, stay in production and have visibility to your models and data throughout the entire cycle. You can keep your data safe, whether it's cloud, on-prem or private cloud. Use the tools you love to integrate Snitch into your MLops process! We make it easy to get up and running quickly. Sometimes accuracy can be misleading. Before you deploy your models, make sure to assess their robustness and importance. Get actionable insights that will help you improve your models. Compare your models against historical metrics.

ModelOp is a leading AI governance tool that helps enterprises safeguard AI initiatives including generative AI and Large Language Models. It also protects in-house vendors, third-party vendors and embedded systems without stifling the innovation. Corporate boards and C suites demand the rapid adoption of generative AI, but face financial risks, regulatory, privacy, security, and ethical issues. Governments at all levels, including federal, state and local, are implementing AI regulations and overseeing the industry quickly. This forces enterprises to prepare and comply with rules that prevent AI from going awry. Connect with AI Governance specialists to stay informed on market trends, regulations and news. You can also get insights and opinions from experts. ModelOp Center helps organizations stay safe and provides peace of mind for all stakeholders. Streamline reporting and compliance across the enterprise.

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!

Cisco AI Defense is an advanced security platform designed to help organizations securely adopt and manage AI technologies. It tackles key challenges like unauthorized usage of generative AI tools and vulnerabilities in AI applications by delivering comprehensive visibility and control over AI assets. The solution includes features such as AI Access to regulate third-party AI usage, automated vulnerability scans for AI models and applications, real-time protections against adversarial attacks, and a centralized inventory of AI resources across hybrid environments. With its integration of network-level insights and ongoing threat intelligence, Cisco AI Defense provides a robust framework for mitigating the risks associated with AI deployment and ensuring the safe operation of AI systems.

Our easy-to-implement AI Governance Control Plane ensures AI usage adheres to corporate policies. SurePath AI helps you to reduce complexity, gain visibility and increase AI adoption in a secure manner. Native integrations with your existing security solutions. Private models and enterprise data sources. Native support for SSO, SCIM and SIEM. Detect AI usage at the network level. Control access to sensitive data and inspect requests. Redact sensitive data from requests to public models. Modifications in-line of requests can be made to improve productivity and reduce risk. Redirect traffic to private AI models. Use SurePath AI’s private model access control as your own, internally branded enterprise AI Portal. Policy-based controls enrich request with only enterprise data that users have been granted access to. This gives meaningful responses based upon relevant business context. Users' prompts will automatically be enhanced to align output with enterprise objectives.

Use Qlik®, Staige™, to make AI real. It will provide a trusted foundation for data, automation, actionable forecasts, and a company-wide impact. AI is not just experiments and initiatives - it's a whole ecosystem of files, scripts and results. We've partnered up with the best sources to provide you with integrations that will save time, enable better management, and validate the quality of your data. Automate the delivery and management of real-time AWS data to data lakes or warehouses, and make this data easily accessible via a governed catalogue. With our new integration with Amazon Bedrock you can easily connect foundational large-language models (LLMs), including A21 Labs Amazon Titan, Anthropic Cohere and Meta. AWS customers can leverage AI-driven insights with ease using seamless integration with Amazon Bedrock.

Acuvity provides the most comprehensive AI governance and security platform for your employees and apps. DevSecOps allows developers to focus on AI Innovation while DevSecOps implements AI Security without code changes. Pluggable AI security ensures complete coverage without outdated libraries or inadequate coverage. By utilizing GPUs only to run LLM models, you can reduce costs. Full visibility of all GenAI models and apps, plugins and services that are being used and explored by your teams. Granular observability of all GenAI interactions, with comprehensive logging. AI usage in enterprises needs a specialized framework that can address new AI risks and comply with emerging AI regulation. Employees can use AI with confidence, without exposing confidential information. Legal wants to make sure that AI-generated content is free of copyright or regulatory issues.

