Credo AI Alternatives

Build, deploy, and scale machine learning (ML) models faster, with fully managed ML tools for any use case. Through Vertex AI Workbench, Vertex AI is natively integrated with BigQuery, Dataproc, and Spark. You can use BigQuery ML to create and execute machine learning models in BigQuery using standard SQL queries on existing business intelligence tools and spreadsheets, or you can export datasets from BigQuery directly into Vertex AI Workbench and run your models from there. Use Vertex Data Labeling to generate highly accurate labels for your data collection.

(Bank CFO) “I don’t have confidence and trust in our data. We keep discovering hidden risks”. Since 70% of data initiatives fail due to unreliable data (Gartner research), are you risking your reputation by trusting the accuracy of your data that you share with your business stakeholders and partners? Data Trust Scores must be measured in Data Lakes, warehouses, and throughout the pipeline, to ensure the data is trustworthy and fit for use. It typically takes 4-6 weeks of manual effort just to set a file or table for validation. Then, the rules have to be constantly updated as the data evolves. The only scalable option is to automate data validation rules discovery and rules maintenance. DataBuck is an autonomous, self-learning, Data Observability, Quality, Trustability and Data Matching tool. It reduces effort by 90% and errors by 70%. "What took my team of 10 Engineers 2 years to do, DataBuck could complete it in less than 8 hours." (VP, Enterprise Data Office, a US bank)

Go beyond compliance and build trust through transparency, choice, and control. People demand greater control of their data, unlocking an opportunity for organizations to use these moments to build trust and deliver more valuable experiences. We provide privacy and data governance automation to help organizations better understand their data across the business, meet regulatory requirements, and operationalize risk mitigation to provide transparency and choice to individuals. Achieve data privacy compliance faster and build trust in your organization. Our platform helps break down silos across processes, workflows, and teams to operationalize regulatory compliance and enable trusted data use. Build proactive privacy programs rooted in global best practices, not reactive to individual regulations. Gain visibility into unknown risks to drive mitigation and risk-based decision making. Respect individual choice and embed privacy and security by default into the data lifecycle.

Amazon SageMaker is a fully managed service that provides every developer and data scientist with the ability to build, train, and deploy machine learning (ML) models quickly. SageMaker removes the heavy lifting from each step of the machine learning process to make it easier to develop high quality models. Traditional ML development is a complex, expensive, iterative process made even harder because there are no integrated tools for the entire machine learning workflow. You need to stitch together tools and workflows, which is time-consuming and error-prone. SageMaker solves this challenge by providing all of the components used for machine learning in a single toolset so models get to production faster with much less effort and at lower cost. Amazon SageMaker Studio provides a single, web-based visual interface where you can perform all ML development steps. SageMaker Studio gives you complete access, control, and visibility into each step required.

The Holistic AI Governance Platform is a 360 solution for AI trust, risk, security, and compliance that empowers companies to adopt AI at scale.

Datatron offers tools and features built from scratch, specifically to make machine learning in production work for you. Most teams discover that there’s more to just deploying models, which is already a very manual and time-consuming task. Datatron offers single model governance and management platform for all of your ML, AI, and Data Science models in production. We help you automate, optimize, and accelerate your ML models to ensure that they are running smoothly and efficiently in production. Data Scientists use a variety of frameworks to build the best models. We support anything you’d build a model with ( e.g. TensorFlow, H2O, Scikit-Learn, and SAS ). Explore models built and uploaded by your data science team, all from one centralized repository. Create a scalable model deployment in just a few clicks. Deploy models built using any language or framework. Make better decisions based on your model performance.

An AI governance platform designed by lawyers with regulatory expertise, tailored to your use cases and policies. Businesses must learn to navigate and comply with new legislation and guidelines. Organizations risk losing customer trust and a breakdown in product engagement if AI malfunctions. Teams must deal with increasingly complex AI systems, with more use cases than ever. Monitor compliance of your AI systems through our assessments and live model controls. Alert users to mitigate potential issues or risks. Implementing good AI governance practices can be time-consuming. Leverage built-in automation to import model data and artifacts, and review and update documentation. Understand AI compliance across your organization. Provide senior stakeholders with the full picture of their AI compliance to make strategic decisions and share reports for curated audiences. We offer a complete set of policies that ensure legal and regulatory compliance through pre-configured assessments.

