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Platform MLOpsAI Model Deployment & ServingData IntegrityAI ObservabilityLLM EvaluationExplainabilityRAG Applications Stream ProcessingData TransformationOpen Source AI MonitoringAI GatewaySolutions ResourcesBlogDocsGlossary Contact UsContact UsGithub RadicalbitGet Demo EnglishItaliano Platform MLOpsAI Model Deployment & ServingData IntegrityAI ObservabilityLLM EvaluationExplainabilityRAG Applications Stream ProcessingData TransformationOpen Source AI MonitoringAI GatewaySolutions ResourcesBlogDocsGlossary Contact UsContact UsGithub RadicalbitGet Demo EnglishItaliano Your ready-to-use MLOps platformfor Machine Learningfor Computer Visionfor LLMsDeploy & Serve at scale.Observe & Explain in real-time.Reduce Time-to-Value for your AI applications.Book Your Demo Simpler, Faster, Better MLOpsRadicalbit is the MLOps & AI Observability platform that supercharges the deployment, serving, observability and explainability of your AI models. It helps your data teams maintain full control over the whole data lifecycle with real-time data exploration, outlier & drift detection, and model monitoring in production. Seamlessly integrate Radicalbit in your ML stack, SaaS or on-prem, and start running your AI applications in minutes. 92% Faster Time-to-ValueAchieved on average when deploying ML Pipelines to AI-powered applicationsCost ReductionSave time and avoid obsolescence with automations, outlier & drift detection, and metric monitoringScalability & Sustainability Adjust your workloads and save energy with scale-to-zero and automated resource managementControl & GovernanceTimely identify potential issues and risks, using advanced monitoring & observability. Explain models and achieve fairness.Deploy & Serve AI ModelsTransform DataEnforce Data IntegrityScore PredictionsMonitor & ObserveExplain BehaviorCreate & Monitor RAG AppsDeploy & Serve AI ModelsLeverage Radicalbit’s UI or APIs to upload your own MLflow model or import ready-made models from Hugging Face.Learn More »Transform DataDesign and run real-time data transformation pipelinesin our visual canva with prebuilt operators or custom Python Code.Learn More »Enforce Data IntegrityEnsure data integrity mitigating data & concept drift.Identify missing values and outliers. Manage ranges and schema evolution.Learn More »Score PredictionsRun model inference via pipelines or APIs, securely storing bothonline and offline features and predictions within our built-in feature store.Monitor & ObserveTrack model activity and performance for Machine Learning, Computer Vision, and LLMs. Achieve Continual Learning by auto-triggering retraining when performance declines.Learn More »Explain BehaviorClearly understand the output of AI models to avoid bias, achieve compliance and optimize business processes.Learn More »Create & Monitor RAG AppsCombine LLMs with your knowledge bases by developing and monitoring custom RAG applications with Radicalbit.Learn More »Deploy & Serve AI ModelsLeverage Radicalbit’s UI or APIs to upload your own MLflow model or import ready-made models from Hugging Face.Learn More >Transform DataDesign and run real-time data transformation pipelines in our visual canva with prebuilt-in operators or custom Python Code.Learn More >Enforce Data IntegrityEnsure data integrity mitigating data & concept drift. Identify missing values and outliers. Manage ranges and schema evolution.Learn More >Score PredictionsRun model inference via pipelines or APIs, securely storing both online and offline features and predictions within our built-in feature store.Monitor & ObserveTrack model activity and performance for Machine Learning, Computer Vision, and LLMs. Achieve Continual Learning by auto-triggering retraining when performance declines.Learn More >Explain BehaviorClearly understand the output of AI models to avoid bias, achieve compliance and optimize business processes.Learn More >Create & Monitor RAG Apps Combine LLMs with your knowledge bases by developing and monitoring custom RAG applications with Radicalbit.Learn More >Our latest content Read allPrevious From Bill Shock to Actionable Intelligence: LLM Usage Controlby valedellavalle | Mar 6, 2026 | Blog, by Radicalbit, Technology | 0 CommentsThe rapid integration of Large Language Models (LLMs) into the enterprise fabric has shifted the conversation from what is possible to what is sustainable. While early...Read More The Gateway as Your Central AI Security Hubby valedellavalle | Feb 13, 2026 | Blog, by Radicalbit, Technology | 0 CommentsThe rapid integration of Large Language Models (LLMs) into the enterprise tech stack has mirrored the early days of Shadow IT, when the speed of adoption often outpaced...Read More Scaling Generative AI in Banking with an AI Gatewayby valedellavalle | Jan 20, 2026 | Blog, by Radicalbit, Technology | 0 CommentsThe primary challenge for leadership in the financial sector has shifted. It is no longer about proving that Large Language Models (LLMs) can function: it is about...Read More Navigating the AI Act: How to Implement AI Compliance and Governance with an AI Gatewayby valedellavalle | Dec 12, 2025 | Blog, by Radicalbit, Technology | 0 CommentsThe European Union's AI Act has fundamentally altered the landscape of AI deployment. As these regulations transition from legislative text to enforceable law,...Read More The Composable AI Stack: Why Monoliths are Falling Behindby valedellavalle | Nov 18, 2025 | Blog, by Radicalbit, Technology | 0 CommentsThe landscape of Artificial Intelligence is evolving quickly, driven by the explosive capabilities of LLMs and generative tools. However, the architectures needed to...Read More Gaining Full Observability into Your LLM-Powered Apps: Metrics, Tracing, and Loggingby valedellavalle | Oct 21, 2025 | by Radicalbit, Technology | 0 CommentsGenerative AI and Large Language Models (LLMs) are rapidly transforming enterprise applications, offering unprecedented power and paving the way for revolutionary user...Read More Enforcing Data Privacy in Your LLM Applications: PII Redaction and Anonymization at the Gateway Levelby valedellavalle | Oct 8, 2025 | by Radicalbit, Technology | 0 CommentsAs a data scientist or engineer, you live at the frontier of innovation. Your goal is to harness the unprecedented power of LLMs to build intelligent applications that...Read More Optimizing LLM Performance with Caching, Fallback, and Load Balancingby valedellavalle | Sep 25, 2025 | Authors, by Radicalbit, Technology | 0 CommentsIn the initial gold rush to deploy Generative AI, the primary focus was capability. Can the model generate accurate code, draft compelling marketing copy, or provide...Read More LLM Cost Control: Practical LLMOps Strategies for Monitoring API Spendby Daniele Croci | Sep 15, 2025 | Authors, by Radicalbit, Technology | 0 CommentsThe decision to integrate Large Language Models (LLMs) into your products and workflows was likely driven by the immense promise of transformative innovation. The...Read More Supercharging LLMs: From Prompt Engineering to Context Engineeringby Daniele Croci | Jul 29, 2025 | by D. Croci, Product | 0 CommentsThe world of LLMs is in a constant state of flux. New models, techniques, and philosophies emerge at a breakneck pace, each promising to unlock even greater potential...Read More New: Agent Tracing, More Powerful LLM Monitoring & Moreby Daniele Croci | Jul 24, 2025 | Authors, by D. Croci, Product | 0 CommentsWe are proud to announce the 1.3.0 release of Radicalbit AI Monitoring, our open source solution that helps data teams measure the effectiveness and reliability of...Read More 5 Ways to Ensure Data Governance in AI Applicationsby Daniele Croci | Jul 10, 2025 | Authors, by Radicalbit, Technology | 0 CommentsIn the relentless pursuit of competitive advantage, artificial intelligence has transitioned from a futuristic buzzword to a cornerstone of modern business strategy....Read MoreNext123456789Our latest contentPrevious From Bill Shock to Actionable Intelligence: LLM Usage Controlby valedellavalle | Mar 6, 2026 | Blog, by Radicalbit, Technology | 0 CommentsThe rapid integration of Large Language Models (LLMs) into the enterprise fabric has shifted the conversation from what is possible to what is sustainable. While early...Read More The Gateway as Your Central AI Security Hubby valedellavalle | Feb 13, 2026 | Blog, by Radicalbit, Technology | 0 CommentsThe rapid integration of Large Language Models (LLMs) into the enterprise tech stack has mirrored the early days of Shadow IT, when the speed of adoption often outpaced...Read More Scaling Generative AI in Banking with an AI Gatewayby valedellavalle | Jan 20, 2026 | Blog, by Radicalbit, Technology | 0 CommentsThe primary challenge for leadership in the financial sector has shifted. It is no longer about proving that Large Language Models (LLMs) can function: it is about...Read More Navigating the AI Act: How to Implement AI Compliance and Governance with an AI Gatewayby valedellavalle | Dec 12, 2025 | Blog, by Radicalbit, Technology | 0 