--- title: "Definite" type: "AI Tool" url: "https://aidemos.com/tools/definite" description: "Using an ecommerce database, we tested Definite’s NL2SQL queries, follow-up analysis, and dashboard generation—its chat workflow feels heavy." category: "text" authors: - "Ayush Ghosh" published: "2026-06-12T05:45:17.627Z" updated: "2026-06-15T06:57:59.651Z" --- # Definite AI Data Platform · NL2SQL · AI Analyst · Dashboard Builder · June 2026 `nl2sql` · `ai-data-analyst` · `data-platform` · `business-intelligence` · `dashboard-tool` · `ai-analytics` · `data-visualization` · `sql-ai` · `ecommerce-analytics` · `operations-analytics` · `founders` · `operations-teams` · `non-technical-users` > **💡 Our take** > > Definite is strongest when a chat result needs to become a reusable dashboard. It can create dashboard-style outputs with KPI cards, charts, multiple views, and filters instead of keeping the result only inside the chat. > The trade-off is speed and simplicity. The flow feels heavier than AskYourDatabase and Basedash because visualizations are not shown directly inside the chat. Definite also missed part of the intent in the best-customer query by ranking only on spend instead of balancing spend and order frequency. ## Demo Recording [Video: Definite demo recording](https://d3epheqghktydj.cloudfront.net/definite-definite-demo-walkthrough.mp4) *Video — Hands-on walkthrough of Definite answering ecommerce database questions, handling follow-up analysis, creating dashboard-style outputs, and showing where its business reasoning works well or misses query intent.* ## Feature-by-Feature Breakdown ### Natural Language Database Querying — 7.2/10 **Verdict:** Good — accepts plain English database questions and returns structured answers, but can miss part of a multi-intent query. Definite lets users ask database questions in plain English and get table-based answers without writing SQL manually. **Input:** ``` Show all customers created in the last 90 days. How does new customer acquisition compare to the previous 90 days? ``` **Output:** ![definite-natural-language-database-querying-1.png](https://d3epheqghktydj.cloudfront.net/definite-natural-language-database-querying-1.png) *Image: definite-natural-language-database-querying-1.png* **Input:** ``` Who are my best customers — the ones who order the most and spend the most? ``` **Output:** ![definite-natural-language-database-querying-2.png](https://d3epheqghktydj.cloudfront.net/definite-natural-language-database-querying-2.png) *Image: definite-natural-language-database-querying-2.png* **Bottom line:** Definite can answer plain English database questions, but the artifact is worth checking because it shows both sides: simple queries are handled clearly, while multi-intent questions can be narrowed without clarification. ### AI Business Commentary — 8/10 **Verdict:** Strong — adds business-friendly observations that make outputs easier to understand. Definite adds natural language commentary around database results, including observations, caveats, and business meaning. **Input:** ``` For the top 3 from that list — do any of them have unpaid orders? ``` **Output:** ![definite-ai-business-commentary.png](https://d3epheqghktydj.cloudfront.net/definite-ai-business-commentary.png) *Image: definite-ai-business-commentary.png* **Bottom line:** Definite does not only return rows. The artifact is worth checking because the commentary gives business context, like acquisition clustering and overdue unpaid-order risk, which a raw SQL table would not explain by itself. ### Follow-Up Question Handling — 7.5/10 **Verdict:** Mixed — follow-up context is retained, but follow-ups can inherit the first answer’s narrowed interpretation. Definite lets users continue analysis through follow-up questions and uses previous context to answer the next query. **Input:** ``` For the top 3 from that list — do any of them have unpaid orders? ``` **Output:** ![definite-follow-up-question-handling-1.png](https://d3epheqghktydj.cloudfront.net/definite-follow-up-question-handling-1.png) *Image: definite-follow-up-question-handling-1.png* **Input:** ``` What payment methods do these top 3 usually use? ``` **Output:** ![definite-follow-up-question-handling-2.png](https://d3epheqghktydj.cloudfront.net/definite-follow-up-question-handling-2.png) *Image: definite-follow-up-question-handling-2.png* **Bottom line:** Definite can maintain follow-up context, but the artifact is worth checking because it shows an important risk: when the first interpretation is narrowed, later follow-ups can continue from that narrowed scope. ### Dashboard Generation — 8.6/10 **Verdict:** Strong — turns chat answers into reusable dashboard-style outputs with multiple views and charts. Definite lets users generate a separate dashboard/doc from chat results, making the analysis reusable instead of leaving it as a one-time response. **Input:** ``` Can you visualize it? ``` **Output:** ![definite-dashboard-generation-1.png](https://d3epheqghktydj.cloudfront.net/definite-dashboard-generation-1.png) *Image: definite-dashboard-generation-1.png* **Input:** ``` Show me this in pie chart. ``` **Output:** ![definite-dashboard-generation-2.png](https://d3epheqghktydj.cloudfront.net/definite-dashboard-generation-2.png) *Image: definite-dashboard-generation-2.png* **Bottom line:** This