Akkio Review 2026

Julius AI

Trending

Chat with your data & spreadsheets

Julius AI turns a spreadsheet, CSV or database connection into a conversation. Upload a file or paste in messy data and ask questions in plain English — Julius writes and runs the underlying Python analysis itself, then hands back a chart, a table or a written answer instead of a wall of code. What sets Julius apart from a generic chatbot is that it treats analysis as a process, not a single prompt: it plans the steps, executes them, checks the output makes sense and iterates if a chart looks wrong or a query returns something unexpected. That loop is what lets non-technical users get correct pivot tables, regressions and visualisations without ever opening a notebook. Founders, analysts and ops teams use it as a faster substitute for pestering a data analyst with one-off questions — connect the data once and keep asking follow-ups the way you would in a conversation with a colleague who happens to know Python.

Hex

AI-assisted notebooks and data apps for analytics teams

Hex is a collaborative data workspace where SQL, Python and no-code cells live in one reactive notebook. Magic AI writes queries and transformation code from a plain-language question, using your warehouse schema and column descriptions as context so the generated SQL references real tables rather than plausible-sounding guesses. The reactive execution model means changing an upstream cell recomputes everything downstream, which keeps long analyses honest. When the work is done, publishing turns the same notebook into a polished interactive app with filters and parameters for stakeholders who will never open a notebook. Analytics engineers appreciate the dbt and warehouse integrations, version control and review workflow, while analysts get an AI pair that handles the boilerplate joins and chart code.

Formula Bot

Excel & Sheets formulas from text

Formula Bot solves a narrower but universally annoying problem: writing the right Excel or Google Sheets formula. Describe what you want in plain language — "sum column B where column A is 2025" — and it returns a working formula with an explanation of what each part does, so you are not just copy-pasting something you don't understand. Beyond formulas, it extends into a broader AI-for-spreadsheets toolkit: explaining an existing formula someone else wrote, generating VBA or Apps Script, and a chat-with-your-data mode for quick summaries directly inside a spreadsheet. It installs as an add-on for Excel and Google Sheets, so the workflow stays inside the tool people already use rather than pulling data into a separate app. It is aimed squarely at the person who knows what result they need but doesn't want to relearn spreadsheet syntax — marketers, ops staff and analysts who live in spreadsheets but aren't formula specialists.

ThoughtSpot

Conversational BI for the enterprise

ThoughtSpot is an enterprise business intelligence platform built around search-driven analytics: type or ask a question in natural language and get back a governed chart or dashboard pulled from the company's actual data warehouse, not a guess. Its AI layer, Sage, was the conversational front-end that popularised this natural-language search approach and has since been developed further into the platform's broader AI analyst capabilities. Unlike lightweight spreadsheet copilots, ThoughtSpot is designed for large, governed datasets — it sits on top of existing warehouses like Snowflake, BigQuery or Databricks and enforces row-level security and consistent metric definitions, so every answer traces back to a single source of truth rather than a spreadsheet someone edited last week. It's built for organisations that already have a data warehouse and want to put self-serve, natural-language analytics in front of non-technical staff — sales, marketing and ops teams asking questions without filing a ticket with the data team.

Julius AI

Trending

Chat with your data & spreadsheets

Julius AI turns a spreadsheet, CSV or database connection into a conversation. Upload a file or paste in messy data and ask questions in plain English — Julius writes and runs the underlying Python analysis itself, then hands back a chart, a table or a written answer instead of a wall of code. What sets Julius apart from a generic chatbot is that it treats analysis as a process, not a single prompt: it plans the steps, executes them, checks the output makes sense and iterates if a chart looks wrong or a query returns something unexpected. That loop is what lets non-technical users get correct pivot tables, regressions and visualisations without ever opening a notebook. Founders, analysts and ops teams use it as a faster substitute for pestering a data analyst with one-off questions — connect the data once and keep asking follow-ups the way you would in a conversation with a colleague who happens to know Python.