Creating responsible AI is a business problem, not just a tech problem. We solve for the whole problem by bringing teams together onto one platform to mitigate risk, leverage your full potential, and turn intention into action. Uniting every stage of your AI/ML journey with cloud-based governance applications. GovernML is the kickstarter you need to bring good AI/ML systems into the world. We bring user-friendly workflows that document the lifecycle of your AI journey on one platform. That’s good news for your risk mitigation and your bottom line. Monitaur provides cloud-based governance applications that track your AI/ML models from policy to proof. We are SOC 2 Type II-certified to enhance your AI governance and deliver bespoke solutions on a single unifying platform. GovernML brings responsible AI/ML systems into the world. Get scalable, user-friendly workflows that document the lifecycle of your AI journey on one platform.

The Databricks Data Intelligence Platform allows your entire organization to use data and AI. It’s built on a lakehouse to provide an open, unified foundation for all data and governance, and is powered by a Data Intelligence Engine that understands the uniqueness of your data. The winners in every industry will be data and AI companies. From ETL to data warehousing to generative AI, Databricks helps you simplify and accelerate your data and AI goals. Databricks combines generative AI with the unification benefits of a lakehouse to power a Data Intelligence Engine that understands the unique semantics of your data. This allows the Databricks Platform to automatically optimize performance and manage infrastructure in ways unique to your business. The Data Intelligence Engine understands your organization’s language, so search and discovery of new data is as easy as asking a question like you would to a coworker.

While not all models are created equal, every model needs governance to drive responsible and ethical decision-making throughout the business. IBM® watsonx.governance™ toolkit for AI governance allows you to direct, manage and monitor your organization’s AI activities. It employs software automation to strengthen your ability to mitigate risks, manage regulatory requirements and address ethical concerns for both generative AI and machine learning (ML) models. Access automated and scalable governance, risk and compliance tools that cover operational risk, policy management, compliance, financial management, IT governance and internal or external audits. Proactively detect and mitigate model risks while translating AI regulations into enforceable policies for automatic enforcement.

AI and non-AI models need risk management and oversight. Fairly provides a continuous monitoring system for advanced model governance and oversight. With Fairly, risk and compliance teams can collaborate with data science and cyber security teams easily to ensure models are reliable and secure. Fairly makes it easy to stay up-to-date with policies and regulations for procurement, validation and audit of non-AI, predictive AI and generative AI models. Fairly simplifies the model validation and auditing process with direct access to the ground truth in a controlled environment for in-house and third-party models, without adding overhead to development and IT teams. Fairly's platform ensures compliant, secure, and ethical models. Fairly helps teams identify, assess, monitor, report and mitigate compliance, operational and model risks according to internal policies and external regulations.

Acuvity is the most comprehensive AI security and governance platform for your employees and applications. DevSecOps implements AI security without code changes and devs can focus on AI Innovation. Pluggable AI security results in completeness of coverage, without old libraries or insufficient coverage. Optimize costs by efficiently using GPUs only for LLM models. Full visibility into all GenAI models, apps, plugins, and services that your teams are using and exploring. Granular observability into all GenAI interactions with comprehensive logging and an audit trail of inputs and outputs. AI usage in enterprises requires a specialized security framework that is able to address new AI risk vectors and comply with emerging AI regulations. Employees can use AI confidently, without risking exposing confidential data. Legal would like to ensure there are no copyright, or regulatory issues while using AI-generated content.

ModelOp is the leading AI governance software that helps enterprises safeguard all AI initiatives, including generative AI, Large Language Models (LLMs), in-house, third-party vendors, embedded systems, etc., without stifling innovation. Corporate boards and C‑suites are demanding the rapid adoption of generative AI but face financial, regulatory, security, privacy, ethical, and brand risks. Global, federal, state, and local-level governments are moving quickly to implement AI regulations and oversight, forcing enterprises to urgently prepare for and comply with rules designed to prevent AI from going wrong. Connect with AI Governance experts to stay informed about market trends, regulations, news, research, opinions, and insights to help you balance the risks and rewards of enterprise AI. ModelOp Center keeps organizations safe and gives peace of mind to all stakeholders. Streamline reporting, monitoring, and compliance adherence across the enterprise.

