Data & Analytics
Conversational AI tools that let anyone analyse data, build dashboards, and surface insights without writing code.
AI data analysis tools are making it possible for any business team to get answers from their data without SQL, without an analyst, and without a BI ticket queue. Most companies have more data than they know what to do with, and most of it goes unexamined because querying it requires a specialist — these tools are changing that. You can ask a question in plain English and get a chart or summary back in seconds, without SQL, without waiting on an analyst, without a BI ticket queue. For ops, finance, and product teams, this shifts the dynamic from 'we should look at that data' to actually looking at it. The tools that go further also flag anomalies you didn't think to ask about, which is often where the useful insights are.
The distinction that matters most when evaluating data tools is who the end user is. Conversational analytics tools like Julius AI are designed for business users who need answers from data but do not want to learn SQL or Python. Notebook tools with AI assistance like Hex and Noteable are designed for analysts and data scientists who write code but want AI to accelerate it. Spreadsheet tools with live data connections like Equals are designed for finance and ops teams who are comfortable in spreadsheets but need access to live data. Matching the tool to the user type matters more than comparing features in isolation.
For data teams specifically, the most valuable AI capability is not necessarily query generation — it is explanation. The ability to ask what a query is doing or why a metric is behaving unexpectedly in plain English, and get an accurate explanation in response, reduces the time junior analysts spend deciphering legacy code and helps senior analysts document their work more effectively.
The compounding benefit of democratising data access across an organisation is that the data team gets fewer ad hoc requests for routine analysis, and the business teams asking the questions get answers faster. For companies where the data team is a bottleneck — where business stakeholders regularly wait days for simple data questions to be answered — deploying a conversational analytics tool for non-technical teams often delivers ROI faster than any other data investment.
4 Tools
Julius AI
Julius AITalk to your data in plain English
Julius AI is a conversational AI data analysis tool that lets you upload a spreadsheet, connect a database, or paste raw data, then ask questions in plain English. It produces charts, statistical summaries, correlations, and forecasts without requiring SQL, Python, or any technical background. The analysis is conversational: you ask a question, Julius produces a result, you ask a follow-up, and the session builds on itself. It also proactively suggests follow-up analyses based on patterns it detects, which is often where the most useful insights surface.
Hex
Hex TechnologiesAI-powered data notebooks and apps
Hex is an AI-powered data notebook platform where Magic AI generates Python and SQL so analysts can focus on the reasoning and interpretation rather than the syntax. You describe what you want — 'calculate 30-day retention for each cohort' or 'join these two tables and show me month-over-month growth' — and Hex's Magic AI writes the code and runs it. Existing code can be explained in plain English, refactored on request, or used as the basis for follow-up queries.
Noteable
NoteableAI-powered collaborative data notebooks
Noteable is a browser-based data notebook with an AI co-pilot that suggests next analysis steps, generates code from plain English descriptions, and flags potential issues before they become errors in your results. The co-pilot understands the context of what you are working on — the data you have loaded, the analyses you have already run — and makes suggestions that are relevant to your specific dataset rather than generic.
Equals
EqualsAI-powered spreadsheets connected to your data
Equals is an AI-powered spreadsheet platform that connects directly to your databases and data warehouse, so every number you look at is live rather than a CSV export from last Tuesday. When the data refreshes, every chart, formula, and calculation updates automatically — there is no manual export step, no question of whether the numbers are current, and no version control problem of multiple people working on different exports of the same data.