CommentsThe European Union's AI Act has fundamentally altered the landscape of AI deployment. As these regulations transition from legislative text to enforceable law,...Read More The Composable AI Stack: Why Monoliths are Falling Behindby valedellavalle | Nov 18, 2025 | Blog, by Radicalbit, Technology | 0 CommentsThe landscape of Artificial Intelligence is evolving quickly, driven by the explosive capabilities of LLMs and generative tools. However, the architectures needed to...Read More Gaining Full Observability into Your LLM-Powered Apps: Metrics, Tracing, and Loggingby valedellavalle | Oct 21, 2025 | by Radicalbit, Technology | 0 CommentsGenerative AI and Large Language Models (LLMs) are rapidly transforming enterprise applications, offering unprecedented power and paving the way for revolutionary user...Read More Enforcing Data Privacy in Your LLM Applications: PII Redaction and Anonymization at the Gateway Levelby valedellavalle | Oct 8, 2025 | by Radicalbit, Technology | 0 CommentsAs a data scientist or engineer, you live at the frontier of innovation. Your goal is to harness the unprecedented power of LLMs to build intelligent applications that...Read More Optimizing LLM Performance with Caching, Fallback, and Load Balancingby valedellavalle | Sep 25, 2025 | Authors, by Radicalbit, Technology | 0 CommentsIn the initial gold rush to deploy Generative AI, the primary focus was capability. Can the model generate accurate code, draft compelling marketing copy, or provide...Read More LLM Cost Control: Practical LLMOps Strategies for Monitoring API Spendby Daniele Croci | Sep 15, 2025 | Authors, by Radicalbit, Technology | 0 CommentsThe decision to integrate Large Language Models (LLMs) into your products and workflows was likely driven by the immense promise of transformative innovation. The...Read More Supercharging LLMs: From Prompt Engineering to Context Engineeringby Daniele Croci | Jul 29, 2025 | by D. Croci, Product | 0 CommentsThe world of LLMs is in a constant state of flux. New models, techniques, and philosophies emerge at a breakneck pace, each promising to unlock even greater potential...Read More New: Agent Tracing, More Powerful LLM Monitoring & Moreby Daniele Croci | Jul 24, 2025 | Authors, by D. Croci, Product | 0 CommentsWe are proud to announce the 1.3.0 release of Radicalbit AI Monitoring, our open source solution that helps data teams measure the effectiveness and reliability of...Read More 5 Ways to Ensure Data Governance in AI Applicationsby Daniele Croci | Jul 10, 2025 | Authors, by Radicalbit, Technology | 0 CommentsIn the relentless pursuit of competitive advantage, artificial intelligence has transitioned from a futuristic buzzword to a cornerstone of modern business strategy....Read MoreNext Read allSeamless Integration, Out-of-the-Box flexibilitySaaS or On-PremDeploy Radicalbit platform as SaaS or on-prem, whether on your private cloud or your own infrastructurePlug & PlayEasily plug Radicalbit into your AI stack and work with self trained MLflow models, or directly import them from Hugging FaceLow-Code & APIsAccess Radicalbit’s features both via intuitive visual UI and APIs, supporting industry-standard languages such as Python, Java, and JavaScript. Enhancing Observabilityto Embrace Regulations The Radicalbit MLOps platform offers advanced monitoring, observability and explainability features that provide deep insights into your AI models, ensuring that they adhere to the emerging regulatory requirements such as the European Union AI Act. Paving the way for responsible AI practices, Radicalbit empowers you to run and manage AI applications that adhere to the highest standards of fairness, transparency and accountability. Learn MoreWe’re proud to work with some of the most innovative companies in the data & AI world Discover the MLOps & AI Observability Toolbox for your AI ApplicationsBook a Demo Platform AI Model Deployment & ServingData TransformationData IntegrityAI ObservabilityLLM EvaluationExplainabilityRAG ApplicationsOpen Source AI MonitoringAI GatewaySolutions SolutionsResources BlogDocsGlossaryContact Us Contact Us Platform AI Model Deployment & ServingData TransformationData IntegrityAI ObservabilityLLM EvaluationExplainabilityRAG ApplicationsOpen Source AI MonitoringAI GatewaySolutions SolutionsResources BlogDocsGlossaryContact Us Contact UsPrivacy Policy - Cookie Policy©2025 Radicalbit is owned and operated by Fortitude Group Srl.All rights reserved VAT IT04268680263FollowFollowFollowFollowFollow × We (www.radicalbit.ai (owned an