FairNow equips organizations with all the AI governance tools they need to ensure global compliance and manage AI risk. Loved by CPOs, CAIOs, risk management, and legal professionals, FairNow's features are simplified, centralized, and empowering for the entire team. FairNow’s platform continuously monitors AI models to ensure that every model is fair, compliant, and audit-ready. Top features include: - Intelligent AI Risk Assessments: Conduct real-time assessments of AI models, using their deployment locations to highlight possible reputational, financial, and operational risks. - Hallucination Detection: Proactively detect errors and unexpected answers. - Automated Bias Evaluations: Automate bias evaluations and mitigate algorithmic bias as it happens. Plus: - AI Inventory - Centralized Policy Center - Roles and Controls FairNow’s AI governance platform helps organizations build, buy, and deploy AI with complete confidence.

Take your data-driven enterprise to the next level with augmented intelligence. From algorithms to architecture, BasisAI manages the end to end development of real-time, scalable and responsible AI systems. Complete lifecycle AI solution: from bespoke AI algorithms, to production-grade AI application, and ongoing multi-year management. Rapid time to market: from your data to scalable, containerised deployment of real-time AI engine in weeks. No black boxes. Built-in AI governance, fairness and compliance. Retain control over your enterprise data, whether it is on AWS, GCP or another cloud infrastructure. We provide strategic guidance in building the right structures, frameworks and technologies, giving you a path to long-term scalability. Through exploratory use case sessions and system design workshops, we help you to move beyond experiments and algorithms and have control over your own capability development.

SolasAI is software that detects and removes bias & discrimination from a customer's decisioning models. It works in credit & insurance underwriting, predictive marketing, healthcare, and employment to name a few use cases. We provide trust & transparency into artificial intelligence, machine learning, and standard statistical models. If you are tired of paying expensive experts who can't seem to agree, and then leave the hard part of fixing the problems to your expensive and over worked data scientists, then SolasAI is for you. We follow the latest decisions and signals from courts, regulators, and law makers, as well as the latest and greatest technology trends for AI and fairness as a whole. This is built into SolasAI so you don't have to figure it out yourself.

Modulos AG, founded in 2018, is a Swiss pioneer in Responsible AI Governance and the first AI Governance platform to achieve ISO 42001 certification. With a mission to empower organizations to govern AI products and services responsibly in regulated environments, Modulos streamlines and accelerates the AI compliance process. The platform enables businesses to efficiently manage risks and align with key regulatory frameworks like the EU AI Act, NIST AI RMF, ISO 42001, and more. As a result, Modulos helps clients avoid economic, legal, and reputational risks, fostering trust and long-term success in their AI initiatives.

Bring data analysts, engineers, and scientists together. Enable self-service analytics and operationalize machine learning. Get results today and build for tomorrow. Dataiku DSS is the collaborative data science software platform for teams of data scientists, data analysts, and engineers to explore, prototype, build, and deliver their own data products more efficiently. Use notebooks (Python, R, Spark, Scala, Hive, etc.) or a customizable drag-and-drop visual interface at any step of the predictive dataflow prototyping process – from wrangling to analysis to modeling. Profile the data visually at every step of the analysis. Interactively explore and chart your data using 25+ built-in charts. Prepare, enrich, blend, and clean data using 80+ built-in functions. Leverage Machine Learning technologies (Scikit-Learn, MLlib, TensorFlow, Keras, etc.) in a visual UI. Build & optimize models in Python or R and integrate any external ML library through code APIs.

The biggest challenge to scaling AI-powered decision-making is unused data. IBM Cloud Pak® for Data is a unified platform that delivers a data fabric to connect and access siloed data on-premises or across multiple clouds without moving it. Simplify access to data by automatically discovering and curating it to deliver actionable knowledge assets to your users, while automating policy enforcement to safeguard use. Further accelerate insights with an integrated modern cloud data warehouse. Universally safeguard data usage with privacy and usage policy enforcement across all data. Use a modern, high-performance cloud data warehouse to achieve faster insights. Empower data scientists, developers and analysts with an integrated experience to build, deploy and manage trustworthy AI models on any cloud. Supercharge analytics with Netezza, a high-performance data warehouse.

