Conversational analytics tools generate answers.
ADAT certifies them.
Julius AI, ChatGPT ADA, Rows, Akkio, and similar tools let you ask questions in plain English. So does ADAT. The difference is what happens next — and whether you can trust the number in a board meeting.
Ask the same question twice.
Get two different answers.
Every conversational analytics tool works the same way. You ask a question. The AI generates code — SQL, Python, R — to answer it. Each generation is a fresh attempt. Fresh attempts produce different results. That is not a bug. It is how the technology works.
The reproducibility problem
Ask Julius AI "what is our default rate" on Monday and Friday. The AI may write different SQL each time — different column interpretations, different aggregations, different results. Both answers are confident. Neither is certified.
The audit problem
When a board member asks where the number came from, the honest answer from any conversational AI tool is: "the AI generated it." That is not an audit trail. That is not a defensible answer in a regulated environment.
The trust problem
Conversational analytics tools are impressive in demos. They become dangerous when executives make million-dollar decisions on AI-generated numbers that have never been validated against a fixed methodology.
What each tool does —
and where the gap is.
Julius AI
Conversational data analysis. Upload a file, ask questions in plain English, receive AI-generated charts and answers.
Gap: Every answer is freshly generated. No fixed formula. No audit trail. No certified result.
ChatGPT Advanced Data Analysis
OpenAI's code interpreter. Uploads data, writes Python to answer questions, produces visualisations on demand.
Gap: AI-written code per query. Same question can produce different code and different results.
Rows
Spreadsheet with AI capabilities. Integrates external data, uses AI to generate formulas and analysis.
Gap: Spreadsheet paradigm with AI assistance — not a governed analytical system.
Akkio
No-code AI analytics and prediction platform. Drag-and-drop data preparation and forecasting.
Gap: Prediction-focused. No certified metric layer. Results vary by model retraining.
Obviously AI
Point-and-click predictive analytics. Build ML models without code.
Gap: Prediction tool, not a governed analytical canvas. No audit trail per answer.
Polymer
AI-powered data exploration. Upload spreadsheets and ask questions visually.
Gap: Exploration tool. No certified metric system. No reproducibility guarantee.
Conversational analytics vs
certified analytics.
| Capability | Conversational AI tools | ADAT |
|---|---|---|
| Plain English questions | Yes | Yes |
| Same answer twice | Not guaranteed — AI regenerates each time | Always — certified formula, fixed result |
| Audit trail | None — AI generation is not traceable | Complete — every formula, every computation logged |
| Formula shown | Code shown — not readable by executives | Plain English explanation of every result |
| Data preparation | Requires clean, pre-formatted data | Automatic — upload any structure, any format |
| Visualisation | AI-generated charts — varies by session | Certified visualisations from prepared data |
| Your data location | Processed on vendor cloud servers | Never moves — processed where it lives |
| Pricing model | Per query, per token, or per seat with limits | Flat — unlimited questions, one price |
| On-premises option | No | Yes — cloud, on-prem, or desktop |
| Board-ready results | Use with caution — verify independently | Yes — certified, auditable, reproducible |
One question. One certified answer.
Every time.
Upload your first dataset free. No credit card. No analyst. No waiting.