Best AI Data Analytics Tools & Software in 2026 (Free & Paid)
Explore 268 high-quality AI tools, software and services for AI Data Analytics. including Microsoft Knowledge Exploration, PostgresML, Sketch, PandasAI
Flowpoint is an AI-powered tool that simplifies website analytics, helping businesses create detailed reports and optimize their workflows efficiently.
Alembic is a game-changing AI platform that transforms marketing measurement, helping businesses make smarter, data-driven decisions.
GobbleCube is an AI-driven platform that automates revenue monitoring and RCA, helping brands grow faster with real-time insights and secure, enterprise-ready solutions.
Proxima is a game-changing platform that helps brands scale marketing efficiently, lower acquisition costs, and maximize customer lifetime value through predictive data intelligence.
DEMA is an AI-powered e-commerce analytics platform that helps businesses make smarter decisions, optimize marketing spend, and boost profits with real-time data and predictions.
Viam is the easiest way to integrate AI, automation, and data into your business, offering solutions for industries like manufacturing, marine, and sports.
Hyperscience is a game-changing AI platform that automates document processing, turning unstructured data into actionable insights. It’s trusted by industries worldwide for its accuracy, flexibility, and compliance.
Datamatics empowers businesses with AI-driven automation, finance transformation, and customer experience solutions to boost productivity and competitiveness.
Planck’s GenAI solutions transform commercial underwriting with smarter risk insights, comprehensive classifications, and a powerful risk workbench.
Indicium empowers businesses to modernize their data, scale AI, and drive innovation with tailored solutions and expert guidance.
BigPanda is a game-changer for IT teams, using AI to automate workflows, reduce noise, and speed up incident resolutions, all while improving service reliability.
Snorkel AI accelerates AI development with programmatic data labeling, LLM fine-tuning, and RAG optimization, making it 100x faster to build production-ready AI applications.