Mind Foundry is an artificial intelligence company operating at the intersection of research, innovation, and usability to empower teams with AI that is built for humans. Founded by world-leading academics, Mind Foundry develops AI solutions that help organisations in the public and private sectors tackle high-stakes problems, focusing on human outcomes and the long-term impact of AI interventions. Our intrinsically collaborative platform powers AI design, testing and deployment and enables stakeholders to manage their AI investment responsibly with key focus on performance, efficiency and ethical impact. Built on a cornerstone of scientific principles and an understanding that you can’t add things like ethics and transparency after the fact. The fusion of experience design and quantitative methods that makes collaboration between humans and AI more intuitive, efficient and powerful.

Create customized monitors for your machine learning models with our magically-simple monitor builder, and get alerts for issues like concept drift, model performance degradation, bias and more. Aporia integrates seamlessly with any ML infrastructure. Whether it’s a FastAPI server on top of Kubernetes, an open-source deployment tool like MLFlow or a machine learning platform like AWS Sagemaker. Zoom into specific data segments to track model behavior. Identify unexpected bias, underperformance, drifting features and data integrity issues. When there are issues with your ML models in production, you want to have the right tools to get to the root cause as quickly as possible. Go beyond model monitoring with our investigation toolbox to take a deep dive into model performance, data segments, data stats or distribution.

Enable observability to detect data and ML issues faster, deliver continuous improvements, and avoid costly incidents. Start with reliable data. Continuously monitor any data-in-motion for data quality issues. Pinpoint data and model drift. Identify training-serving skew and proactively retrain. Detect model accuracy degradation by continuously monitoring key performance metrics. Identify risky behavior in generative AI applications and prevent data leakage. Protect your generative AI applications are safe from malicious actions. Improve AI applications through user feedback, monitoring, and cross-team collaboration. Integrate in minutes with purpose-built agents that analyze raw data without moving or duplicating it, ensuring privacy and security. Onboard the WhyLabs SaaS Platform for any use cases using the proprietary privacy-preserving integration. Security approved for healthcare and banks.

Our platform dynamically assesses and mitigates AI risks in models and datasets concerning bias, proxy bias and fairness. Our Responsible AI technology enables deeper visibility into AI models and makes them explainable and interpretable. Our research-based AI robustness assurance algorithms identify and mitigate risks related to lack of robustness. Our platform reviews AI landscape about various AI and MRM regulations and provides deeper risk analysis, comprehensive reporting, and automated remediation. AI risks across in-house AI systems as well as AI systems provided by third parties need to be assessed and remediated. SigmaRed platform enables comprehensive third-party AI risk management (AI TPRM) and rapidly reduces the cycle time of conducting AI risk assessments while providing deep visibility, control, stakeholder-based reporting, and detailed evidence repository.

55% of organizations are adopting AI to stay competitive. Harmonic ensures you're not left behind by equipping security teams with robust tools for secure implementation. As employees embrace new tools, especially from remote locations, Harmonic extends your security reach, ensuring no shadow AI escapes detection. Mitigate the risks of data exposure and maintain compliance with Harmonic's advanced safeguards, keeping your sensitive information secure and private. Traditional data security methods are failing to keep pace with the rapid advancements in AI. Many security teams find themselves stuck using broad, restrictive measures that severely impact productivity. Harmonic provides a smarter alternative. Our solutions are designed to give security professionals the tools and visibility they need to safeguard sensitive, unstructured data effectively, without compromising on efficiency.

Build, run and manage AI models, and optimize decisions at scale across any cloud. IBM Watson Studio empowers you to operationalize AI anywhere as part of IBM Cloud Pak® for Data, the IBM data and AI platform. Unite teams, simplify AI lifecycle management and accelerate time to value with an open, flexible multicloud architecture. Automate AI lifecycles with ModelOps pipelines. Speed data science development with AutoAI. Prepare and build models visually and programmatically. Deploy and run models through one-click integration. Promote AI governance with fair, explainable AI. Drive better business outcomes by optimizing decisions. Use open source frameworks like PyTorch, TensorFlow and scikit-learn. Bring together the development tools including popular IDEs, Jupyter notebooks, JupterLab and CLIs — or languages such as Python, R and Scala. IBM Watson Studio helps you build and scale AI with trust and transparency by automating AI lifecycle management.