operated by Fortitude Group)) and selected third parties (14) use cookies or similar technologies for technical purposes and, with your consent, for functionality, experience, measurement and “marketing (personalized ads)” as specified in the cookie policy. You can freely give, deny, or withdraw your consent at any time by accessing the preferences panel. Denying consent may make related features unavailable.Use the “Accept all” button to consent. Use the “Reject all” button to continue without accepting.NecessaryFunctionalityExperienceMeasurementMarketingPress again to continue 0/1Learn moreReject allAccept all --- Deploy and Serve your Generative and Predictive AI models in a Fraction of the TimeEmpower DevOps and ML engineering teams to streamline AI model deployment & serving operations.Let your data teams focus on delivery, not process, and reduce your time-to-value by up to 92%. Book a Demo Manage Your AI Model ArtifactsVersion the models, perform A/B testing by deploying and serving different versions in parallel. Split the traffic using techniques such as multi-armed bandits, shadows, and canaries.Deploy Models Trained with Your Favorite FrameworksDeploy and serve your artifacts by serializing models using the MLflow Models API or by importing directly from the Hugging Face repository. Deploy Models Trained with Your Favorite FrameworksDeploy and serve your artifacts by serializing models using the MLflow Models API or by importing directly from the Hugging Face repository. Accelerate & Simplify AI Model DeploymentDeploy your models in seconds using Radicalbit’s visual UI or the proprietary APIs. Take advantage of native support for your favorite CI/CD solution.Integrate AI into Your ApplicationsSeamlessly incorporate your ML, LLM, and CV models into your AI-powered applications with the built-in APIs available in the most popular languages such as Python. Integrate AI into Your ApplicationsSeamlessly incorporate your ML, LLM, and CV models into your AI-powered applications with the built-in APIs available in the most popular languages such as Python. Run Radicalbit in the Cloud or On-PremisesRun and efficiently scale your workloads wherever you prefer, whether in the Radicalbit Platform Cloud, your private cloud, or on-premises.Talk to our experts and discover Radicalbit’s advanced AI Model Serving and Deployment capabilities!Book a Demo AI Model Deployment Data Integrity AI Observability LLM Evaluation Explainability RAG Apps × We (www.radicalbit.ai (owned an operated by Fortitude Group)) and selected third parties (14) use cookies or similar technologies for technical purposes and, with your consent, for functionality, experience, measurement and “marketing (personalized ads)” as specified in the cookie policy. You can freely give, deny, or withdraw your consent at any time by accessing the preferences panel. Denying consent may make related features unavailable.Use the “Accept all” button to consent. Use the “Reject all” button to continue without accepting.NecessaryFunctionalityExperienceMeasurementMarketingPress again to continue 0/1Learn moreReject allAccept all --- Safeguard AI Decisions with Real-time Data IntegrityEnsure the reliability and trustworthiness of your AI models by maintaining real-time data integrity. Radicalbit continuously monitors and validates batch and streaming data, protecting your models from inaccurate or corrupted data that could compromise their effectiveness. Book a Demo Guarantee Data ReliabilityEnsure the trustworthiness of your AI models by safeguarding data integrity in real time. Continuously monitor and validate incoming data to prevent errors, inconsistencies, or anomalies from impacting model performance.Enforce Data GovernanceImplement robust data governance policies to maintain data quality and consistency. Enforce data schema evolution and schema enforcement rules in real time to ensure data adheres to established standards. Enforce Data GovernanceImplement robust data governance policies to maintain data quality and consistency. Enforce data schema evolution and schema enforcement rules in real time to ensure data adheres to established standards. Detect Drift, Outliers, and AnomaliesIdentify and address outliers, data drift, and missing values in real time. Utilize advanced algorithms to detect anomalies and alert users of potential data quality issues before they affect AI models.Protect Against Data CorruptionSafeguard your AI models from corrupted or inaccurate data. Implement real-time data validation processes