Aithenticate, a tool for bringing transparency to AI content allows users to disclose artificial intelligence use and achieve greater compliance to AI regulations. Aithenticate allows website owners to easily communicate with their readers whether content is created by humans or AI. This ensures clarity and trust in information provided. The plugin includes features such as a WordPress plug-in that manages AI transparency, a company profile page detailing information about the business and AI usage, and disclosure generators to create concise statements regarding AI-assisted creation of content. Our plugin allows you to easily communicate the nature of content creation to your readers, ensuring trust and clarity in the information provided. Our generator will produce a brief disclosure to inform users that a website was created with the aid of AI technology.

Observability allows you to detect data issues and ML problems faster, to deliver continuous improvements and to avoid costly incidents. Start with reliable data. Monitor data in motion for quality issues. Pinpoint data and models drift. Identify the training-serving skew, and proactively retrain. Monitor key performance metrics continuously to detect model accuracy degradation. Identify and prevent data leakage in generative AI applications. Protect your generative AI apps from malicious actions. Improve AI applications by using user feedback, monitoring and cross-team collaboration. Integrate in just minutes with agents that analyze raw data, without moving or replicating it. This ensures privacy and security. Use the proprietary privacy-preserving technology to integrate the WhyLabs SaaS Platform with any use case. Security approved by healthcare and banks.

OneTrust Data & AI Governance is an integrated platform that consolidates insights from data, models, risk assessments, and metadata. It provides comprehensive visibility to data products and AI developments. It accelerates data driven innovation by increasing approval speed for data products and AI system. The solution ensures business continuity by continuously monitoring data and AI systems. This ensures regulatory compliance, effective management of risk, and reduced application downtime. It simplifies compliance through centrally defining and orchestrating data policies, as well as natively enforcing them. The scanning, classification and tagging sensitive data are key features that ensure reliable application of data governance across structured and nonstructured sources. It promotes responsible use of data by enforcing a robust data governance frame work that enforces role-based access.

Controllo, an AI-enhanced platform for Governance, Risk, and Compliance, unifies data, teams, and tools to streamline audit and regulatory compliance processes, thereby reducing costs and timelines. It provides comprehensive end-toend GRC management. Information security teams can get a 360-degree overview of compliance across multiple frameworks. The platform integrates seamlessly with ticketing tools like Jira or ServiceNow as well as communication software to ensure effective risk mitigation. It prioritizes vulnerabilities according to the actual cyber risk impact, rather than relying on technical severity scores. This allows for data-driven mitigation and ensures regulatory compliance. Controllo supports various frameworks.

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.

Scale the next generation of AI applications with confidence. Scale AI with confidence across your organization using industry-leading technologies that manage risk, improve accuracy and privacy, reinforce transparency and simplify compliance. Use templates and tools that integrate responsible AI into open source, machine-learning operations, and generative AI workflows to empower cross-functional teams in building the next generation of AI apps. With Azure security and tooling for responsible AI, you can detect and mitigate harmful usage. Monitor text and images for offensive or inappropriate content. Rapid machine-learning models can be deployed and seamless collaboration is enabled with prompt flow. This accelerates time to value. Create generative AI applications, and copilots on one platform.

Lanai, an AI empowerment platform, is designed to help enterprises navigate through the complexities of AI adoption. It does this by providing visibility into AI interaction, protecting sensitive data, and speeding up successful AI initiatives. The platform includes features such as AI Visibility to discover prompt interactions between applications and teams, Risk Monitoring to track compliance and identify possible exposures, and Progress Tracking to measure adoption against strategy targets. Lanai also provides policy intelligence, guardrails, and in-context guidance to help users navigate queries appropriately and maintain document integrity. The platform provides smart prompt coaching to provide real-time guidance. It also offers personalized insights into the top use cases and apps, as well as manager and user reports that accelerate enterprise usage and ROI.

Google Cloud Dataplex is a data fabric that allows organizations to centrally manage, monitor and govern data across data lakes and data warehouses. It provides access to trusted data, while enabling analytics and AI to be powered at scale. Dataplex provides a unified data management interface that allows users to automate data discovery and classification, as well as metadata enrichment, for structured, semistructured, or unstructured data in Google Cloud, and beyond. It simplifies data curation, tiering and archiving by facilitating the logical organization into business-specific domains, using lakes and zones. Centralized governance and security features allow for policy management, monitoring and auditing across silos of data, allowing distributed data ownership and global oversight. Dataplex also has built-in capabilities for data quality and data lineage, automating data assessments and capturing lineage.