Accelerate the end-to-end machine learning lifecycle. Empower developers and data scientists with a wide range of productive experiences for building, training, and deploying machine learning models faster. Accelerate time to market and foster team collaboration with industry-leading MLOps—DevOps for machine learning. Innovate on a secure, trusted platform, designed for responsible ML. Productivity for all skill levels, with code-first and drag-and-drop designer, and automated machine learning. Robust MLOps capabilities that integrate with existing DevOps processes and help manage the complete ML lifecycle. Responsible ML capabilities – understand models with interpretability and fairness, protect data with differential privacy and confidential computing, and control the ML lifecycle with audit trials and datasheets. Best-in-class support for open-source frameworks and languages including MLflow, Kubeflow, ONNX, PyTorch, TensorFlow, Python, and R.

The Grace Enterprise AI Platform, the AI platform with full support for Governance, Risk & Compliance (GRC) for AI. Grace offers an efficient, secure, and robust AI implementation across any organization, standardizing processes, and workflows across all your AI projects. Grace covers the full range of rich functionality your organization needs to become fully AI proficient and helps ensure regulatory excellence for AI, to avoid compliance requirements slowing or stopping AI implementation. Grace lowers the entry barriers for AI users across all functional and operational roles in your organization, including technical, IT, project management, and compliance, while still offering efficient workflows for experienced data scientists and engineers. Ensuring that all activities are traced, explained, and enforced. This includes all areas within the data science model development, data used for model training and development, model bias, and more.

Quality assurance for machine learning simplified. Snitch removes the noise to surface only the most useful information to improve your models. Track your model’s performance beyond just accuracy with powerful dashboards and analysis. Identify problems in your data pipeline and distribution shifts before they affect your predictions. Stay in production once you’ve deployed and gain visibility on your models & data throughout its cycle. Keep your data secure, cloud, on-prem, private cloud, hybrid, and you decide how to install Snitch. Work within the tools you love and integrate Snitch into your MLops pipeline! Get up and running quickly, we keep installation, learning, and running the product easy as pie. Accuracy can often be misleading. Look into robustness and feature importance to evaluate your models before deploying. Gain actionable insights to improve your models. Compare against historical metrics and your models’ baseline.

Get in minutes what used to take years to build. Simple, customizable, scalable, secure, ML monitoring. Everything you need to deploy, maintain and improve ML in production. Superwise is an open platform that integrates with any ML stack and connects to your choice of communication tools. Want to take it further? Superwise is API-first and everything (and we mean everything) is accessible via our APIs. All from the comfort of the cloud of your choice. When it comes to ML monitoring you have full self-service control over everything. Configure metrics and policies through our APIs and SDK or simply select a monitoring template and set the sensitivity, conditions, and alert channels of your choice. Try Superwise out or contact us to learn more. Easily create alerts with Superwise’s ML monitoring policy templates and builder. Select from dozens of pre-build monitors ranging from data drift to equal opportunity, or customize policies to incorporate your domain expertise.

Harness the power of Qlik® Staige™ to make AI real by delivering a trusted data foundation, automation, actionable predictions, and company-wide impact. AI isn’t just experiments and initiatives — it’s an entire ecosystem of files, scripts, and results. Wherever your investments, we’ve partnered with top sources to bring you integrations that save time, enable management, and validate quality. Automate the delivery of real-time data into AWS data warehouses or data lakes, and make it easily accessible through a governed catalog. Through our new integration with Amazon Bedrock, you can easily connect to foundational large language models (LLMs) including A21 Labs, Amazon Titan, Anthropic, Cohere, and Meta. Seamless integration with Amazon Bedrock makes it easier for AWS customers to leverage large language models with analytics for AI-driven insights.

The Domino platform helps data science teams improve the speed, quality, and impact of data science at scale. Domino is open and flexible, empowering professional data scientists to use their preferred tools and infrastructure. Data science models get into production fast and are kept operating at peak performance with integrated workflows. Domino also delivers the security, governance and compliance that enterprises expect. The Self-Service Infrastructure Portal makes data science teams become more productive with easy access to their preferred tools, scalable compute, and diverse data sets. The Integrated Model Factory includes a workbench, model and app deployment, and integrated monitoring to rapidly experiment, deploy the best models in production, ensure optimal performance, and collaborate across the end-to-end data science lifecycle. The System of Record allows teams to easily find, reuse, reproduce, and build on any data science work to amplify innovation.

