Top 10 Built AI Alternatives & Competitors

Top 10 Alternatives to Built AI Recently Reviewed By G2 Community

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Domo
By Domo
4.3/5
(997)
Product Description
Domo is a cloud-native data experience platform that empowers organizations to connect, visualize, and analyze data from diverse sources in real-time. Designed for both technical and non-technical users, Domo facilitates data-driven decision-making across all levels of an organization by providing intuitive dashboards, AI-powered insights, and customizable visualizations. Its scalable architecture ensures seamless integration with existing cloud and on-premise systems, enabling businesses to optimize processes and drive actionable outcomes efficiently. Key Features and Functionality: - Data Integration: Connects with over 1,000 pre-built connectors, allowing seamless access to various data systems, including CRM, ERP, and cloud databases. - Business Intelligence & Analytics: Offers intuitive tools for creating dynamic dashboards, reports, and visualizations, making complex analytics accessible to all teams. - AI and Predictive Insights: Leverages machine learning capabilities to provide predictive analytics and actionable recommendations based on real-time data. - App Creation: Enables the development of custom, low-code, and pro-code business applications that automate processes and streamline decision-making. - Security & Governance: Provides robust data governance tools, including personalized data permissions, custom user roles, and compliance with standards like GDPR and HIPAA. Primary Value and Solutions: Domo addresses the challenge of fragmented data by unifying information from multiple sources into a single platform, enabling organizations to gain comprehensive insights and make informed decisions swiftly. Its user-friendly interface democratizes data access, allowing teams to collaborate effectively using real-time information. By integrating AI-powered analytics and customizable applications, Domo helps businesses optimize operations, identify trends, and drive growth, all while maintaining stringent security and governance standards.
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Categories in common with Built AI:
Data Science and Machine Learning Platforms

MATLAB
By MathWorks
4.5/5
(765)
Product Description
MATLAB is a high-level programming and numeric computing environment widely utilized by engineers and scientists for data analysis, algorithm development, and system modeling. It offers a desktop environment optimized for iterative analysis and design processes, coupled with a programming language that directly expresses matrix and array mathematics. The Live Editor feature enables users to create scripts that integrate code, output, and formatted text within an executable notebook. Key Features and Functionality: - Data Analysis: Tools for exploring, modeling, and analyzing data. - Graphics: Functions for visualizing and exploring data through various plots and charts. - Programming: Capabilities to create scripts, functions, and classes for customized workflows. - App Building: Facilities to develop desktop and web applications. - External Language Interfaces: Integration with languages such as Python, C/C++, Fortran, and Java. - Hardware Connectivity: Support for connecting MATLAB to various hardware platforms. - Parallel Computing: Ability to perform large-scale computations and parallelize simulations using multicore desktops, GPUs, clusters, and cloud resources. - Deployment: Options to share MATLAB programs and deploy them to enterprise applications, embedded devices, and cloud environments. Primary Value and User Solutions: MATLAB streamlines complex mathematical computations and data analysis tasks, enabling users to develop algorithms and models efficiently. Its comprehensive toolboxes and interactive apps facilitate rapid prototyping and iterative design, reducing development time. The platform's scalability allows for seamless transition from research to production, supporting deployment on various systems without extensive code modifications. By integrating with multiple programming languages and hardware platforms, MATLAB provides a versatile environment that addresses the diverse needs of engineers and scientists across industries.
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Categories in common with Built AI:
Data Science and Machine Learning Platforms

SAS Viya
By SAS Institute Inc.
4.3/5
(732)
Product Description
As a cloud-native AI, analytics and data management platform, SAS Viya enables you to scale cost-effectively, increase productivity and innovate faster, backed by trust and transparency. SAS Viya makes it possible to integrate teams and technology enabling all users to work together successfully to turn critical questions into accurate decisions.
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Categories in common with Built AI:
Data Science and Machine Learning Platforms

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Snowflake
By Snowflake, Inc.
4.6/5
(696)
Product Description
Snowflake’s platform eliminates data silos and simplifies architectures, so organizations can get more value from their data. The platform is designed as a single, unified product with automations that reduce complexity and help ensure everything “just works”. To support a wide range of workloads, it’s optimized for performance at scale no matter whether someone’s working with SQL, Python, or other languages. And it’s globally connected so organizations can securely access the most relevant content across clouds and regions, with one consistent experience.
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Categories in common with Built AI:
Data Science and Machine Learning Platforms

Alteryx
By Alteryx
4.6/5
(670)
Product Description
Alteryx drives transformational business outcomes through unified analytics, data science, and process automation.
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Categories in common with Built AI:
Data Science and Machine Learning Platforms

Vertex AI
By Google
4.3/5
(652)
Product Description
Vertex AI is a managed machine learning (ML) platform that helps you build, train, and deploy ML models faster and easier. It includes a unified UI for the entire ML workflow, as well as a variety of tools and services to help you with every step of the process. Vertex AI Workbench is a cloud-based IDE that is included with Vertex AI. It makes it easy to develop and debug ML code. It provides a variety of features to help you with your ML workflow, such as code completion, linting, and debugging. Vertex AI and Vertex AI Workbench are a powerful combination that can help you accelerate your ML development. With Vertex AI, you can focus on building and training your models, while Vertex AI Workbench takes care of the rest. This frees you up to be more productive and creative, and it helps you get your models into production faster. If you're looking for a powerful and easy-to-use ML platform, then Vertex AI is a great option. With Vertex AI, you can build, train, and deploy ML models faster and easier than ever before.
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Categories in common with Built AI:
Data Science and Machine Learning Platforms

SAP HANA Cloud
By SAP
4.3/5
(595)
Product Description
SAP HANA Cloud is the cloud-native data foundation of SAP Business Technology Platform, it stores, processes and analyzes data in real time at petabyte scale and converges multiple data types in a single system while managing it more efficiently with integrated multitier storage.
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Categories in common with Built AI:
Data Science and Machine Learning Platforms

Posit
By Posit
4.5/5
(569)
Product Description
In addition to our open-source data science software, RStudio produces RStudio Team, a unique, modular platform of enterprise-ready professional software products that enable teams to adopt R, Python, and other open-source data science software at scale.
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Categories in common with Built AI:
Data Science and Machine Learning Platforms

Altair AI Studio
By Altair
4.6/5
(516)
Product Description
RapidMiner is a powerful, easy to use and intuitive graphical user interface for the design of analytic processes. Let the Wisdom of Crowds and recommendations from the RapidMiner community guide your way. And you can easily reuse your R and Python code.
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Categories in common with Built AI:
Data Science and Machine Learning Platforms