Best Artificial Intelligence Software for Amazon Redshift - Page 3
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Compare the Top Artificial Intelligence Software that integrates with Amazon Redshift as of November 2025 - Page 3
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This a list of Artificial Intelligence software that integrates with Amazon Redshift. Use the filters on the left to add additional filters for products that have integrations with Amazon Redshift. View the products that work with Amazon Redshift in the table below.
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Privacera
Privacera
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™. -
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Tonic
Tonic
Tonic automatically creates mock data that preserves key characteristics of secure datasets so that developers, data scientists, and salespeople can work conveniently without breaching privacy. Tonic mimics your production data to create de-identified, realistic, and safe data for your test environments. With Tonic, your data is modeled from your production data to help you tell an identical story in your testing environments. Safe, useful data created to mimic your real-world data, at scale. Generate data that looks, acts, and feels just like your production data and safely share it across teams, businesses, and international borders. PII/PHI identification, obfuscation, and transformation. Proactively protect your sensitive data with automatic scanning, alerts, de-identification, and mathematical guarantees of data privacy. Advanced sub setting across diverse database types. Collaboration, compliance, and data workflows — perfectly automated. -
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Feast
Tecton
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. -
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Zepl
Zepl
Sync, search and manage all the work across your data science team. Zepl’s powerful search lets you discover and reuse models and code. Use Zepl’s enterprise collaboration platform to query data from Snowflake, Athena or Redshift and build your models in Python. Use pivoting and dynamic forms for enhanced interactions with your data using heatmap, radar, and Sankey charts. Zepl creates a new container every time you run your notebook, providing you with the same image each time you run your models. Invite team members to join a shared space and work together in real time or simply leave their comments on a notebook. Use fine-grained access controls to share your work. Allow others have read, edit, and run access as well as enable collaboration and distribution. All notebooks are auto-saved and versioned. You can name, manage and roll back all versions through an easy-to-use interface, and export seamlessly into Github. -
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Amazon SageMaker Feature Store is a fully managed, purpose-built repository to store, share, and manage features for machine learning (ML) models. Features are inputs to ML models used during training and inference. For example, in an application that recommends a music playlist, features could include song ratings, listening duration, and listener demographics. Features are used repeatedly by multiple teams and feature quality is critical to ensure a highly accurate model. Also, when features used to train models offline in batch are made available for real-time inference, it’s hard to keep the two feature stores synchronized. SageMaker Feature Store provides a secured and unified store for feature use across the ML lifecycle. Store, share, and manage ML model features for training and inference to promote feature reuse across ML applications. Ingest features from any data source including streaming and batch such as application logs, service logs, clickstreams, sensors, etc.
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Amazon SageMaker Data Wrangler reduces the time it takes to aggregate and prepare data for machine learning (ML) from weeks to minutes. With SageMaker Data Wrangler, you can simplify the process of data preparation and feature engineering, and complete each step of the data preparation workflow (including data selection, cleansing, exploration, visualization, and processing at scale) from a single visual interface. You can use SQL to select the data you want from a wide variety of data sources and import it quickly. Next, you can use the Data Quality and Insights report to automatically verify data quality and detect anomalies, such as duplicate rows and target leakage. SageMaker Data Wrangler contains over 300 built-in data transformations so you can quickly transform data without writing any code. Once you have completed your data preparation workflow, you can scale it to your full datasets using SageMaker data processing jobs; train, tune, and deploy models.