ClearOPS assists buyers and sellers to manage their vendors and meet due diligence requirements. ClearOPS is a third-party risk platform that covers the full circle. ClearOPS allows you to track and monitor your vendors, upload evidence and send assessments, and respond directly to customer's vendor management processes. Vendor security questionnaires can be like a hot potato. No one wants to complete them. Our A.I. Our A.I. takes the first pass, saving you a lot of time. You don't have to worry about the information about your business being lost. Now that you have won the customer, what do you do? You have to keep them. We are passionate about maintaining healthy trust. ClearOPS keeps your privacy and security information up-to-date and easily accessible. Simple third-party risk management solution. Empower your colleagues and evaluate your vendors on your own schedule.

DataHub is a free and open-source metadata platform that streamlines data discovery, observability and governance across diverse data ecologies. It allows organizations to discover trustworthy data with experiences tailored to each user and eliminates breaking updates with detailed cross-platform, column-level lineage. DataHub gives you a complete view of your data, including its business, operational and technical context. The platform provides automated data quality checks, AI-driven anomaly identification and alerts teams when problems arise. It also centralizes incident tracking. DataHub's detailed ownership, documentation, and lineage information allows for quick issue resolution. It automates governance by classifying assets in real-time, reducing manual work with GenAI documentation, AI classification, and smart propagation. DataHub’s extensible architecture supports more than 70 native integrations.

Overseer AI, a platform that ensures AI-generated content is accurate, safe, and aligned to user-defined policies, is designed to ensure this. It provides compliance enforcement through automated adherence to regulatory standard rules, real-time moderation of content to block harmful or toxic AI outputs, debugging AI outcomes by testing and monitoring responses to custom safety policies, policy driven AI governance by applying central safety rules to all AI interactions, as well as trust-building by ensuring safe, accurate and brand-compliant AI outputs. The platform is tailored to cater to various industries including healthcare, finance and legal technology. It also provides solutions that ensure AI responses are aligned with industry-specific standards and regulations. Developers can use comprehensive guides and API references for Overseer AI integration into their applications.

The Databricks Data Intelligence Platform enables your entire organization to utilize data and AI. It is built on a lakehouse that provides an open, unified platform for all data and governance. It's powered by a Data Intelligence Engine, which understands the uniqueness in your data. Data and AI companies will win in every industry. Databricks can help you achieve your data and AI goals faster and easier. Databricks combines the benefits of a lakehouse with generative AI to power a Data Intelligence Engine which understands the unique semantics in your data. The Databricks Platform can then optimize performance and manage infrastructure according to the unique needs of your business. The Data Intelligence Engine speaks your organization's native language, making it easy to search for and discover new data. It is just like asking a colleague a question.

You can now build what took years. Simple, customizable, scalable, secure, ML monitoring. Everything you need to deploy and maintain ML in production. Superwise integrates with any ML stack, and can connect to any number of communication tools. Want to go further? Superwise is API-first. All of our APIs allow you to access everything, and we mean everything. All this from the comfort of your cloud. You have complete control over ML monitoring. You can set up metrics and policies using our SDK and APIs. Or, you can simply choose a template to monitor and adjust the sensitivity, conditions and alert channels. Get Superwise or contact us for more information. Superwise's ML monitoring policy templates allow you to quickly create alerts. You can choose from dozens pre-built monitors, ranging from data drift and equal opportunity, or you can customize policies to include your domain expertise.

Tumeryk Inc. is a leader in advanced generative AI-based security solutions. We offer tools such as the AI Trust Score for real-time monitoring and risk management. Our platform enables organizations to secure AI systems and ensure reliable, trustworthy, policy-aligned deployments. The AI Trust Score quantifies risk associated with generative AI systems. This allows for compliance with regulations such as the EU AI Act ISO 42001 and NIST RMF 6000.1. This score evaluates the trustworthiness and scores generated prompt responses. It accounts for risks such as bias, jailbreak tendency, off-topic answers, toxicity and Personally Identifiable Information data leakage. It can be integrated in business processes to determine whether content should either be accepted, flagged or blocked. This allows organizations to minimize risks associated with AI generated content.

