Spine AI
Predictive AnalyticsPlans, delegates, reviews complex work.
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Plans, delegates, reviews complex work.
Sourcer AI instantly evaluates news content, clarifying bias and reputability.
Firstup's AI platform boosts employee engagement and productivity.
Soccersm AI analyzes game data to improve team performance. Simple but focused.
Drafts email and social replies with ChatGPT, and can summarize, translate or correct text too.
SmartBids offers AI-powered AVM for accurate pricing but lacks manual customization.
Pulls local businesses from Yelp and Google, then drafts ChatGPT outreach DMs for each one.
Analyze Google Sheets directly with Gemini's insights. Raise your workflow.
Uploads your chatbot conversations automatically to build a shared open-source training dataset.
The only vector database with a feedback loop, powering personalized search and recommendations.
An early-access hub that pulls related files, chats and tasks into whatever tab you're on.
Suits research-driven businesses, not simple data analysis.
Automates TikTok influencer outreach and customer replies for e-commerce sellers in one extension.
Limited to Amazon and Walmart data, this Chrome extension offers detailed analytics for serious sellers.
Automatically documents where your data comes from, who uses it, and what might break.
Catalogs, documents and monitors your data stack, with AI that answers questions about it.
It falls short on speed with complex analyses.
Get real-time insights into GitHub repositories and open-source projects.
Nittii caters to experienced bettors who prefer a wide range of betting options.
Neurons AI analyzes video ads to predict impact.
We bridge AI ambition to working prototypes in days. The real challenge is implementation.
Neodata transforms video, documents, data and assistants into business solutions.
Daily AI predictions for top sports leagues.
Pulls Shopify, Google Analytics, and Facebook Ads data into a single dashboard for tracking PPC campaigns.
The sales assistant built for customer-facing work.
Analyzes how algorithms expose your catalog and translates signals into clear promotion decisions.
Run multiple models, compare outputs.
Gather and analyze customer feedback efficiently.
Lack expertise in AI implementation.
An AI autofill extension that populates forms, spreadsheets and messages from saved templates.
Global economic data, AI-driven insights.
For ML engineers building large-scale systems, but not for beginners or small projects.
A Chrome extension that pulls advertising, sales, revenue and inventory data into one dashboard.
MAYA AI helps accelerate revenue for enterprises using AI.
Lytics helps secure data on web pages.
Tailored for travel companies, not personal travelers.
Linq Alpha offers intelligent search for hedge funds.
Get deep insight at your fingertips with LinqAlpha's AI copilot for hedge funds and asset managers.
Works on any website, but lacks deep analytics.
A dataset inspection tool that surfaces PII, duplicates, and bias before training an LLM.
A Python tool for searching, cleaning, and quantifying datasets before training an LLM.
Full stack AI agents for the entire customer experience journey.
Lettria converts unstructured data into structured knowledge, making AI systems more reliable and traceable. However, it requires a pilot program to scope value.
Lebesgue: AI CMO provides clear, actionable insights but can be expensive for smaller stores.
An AI coaching tool for students that also collects your educational app data.
AI-powered retail automation software
Transform SQL queries into APIs & dashboards quickly.
Ideal for traders who want to test AI bots, not suitable for real trading.
Three worth starting with
Terms to know
AI data and analytics tools cover business intelligence, customer analytics, data visualization, predictive analytics and web analytics. Julius AI answers plain-language questions about a spreadsheet, BigML builds machine-learning models from uploaded data, Piktochart turns tables into charts and infographics, and Ahrefs reports on search traffic and website visibility. Analysts, marketers and founders use them to get from raw numbers to a clear answer without writing SQL or code. Before choosing, check which data sources a tool can connect to, where your data is stored and whether it trains models, how clearly it explains an answer, and whether dashboards can be exported or shared.
Business intelligence describes what has already happened, usually through dashboards and reports built on your existing data. Predictive analytics uses past patterns to estimate what is likely to happen next, such as churn or demand. Many teams start with the first and add the second once their data is clean.
Often yes. Many tools accept a spreadsheet or CSV and let you ask questions in plain language, then return a chart or summary. Always spot-check the numbers against the source, because a confident answer can still come from a misread column or a wrong filter.
It depends on the tool. Look for where files are stored, if your data is used to train models, and if you can delete it. For customer records or financial data, check your company's data policy first and consider anonymising the file before uploading.