Azure AI Content Safety is a content moderation platform that uses AI to keep your content safe. Create better online experiences for everyone with powerful AI models that detect offensive or inappropriate content in text and images quickly and efficiently. Language models analyze multilingual text, in both short and long form, with an understanding of context and semantics. Vision models perform image recognition and detect objects in images using state-of-the-art Florence technology. AI content classifiers identify sexual, violent, hate, and self-harm content with high levels of granularity. Content moderation severity scores indicate the level of content risk on a scale of low to high.

NuEnergy.ai’s Machine Trust Platform™ (MTP) is a unique cloud-based software platform to measure, monitor, and build trust in your artificial intelligence (AI) technology, whether you’re developing it, procuring it, or deploying it. MTP measures essential trust parameters including privacy, ethics, transparency, and bias metrics and protects against the risks of AI drift. The software lets you assess your AI technologies against key risk-mitigating metrics, third-party frameworks, and standards to help ensure governance, ethical and regulatory guidelines are met. It offers flexibility and scope for configurations to ensure you have compatibility to enhance trust in your AI technologies. Global standards, including the Government of Canada Algorithmic Impact Assessment (AIA), are integrated into the platform, which can be customized to include other relevant governance standards. You can choose from an ever-growing list of NuEnergy.ai’s library of qualified AI trust tools.

Fiddler is a pioneer in Model Performance Management for responsible AI. The Fiddler platform’s unified environment provides a common language, centralized controls, and actionable insights to operationalize ML/AI with trust. Model monitoring, explainable AI, analytics, and fairness capabilities address the unique challenges of building in-house stable and secure MLOps systems at scale. Unlike observability solutions, Fiddler 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, build trusted AI solutions, and increase revenue.

Unlocking the power of fully homomorphic encryption for financial institutions. Imagine a world where you can extract insights from your data and perform advanced analytics without worrying about data leakage, attacks and compliance. With Nitromia’s fully homomorphic cryptography, companies perform advanced data science and computations at minimum risk with zero exposure for data at rest and in transit. The Platform. Based on cutting edge fully homomorphic technology, Nitromia’s enablement platform empowers data scientists to run artificial intelligence and machine learning analytics directly on encrypted data. With Nitromia, business insights are extracted and sensitive data is analyzed, all while remaining hidden and secure. Built on the pillars of security, privacy and compliance, the revolutionary platform enables complex calculations and predictive analytics in real time. With Nitromia, financial institutions can finally fully utilize their data with zero risk.

Turn data into answers with Splunk deployed and managed securely, reliably and scalably as a service. With your IT backend managed by our Splunk experts, you can focus on acting on your data. Splunk-provisioned and managed infrastructure delivers a turnkey, cloud-based data analytics solution. Go live in as little as two days. Managed software upgrades ensure you always have the latest functionality. Tap into the value of your data in days with fewer requirements to turn data into action. Splunk Cloud meets the FedRAMP security standards, and helps U.S. federal agencies and their partners drive confident decisions and decisive actions at mission speeds. Drive productivity and contextual insights with Splunk’s mobile apps, augmented reality and natural language capabilities. Extend the utility of your Splunk solutions to any location with a simple phrase or the tap of a finger. From infrastructure management to data compliance, Splunk Cloud is built to scale.

A new category of AI. Most current AI solutions are engineered through a statistical and purely mathematical lens. We took a different approach. With discoveries in information theory, the team at Intelligent Artifacts has built a new category of AI: a true AGI that eliminates current machine intelligence shortcomings. Our framework keeps the data and application layers separate from the intelligence layer allowing it to learn in real-time, and enabling it to explain predictions down to root cause. A true AGI demands a truly integrated platform. With Intelligent Artifacts, you'll model information, not data — predictions and decisions are real-time and transparent, and can be deployed across various domains without the need to rewrite code. And by combining specialized AI consultants with our dynamic platform, you'll get a customized solution that rapidly offers deep insights and greater outcomes from your data.

IBM Watson Machine Learning is a full-service IBM Cloud offering that makes it easy for developers and data scientists to work together to integrate predictive capabilities with their applications. The Machine Learning service is a set of REST APIs that you can call from any programming language to develop applications that make smarter decisions, solve tough problems, and improve user outcomes. Take advantage of machine learning models management (continuous learning system) and deployment (online, batch, streaming). Select any of widely supported machine learning frameworks: TensorFlow, Keras, Caffe, PyTorch, Spark MLlib, scikit learn, xgboost and SPSS. Use the command-line interface and Python client to manage your artifacts. Extend your application with artificial intelligence through the Watson Machine Learning REST API.