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Robust Intelligence
Robust Intelligence
The Robust Intelligence Platform integrates seamlessly into your ML lifecycle to eliminate model failures. The platform detects your model’s vulnerabilities, prevents aberrant data from entering your AI system, and detects statistical data issues like drift. At the core of our test-based approach is a single test. Each test measures your model’s robustness to a specific type of production model failure. Stress Testing runs hundreds of these tests to measure model production readiness. The results of these tests are used to auto-configure a custom AI Firewall that protects the model against the specific forms of failure to which a given model is susceptible. Finally, Continuous Testing runs these tests during production, providing automated root cause analysis informed by the underlying cause of any single test failure. Using all three elements of the Robust Intelligence platform together helps ensure ML Integrity. -
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Layerup
Layerup
Extract and Transform any data from any data source with Natural Language connect to your data source - everything ranging from your DB to your CRM to your billing solution. Improve Productivity by 5-10x Forget about wasting time on clunky BI tools. Use Natural Language to query any complex data in seconds. Transition from DIY tools to non-DIY AI-powered tools. Generate complex dashboards and reports in a few lines. No more SQL or complex formulas - let Layerup AI do the heavy lifting for you. Layerup not only gives you instant answer to questions that would require 5-40 hours/month on SQL queries, but it will act as your personal data analyst 24/7 while providing you complex dashboards/charts that you can embed anywhere. -
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TextQL
TextQL
The platform indexes BI tools and semantic layers, documents data in dbt, and uses OpenAI and language models to provide self-serve power analytics. With TextQL, non-technical users can easily and quickly work with data by asking questions in their work context (Slack/Teams/email) and getting automated answers quickly and safely. The platform also leverages NLP and semantic layers, including the dbt Labs semantic layer, to ensure reasonable solutions. TextQL's elegant handoffs to human analysts, when required, dramatically simplify the whole question-to-answer process with AI. At TextQL, our mission is to empower business teams to access the data that they're looking for in less than a minute. To accomplish this, we help data teams surface and create documentation for their data so that business teams can trust that their reports are up to date. -
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Qualytics
Qualytics
Helping enterprises proactively manage their full data quality lifecycle through contextual data quality checks, anomaly detection and remediation. Expose anomalies and metadata to help teams take corrective actions. Automatically trigger remediation workflows to resolve errors quickly and efficiently. Maintain high data quality and prevent errors from affecting business decisions. The SLA chart provides an overview of SLA, including the total number of SLA monitoring that have been performed and any violations that have occurred. This chart can help you identify areas of your data that may require further investigation or improvement. -
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Acryl Data
Acryl Data
No more data catalog ghost towns. Acryl Cloud drives fast time-to-value via Shift Left practices for data producers and an intuitive UI for data consumers. Continuously detect data quality incidents in real-time, automate anomaly detection to prevent breakages, and drive fast resolution when they do occur. Acryl Cloud supports both push-based and pull-based metadata ingestion for easy maintenance, ensuring information is trustworthy, up-to-date, and definitive. Data should be operational. Go beyond simple visibility and use automated Metadata Tests to continuously expose data insights and surface new areas for improvement. Reduce confusion and accelerate resolution with clear asset ownership, automatic detection, streamlined alerts, and time-based lineage for tracing root causes. -
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Tantl
Tantl
Allow only specified tables and columns to maintain security and privacy. Tantl is like a helpful colleague working alongside you to help answer data queries. The more it’s used, the better it gets at understanding your data. -
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Modelbit
Modelbit
Don't change your day-to-day, works with Jupyter Notebooks and any other Python environment. Simply call modelbi.deploy to deploy your model, and let Modelbit carry it — and all its dependencies — to production. ML models deployed with Modelbit can be called directly from your warehouse as easily as calling a SQL function. They can also be called as a REST endpoint directly from your product. Modelbit is backed by your git repo. GitHub, GitLab, or home grown. Code review. CI/CD pipelines. PRs and merge requests. Bring your whole git workflow to your Python ML models. Modelbit integrates seamlessly with Hex, DeepNote, Noteable and more. Take your model straight from your favorite cloud notebook into production. Sick of VPC configurations and IAM roles? Seamlessly redeploy your SageMaker models to Modelbit. Immediately reap the benefits of Modelbit's platform with the models you've already built. -
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Genie AI
Genie AI
Harness the power of AI to analyze, summarize, and visualize data without all the complex SQL requirements. Allowing anyone on the team to easily ask any data question and get answers in seconds by connecting to any files, database, or API directly into Slack, Teams, or any workspace. Work 10x as fast with Al while keeping your internal data safe and secure. Self-hosted LLMs that run locally into your infrastructure, customized to your data. Genie ecosystem is built to enforce quality and security alongside spearheading the effort to allow any enterprise to easily train and deploy their own Al. Add your data and query in natural language across multiple tables. Ask follow-up questions and get insights and visualizations in seconds. -
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Qlik Staige
QlikTech
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. -
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Validio
Validio