55% of organizations adopt AI to remain competitive. Harmonic equips security teams with robust tools to ensure secure implementation. Harmonic's security reach is extended as employees adopt new tools, particularly from remote locations. Harmonic ensures that no shadow AI escapes detection. Harmonic's advanced security measures will help you to minimize the risk of data exposure, and ensure compliance. Your sensitive information will remain private and secure. The traditional data security methods cannot keep up with the rapid advances in AI. Many security teams are stuck with broad, restrictive measures which severely impact productivity. Harmonic offers a smarter solution. Our solutions give security professionals the visibility and tools they need to protect sensitive, unstructured information effectively without compromising efficiency.

Empowering AI governance leaders with advanced insights & risk intelligence to drive responsible AI innovation and compliance.

WitnessAI builds the guardrails to make AI productive, safe, and usable. Our platform allows enterprises the freedom to innovate, while enjoying the power of generative artificial intelligence, without compromising on privacy or security. With full visibility of applications and usage, you can monitor and audit AI activity. Enforce a consistent and acceptable use policy for data, topics, usage, etc. Protect your chatbots, employee activity, and data from misuse and attack. WitnessAI is building an international team of experts, engineers and problem solvers. Our goal is to build an industry-leading AI platform that maximizes AI's benefits while minimizing its risks. WitnessAI is a collection of security microservices which can be deployed in your environment on-premise, in a sandbox in the cloud, or within your VPC to ensure that data and activity telemetry remain separate from other customers. WitnessAI, unlike other AI governance solutions provides regulatory separation of your information.

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.

We are eCollege. Your digital gateway to further training and education, funded by SOLAS. Our mission is to provide you with excellent online learning experiences that are tailored to enhance your skill set and empower your career and personal growth. We work with learning providers in order to provide you with free, part-time, online programmes that are essential for thriving in this digital age, highly sought after by employers and designed to be engaging and enjoyable. We offer a variety of courses that will meet your needs. Whether you are looking for formal accreditation with online tutors or self-directed training to build your skills and knowledge, we have a course to suit. Some of our courses are available immediately, while others have a set start date to allow you to experience the course with a group. Browse our course catalog to get started!

Manage data security and risk across your entire stack. Data collection and data shaping occurs in your customer-facing assets. Source code with data flow and third-party components. Data breaches, the sharing/selling of information and targeted advertising without consent are all factors that contribute to a lack of trust in how companies handle their data. Don't lose your customers' trust if you expose them to privacy risks. Our data protection plans will protect sensitive information for your organization and ensure their privacy. Our privacy program will protect all the data of your business. Our privacy compliance software will protect your enterprise from fines if you do not comply with security policies. Zendata's platform does not require any code to protect your customers' information and ensure compliance.

The cost of commercial tort litigation against a business (where benefits paid are losses plus defense attorney fees + administrative expenses, e.g. gathering documents, meeting counsel, sitting for depositions etc.). The annual cost was approximately $160 billion. The total amount was nearly $1.6 trillion over a 10-year period. We used 400 federal court complaints (no emails) to extract facts and train a deep learning model for the federal court's category civil rights-employment. We tested the model with 20,401 emails from Enron and put it in a GPU instance in Microsoft Azure. The model had never evaluated any emails before. Each true positive email can be exported to an internal investigation platform or case management platform. You can also save true positives to the UI and add them to your initial training set to retrain the model.

CyberCube's platform for analytics provides unrivalled data, signals, and models to help with cyber risk quantification. CyberCube allows (re)insurance placement, portfolio management optimization, and underwriting decisions - all powered with a state of the art cloud-based technology framework. Our clients get the best in cyber insurance analytics, models, and services. We are a trusted contributor to the industry and work with multiple stakeholders to create world-class solutions. Our team of 100's of experts in data science, cyber security and software engineering can help you unlock the business value of cyber insurance. Allows you to see the enterprise risk profiles and allow individual risk underwriting. Forward-looking models enable portfolio-level decision making.