to detect and prevent the ingestion of corrupted data, ensuring model integrity and reliability. Protect Against Data CorruptionSafeguard your AI models from corrupted or inaccurate data. Implement real-time data validation processes to detect and prevent the ingestion of corrupted data, ensuring model integrity and reliability. Enable Proactive RemediationReact promptly to data integrity issues with an integrated alerting system. Receive real-time alerts for detected anomalies, allowing for swift investigation and remediation before they impact AI model performance.Start safeguarding Data Integrity for real, talk to our product experts now!Book a Demo AI Model Deployment Data Integrity AI Observability LLM Evaluation Explainability RAG Apps × We (www.radicalbit.ai (owned an operated by Fortitude Group)) and selected third parties (14) use cookies or similar technologies for technical purposes and, with your consent, for functionality, experience, measurement and “marketing (personalized ads)” as specified in the cookie policy. You can freely give, deny, or withdraw your consent at any time by accessing the preferences panel. Denying consent may make related features unavailable.Use the “Accept all” button to consent. Use the “Reject all” button to continue without accepting.NecessaryFunctionalityExperienceMeasurementMarketingPress again to continue 0/1Learn moreReject allAccept all --- Drive situational awareness with Comprehensive Observability and Monitoring for ML, LLMs, and CVElevate your AI initiatives with granular insights into the performance and behavior of your machine learning models, large language models, and computer vision applications. Radicalbit’s observability and monitoring capabilities empower you to proactively identify and resolve issues, optimize model performance, and ensure the reliability of your AI-driven decisions across diverse domains. Book Your Demo Monitor Model PerformanceProactively identify performance degradation in your models by tracking metrics such as Mean Absolute Error (MAE), Mean Squared Error (MSE), Precision, Recall, F1-Score, Intersection over Union (IoU), Jaccard Similarity, Mean Average Precision (mAP), Average Precision (AP), and Confusion Matrix.Detect Data & Concept DriftMonitor data drift to ensure that models are trained on current and relevant data. Advanced observability features help you maintain model accuracy and prevent concept drift, occurring when the underlying relationship between the features and target variable changes over time. Detect Data & Concept DriftMonitor data drift to ensure that models are trained on current and relevant data. Advanced observability features help you maintain model accuracy and prevent concept drift, which occurs when the underlying distribution of the data changes over time. Uncover Hidden BiasesRadicalbit helps you identify and address potential biases, so you can ensure fair and unbiased decision-making, fostering trust in AI-driven applications.Centralize Monitoring & Enhance CooperationLeverage a single MLOps and AI monitoring toolbox for your different data teams, share terminology, and eliminate the operational inefficiencies of siloed solutions. Centralize Monitoring & Enhance CooperationLeverage a single MLOps and AI monitoring toolbox for your different data teams, share terminology, and eliminate the operational inefficiencies of siloed solutions. Visualize Metrics for a Greater UnderstandingImmediately grasp key metrics and performance with Radicalbit’s graphical representation of data. Make data-driven decisions to ultimately optimize your AI models by triggering retraining procedures when your models’ predictions fall short of expected accuracy levels.Want to learn more about Radicalbit’s advanced AI Observability features?Book a Demo AI Model Deployment Data Integrity AI Observability LLM Evaluation Explainability RAG Apps × We (www.radicalbit.ai (owned an operated by Fortitude Group)) and selected third parties (14) use cookies or similar technologies for technical purposes and, with your consent, for functionality, experience, measurement and “marketing (personalized ads)” as specified in the cookie policy. You can freely give, deny, or withdraw your consent at any time by accessing the preferences panel. Denying consent may make related features unavailable.Use the “Accept all” button to consent. Use the “Reject all” button to continue without accepting.NecessaryFunctionalityExperienceMeasurementMarketingPress again to continue 0/1Learn moreReject allAccept all