Design and develop data-intensive projects with human-friendly, open-source Metaflow. Run, scale, and deploy them reliably on the fully managed Outerbounds platform. One platform for all your ML and data science projects. Access data securely from your existing data warehouses. Compute with a cluster optimized for scale and cost. 24/7 managed orchestration for production workflows. Use results to power any application. Give your data scientists superpowers, approved by your engineers. Outerbounds Platform allows data scientists to develop rapidly, experiment at scale, and deploy to production confidently. All within the outer bounds of policies and processes defined by your engineers, running on your cloud account, fully managed by us. Security is in our DNA, not at the perimeter. The platform adapts to your policies and compliance requirements through multiple layers of security. Centralized auth, a strict permission boundary, and granular task execution roles.

Emly Labs is an AI framework designed to make AI accessible for users at all technical levels through a user-friendly platform. It offers AI project management with tools for guided workflows and automation for faster execution. The platform encourages team collaboration and innovation, provides no-code data preparation, and integrates external data for robust AI models. Emly AutoML automates data processing and model evaluation, reducing human input. It prioritizes transparency, with explainable AI features and robust auditing for compliance. Security measures include data isolation, role-based access, and secure integrations. Additionally, Emly's cost-effective infrastructure allows on-demand resource provisioning and policy management, enhancing experimentation and innovation while reducing costs and risks.

A machine learning monitoring solution that helps you easily oversee and troubleshoot high model volumes. With explainability accuracy that’s unparalleled and unique analyses that are not available anywhere else, data scientists avoid false alarms and dead ends, addressing critical problems quickly and effectively. Your machine learning models stay optimized, so that your business is optimized. TruEra’s solution is based on an explainability engine that, due to years of dedicated research and development, is significantly more accurate than current tools. TruEra’s enterprise-class AI explainability technology is without peer. The core diagnostic engine is based on six years of research at Carnegie Mellon University and dramatically outperforms competitors. The platform quickly performs sophisticated sensitivity analysis that enables data scientists, business users, and risk and compliance teams to understand exactly how and why a model makes predictions.

Scale your machine learning development from research to production with an end-to-end solution that gives your data science team all the tools they need in one place. As the leading data science platform for MLOps and model management, cnvrg.io is a pioneer in building cutting-edge machine learning development solutions so you can build high-impact machine learning models in half the time. Bridge science and engineering teams in a clear and collaborative machine learning management environment. Communicate and reproduce results with interactive workspaces, dashboards, dataset organization, experiment tracking and visualization, a model repository and more. Focus less on technical complexity and more on building high impact ML models. Cnvrg.io container-based infrastructure helps simplify engineering heavy tasks like tracking, monitoring, configuration, compute resource management, serving infrastructure, feature extraction, and model deployment.

Semantria is a natural language processing (NLP) API from Lexalytics, leaders in enterprise sentiment analysis and text analytics since 2004. Semantria offers multi-layered sentiment analysis, categorization, entity recognition, theme analysis, intention detection and summarization in an easy-to-integrate RESTful API package. Semantria is totally customizable through graphical configuration tools, supports 24 languages, and can be deployed across private, public and hybrid clouds. Semantria scales effortlessly from single servers to entire data centers and back again to meet your on-demand processing needs. Integrate Semantria to add powerful, flexible text analytics and natural language processing capabilities to your cloud-based data analytics products or enterprise business intelligence infrastructure. Or add Lexalytics storage and visualization tools to create a complete business intelligence platform for storing, managing, analyzing and visualizing text documents.

Deploy machine learning applications to production in minutes, rather than months. Automate the transformation of raw data, generate training data sets, and serve features for online inference at scale. Save months of work by replacing bespoke data pipelines with robust pipelines that are created, orchestrated and maintained automatically. Increase your team’s efficiency by sharing features across the organization and standardize all of your machine learning data workflows in one platform. Serve features in production at extreme scale with the confidence that systems will always be up and running. Tecton meets strict security and compliance standards. Tecton is not a database or a processing engine. It plugs into and orchestrates on top of your existing storage and processing infrastructure.