See how your data assets are used: popularity, utilization, and schema coverage. Get important insights about your data assets such as popularity, utilization, quality, and schema coverage. Find and filter the data you need based on metadata tags and descriptions. Get important insights about your data assets such as popularity, utilization, quality, and schema coverage. Drive data governance and ownership across your organization. Stream-lake-warehouse lineage to facilitate data ownership and collaboration. Automatically generated field-level lineage map to understand the entire data ecosystem. Anomaly detection learns from your data and seasonality patterns, with automatic backfill from historical data. Machine learning-based thresholds are trained per data segment, trained on actual data instead of metadata only. -
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HuLoop
HuLoop
Get data-driven recommendations on your people, processes, and technologies. Set up automation of complex business processes, across disparate systems and data. Automate repetitive tasks to perform testing that is difficult to do manually. HuLoop platform creates, deploys, and manages intelligent agents as a digital workforce to perform repetitive tasks your people should no longer do. HuLoop digital agents can help you lower costs, improve productivity, and increase the job satisfaction of people across your organization. Helps you see, understand, and change your capabilities, as well as understand how your people, processes, and technologies interact. Automation and orchestration of complex business processes, across disparate systems and data, minimizing human dependency. Controls and executes tests and verifies expected outcomes. Automates repetitive tasks and performs testing that is difficult to do manually. -
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Fluent
Fluent
Self-serve your company's data insights with AI. Fluent is your AI data analyst, it helps you explore your data and uncover the questions you should be asking. No complicated UI and no learning curve; just type in your question and Fluent will do the rest. Fluent works with you to clarify your question, so you can get the insight you need. With Fluent, you can uncover the questions you should be asking to get more out of your data. Fluent lets you build a shared understanding of your data, with real-time collaboration and a shared data dictionary. No more silos, no more confusion, and no more disagreements on how to define revenue. Fluent integrates with Slack and Teams, so you can get data insights without leaving your chat. Fluent gives verifiable output with a visual display of the exact SQL journey and AI logic for each query. Curate tailored datasets with clear usage guidelines and quality control, enhancing data integrity and access management. -
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UnifyApps
UnifyApps
Reduce fragmented systems & bridge data silos by enabling your teams to develop complex applications, automate workflows and build data pipelines. Automate complex business processes across applications within minutes. Build and deploy customer-facing and internal applications. Use from a wide range of pre-built rich components. Enterprise-grade security and governance and robust debugging and change management. Build enterprise-grade applications 10x faster without writing code. Automate complex business processes across applications within minutes. Powered by enterprise-grade reliability features like caching, rate limiting, and circuit breakers. Build custom integrations in less than a day with connector SDK. Real-time data replication from any source to the destination system. Instantly move data across applications, data warehouses, or data lakes. Enable preload transformations, and automated schema mapping. -
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Quest
Quest
Empower growth & marketing teams to boost engagement and conversion 10x faster without data or engineering teams. Enhance your app with AI-driven personalized UI, seamlessly integrated with your data stack for a tailored user experience. Tailoring the onboarding process can significantly improve user activation. By considering factors like user roles, company type, and intent, we can create custom quick-start guides and tours. By allowing users to customize menu items or shop items based on their interests and behavior, we can create a personalized browsing experience. By leveraging insights such as purchase history, browsing behavior, and demographics, we can deliver targeted promotions and discounts that resonate with each user. Our analytical models find common traits for users who are not active and create thousands of segments to activate them. Easily find winning variants among millions of variants to power users across the customer journey. -
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Shaped
Shaped
The fastest path to relevant recommendations and search. Increase engagement, conversion, and revenue with a configurable system that adapts in real time. We help your users find what they're looking for by surfacing the products or content that are most relevant to them. We do this whilst taking into account your business objectives to ensure all sides of your platform or marketplace are being optimized fairly. Under the hood, Shaped is a real-time, 4-stage, recommendation system containing all the data and machine-learning infrastructure needed to understand your data and serve your discovery use-case at scale. Connect and deploy rapidly with direct integration to your existing data sources. Ingest and re-rank in real-time using behavioral signals. Fine-tune LLMs and neural ranking models for state-of-the-art performance. Build and experiment with ranking and retrieval components for any use case. -
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Velotix
Velotix
Velotix empowers organizations to maximize the value of their data while ensuring security and compliance in a rapidly evolving regulatory landscape. The Velotix Data Security Platform offers automated policy management, dynamic access controls, and comprehensive data discovery, all driven by advanced AI. With seamless integration across multi-cloud environments, Velotix enables secure, self-service data access, optimizing data utilization without compromising on governance. Trusted by leading enterprises across financial services, healthcare, telecommunications, and more, Velotix is reshaping data governance for the ‘need to share’ era. -
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paretos
paretos
Paretos is the leading AI-based decision-intelligence software for optimized decision-making processes. With paretos, businesses can identify, plan, execute, and track business potentials through automated processes across the entire organization. Our cloud-based decision intelligence platform makes complex data analysis as easily accessible as an email program. Forget complicated AI applications: your data can be quickly and risk-free connected, and the output will be visualized in a user-friendly dashboard. Our software supports you by providing practical feedback and actionable recommendations to improve the quality of your data and your output. Identify all factors that influence your decisions and obtain only the truly optimal solutions based on comparable trade-offs. Paretos automatically sets the required input parameters. From now on, our algorithm runs 24/7 and automatically adjusts your input as needed. -
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Unity Catalog
Databricks
Databricks Unity Catalog is the industry’s only unified and open governance solution for data and AI, built into the Databricks Data Intelligence Platform. With Unity Catalog, organizations can seamlessly govern both structured and unstructured data in any format, as well as machine learning models, notebooks, dashboards, and files across any cloud or platform. Data scientists, analysts, and engineers can securely discover, access, and collaborate on trusted data and AI assets across platforms, leveraging AI to boost productivity and unlock the full potential of the lakehouse environment. This unified and open approach to governance promotes interoperability and accelerates data and AI initiatives while simplifying regulatory compliance. Easily discover and classify both structured and unstructured data in any format, including machine learning models, notebooks, dashboards, and files across all cloud platforms. -
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Precog
Precog
Precog is a cutting-edge data integration and transformation platform designed to empower businesses to effortlessly access, prepare, and analyze data from any source. With its no-code interface and powerful automation, Precog simplifies the process of connecting to diverse data sources, transforming raw data into actionable insights without requiring technical expertise. It supports seamless integration with popular analytics tools, enabling users to make data-driven decisions faster. By eliminating complexity and offering unparalleled flexibility, Precog helps organizations unlock the full potential of their data, streamlining workflows and driving innovation across teams and industries. -
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Lumi AI
Lumi AI
Lumi AI is an enterprise analytics platform that enables users to explore data and extract custom insights through natural language queries, eliminating the need for SQL or Python expertise. It offers self-service analytics, conversational analytics, customizable visualizations, knowledge management, seamless integrations, and robust security features. Lumi AI supports diverse teams, including data analysis, supply chain management, procurement, sales, merchandising, and financial planning, by providing actionable insights tailored to unique business terms and metrics. Its agentic workflows address simple to complex queries, uncover root causes, and facilitate complex analyses, all while interpreting business-specific language. Lumi AI integrates effortlessly with various data sources, ensuring enterprise-grade security by processing data within the client's network and offering advanced user permissions and query controls. -
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Amazon SageMaker Unified Studio is a comprehensive, AI and data development environment designed to streamline workflows and simplify the process of building and deploying machine learning models. Built on Amazon DataZone, it integrates various AWS analytics and AI/ML services, such as Amazon EMR, AWS Glue, and Amazon Bedrock, into a single platform. Users can discover, access, and process data from various sources like Amazon S3 and Redshift, and develop generative AI applications. With tools for model development, governance, MLOps, and AI customization, SageMaker Unified Studio provides an efficient, secure, and collaborative environment for data teams.
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Kapiche
Kapiche
Kapiche is an insights and analytics product built to make sense of customer feedback data, empowering you to improve decision-making and positively impact your company’s bottom line. Combine multiple data sources and analyze 1,000s of customer feedback responses in minutes. No setup, no manual coding, no code frames. Uncover insights in minutes, not weeks. Have complete confidence in your analysis and answer business questions easily, with deep, actionable insights from any customer data source. In minutes, not weeks. Use the insights uncovered by your insights analysts to ensure buy-in to your CX programs across the organization and drive impactful, customer-centric change. You’ll never make the most impactful business decisions using only quantitative customer data. The richest insights are found at the intersection of qualitative and quantitative data from every stage of the customer journey. -
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StackState
StackState
StackState's Topology and Relationship-Based Observability platform lets you manage your dynamic IT environment more effectively by unifying performance data from your existing monitoring tools into a single topology. Enabling you to: 1. 80% Decreased MTTR: by identifying the root cause and alerting the right teams with the correct information. 2. 65% Fewer Outages: through real-time unified observability and more planful planning. 3. 3x Faster Releases: by giving time back to developers to increase implementations. Get started today with our free guided demo: https://www.stackstate.com/schedule-a-demo -
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Continual
Continual
Build predictive models that never stop improving without complex engineering. Connect to your existing cloud data warehouse and leverage all your data where it already lives. Share features and deploy state-of-the-art ML models with nothing but SQL or dbt or extend with Python. Maintain predictions directly in your data warehouse for easy consumption by your BI and operational tools. Maintain features and predictions directly in your data warehouse without new infrastructure. Build state-of-the-art models that leverage all your data without writing code or pipelines. Unite analytics and AI teams with full extensibility of Continual's declarative AI engine. Govern features, models, and policies with a declarative GitOps workflow as you scale. Accelerate model development with a shared feature store and data-first workflow.