We help developers solve the world’s most important problems by unlocking the value from sensitive data, without increasing risk. ‍ That's why we're building tools for privacy-safe machine learning and analytics for the distributed future of data. Data of all types are being generated and stored in the cloud, on prem, and increasingly at the edge. The cost of de-identifying, moving, centrally storing, and managing high volumes of data can be prohibitive. HIPAA, GDPR, PIPEDA, CCPA and other regulations limit the ways data can come together, especially across jurisdictions. With federated learning and analytics, only model parameters leave each private server, so data custodians retain full control of their data. Grow your business with existing customers by building valuable new product features that harness the collective intelligence of your customers' data.

The Zinia artificial intelligence platform connects the dots between the key business decision maker and AI. You can now build your trusted AI models without depending on technical teams and ensure alignment of AI with business objectives. Ground-breaking technology simplified to help you build AI backwards from business. Improves revenue by 15-20% and increases efficiency by cutting AI implementation time from months to days. Zinia optimises business outcomes with human-centered AI. Most AI development in organisations is misaligned with business KPIs. Zinia is built with the vision to address this key problem by democratising AI for you. Zinia brings business fit cutting-edge ML and AI Technology into your hands. Built by a team with more than 50 years of experience in AI, Zinia is your trusted platform that simplifies ground-breaking technology and gives you the fastest path from data to business decisions.

Make your offline data available for real-time predictions without having to build custom pipelines. Ensure data consistency between offline training and online inference, eliminating train-serve skew. Standardize data engineering workflows under one consistent framework. Teams use Feast as the foundation of their internal ML platforms. Feast doesn’t require the deployment and management of dedicated infrastructure. Instead, it reuses existing infrastructure and spins up new resources when needed. You are not looking for a managed solution and are willing to manage and maintain your own implementation. You have engineers that are able to support the implementation and management of Feast. You want to run pipelines that transform raw data into features in a separate system and integrate with it. You have unique requirements and want to build on top of an open source solution.

Simplify your MLOps pipelines. Manage, deploy, and scale on any infrastructure with ZenML. ZenML is completely free and open-source. See the magic with just two simple commands. Set up ZenML in a matter of minutes, and start with all the tools you already use. ZenML standard interfaces ensure that your tools work together seamlessly. Gradually scale up your MLOps stack by switching out components whenever your training or deployment requirements change. Keep up with the latest changes in the MLOps world and easily integrate any new developments. Define simple and clear ML workflows without wasting time on boilerplate tooling or infrastructure code. Write portable ML code and switch from experimentation to production in seconds. Manage all your favorite MLOps tools in one place with ZenML's plug-and-play integrations. Prevent vendor lock-in by writing extensible, tooling-agnostic, and infrastructure-agnostic code.

At the intersection of data governance, privacy, and security, Privacera’s unified data access governance platform maximizes the value of data by providing secure data access control and governance across hybrid- and multi-cloud environments. The hybrid platform centralizes access and natively enforces policies across multiple cloud services—AWS, Azure, Google Cloud, Databricks, Snowflake, Starburst and more—to democratize trusted data enterprise-wide without compromising compliance with regulations such as GDPR, CCPA, LGPD, or HIPAA. Trusted by Fortune 500 customers across finance, insurance, retail, healthcare, media, public and the federal sector, Privacera is the industry’s leading data access governance platform that delivers unmatched scalability, elasticity, and performance. Headquartered in Fremont, California, Privacera was founded in 2016 to manage cloud data privacy and security by the creators of Apache Ranger™ and Apache Atlas™.

Qwak simplifies the productionization of machine learning models at scale. Qwak’s [ML Engineering Platform] empowers data science and ML engineering teams to enable the continuous productionization of models at scale. By abstracting the complexities of model deployment, integration and optimization, Qwak brings agility and high-velocity to all ML initiatives designed to transform business, innovate, and create competitive advantage. Qwak build system allows data scientists to create an immutable, tested production-grade artifact by adding "traditional" build processes. Qwak build system standardizes a ML project structure that automatically versions code, data, and parameters for each model build. Different configurations can be used to build different builds. It is possible to compare builds and query build data. You can create a model version using remote elastic resources. Each build can be run with different parameters, different data sources, and different resources. Builds c