is Definite’s strongest feature. The artifact is worth checking because the output becomes a reusable dashboard with views and filters, not just a temporary chart inside chat. ### Metric Assumption Handling — 8.2/10 **Verdict:** Strong — explains assumptions when a metric can be interpreted in more than one way. Definite can explain how it interprets business metrics and show caveats when the result depends on workflow assumptions. **Input:** ``` What percentage of our orders were successfully delivered vs cancelled? ``` **Output:** ![definite-metric-assumption-handling-1.png](https://d3epheqghktydj.cloudfront.net/definite-metric-assumption-handling-1.png) *Image: definite-metric-assumption-handling-1.png* **Input:** ``` Compare that to last month — same breakdown, I want to see if things have improved or got worse. ``` **Output:** ![definite-metric-assumption-handling-2.png](https://d3epheqghktydj.cloudfront.net/definite-metric-assumption-handling-2.png) *Image: definite-metric-assumption-handling-2.png* **Bottom line:** This feature is useful for business users because Definite does not silently choose one interpretation. The artifact is worth checking because it shows both the metric output and the assumptions behind it. ## Pricing & Access Plans as of June 2026 | Plan | Price | Notes | | --- | --- | --- | | Free (tested) | $0 forever | Plan Tested. Includes 2 users, 2 connectors, Fi AI assistant, daily sync, 1 GB storage, and 5 credits/month. | | Standard | $250/month | Includes unlimited users, unlimited connectors, API access, hourly sync, 10 GB storage, and 100 credits/month. | | Enterprise | Custom | Includes 1,000+ credits/month, SSO, SOC 2 Type II, near real-time sync, audit logs, SCIM, dedicated support, SLA, and on-prem deployment options. | | Data Team as a Service Add-on | $2,500/month | Optional add-on for senior data engineering support, connector setup, dashboard building, and data modeling. Also listed as $100/hour for ad hoc work. | *Testing was completed on Definite’s 14-day free trial. Paid plan limits, credit usage, connector access, and enterprise deployment options should be verified again before publishing.* ## Is This Right For You? A side-by-side guide based on our hands-on testing. **✓ Use This If** - You want chat results to become reusable dashboards. - You need KPI cards, charts, filters, and multiple dashboard views. - You want business commentary around order pipeline and operational metrics. - You are comfortable moving from chat into a generated dashboard/doc. - You want an AI analyst inside a broader data platform, not only a simple SQL chatbot. **✕ Skip This If** - You want every visualization to appear directly inside chat. - You need the fastest and simplest NL2SQL experience for non-technical users. - You expect the tool to always clarify multi-intent questions before answering. - You want customer ranking logic to balance spend and order frequency automatically. - You prefer lightweight chat responses over dashboard/app generation. ## Use Case Track Record | Rank | Use Case | Notes | | --- | --- | --- | | | Query Live Databases Using Plain English with AI | | ## Classification - **Type:** text - **Built for:** Founders, Marketing ## Frequently Asked Questions **Q: Does Definite generate charts automatically inside chat?** Not in the tested workflow. Visualizations required an additional prompt, and charts were created in a separate dashboard/doc instead of directly inside the chat response. **Q: What is Definite strongest at?** Definite is strongest at turning analysis into reusable dashboards. In testing, it created dashboard views with KPI cards, charts, filters, and multiple analysis sections. **Q: Can Definite handle follow-up questions?** Yes, but performance varied by workflow. Definite handled follow-ups well in the order pipeline workflow, but in the best-customer workflow, follow-ups were based on an incomplete first interpretation because the main query was ranked only by spend. **Q: Is Definite good for non-technical users?** Partially. The business commentary is useful, but the separate dashboard/doc flow can feel heavier than a simple chat-based answer. It is better for users who want dashboard-style analytics. **Q: Did Definite perform better than AskYourDatabase or Basedash?** Not overall. Definite was strongest in dashboard generation and order pipeline reasoning, but AskYourDatabase and Basedash were smoother for direct non-technical NL2SQL workflows. **Q: What happens when you ask Definite to visualize a result?** Visualizations required an additional prompt, and charts were created in a separate dashboard/doc instead of directly inside the chat response. In testing, the generated dashboards included KPI cards, charts, filters, and multiple analysis sections. **Q: Where did Definite perform best in testing?** Its best result came from the order pipeline workflow, where it handled multiple follow-ups, workflow assumptions, old pending-paid records, and month-over-month comparison well. Dashboard generation was also Definite’s strongest feature. **Q: What was Definite’s main weakness on customer analysis?** The best-customer query missed the order-frequency part of the intent. Definite ranked customers mainly by total spend, and later follow-ups continued from that narrowed scope. **Q: Does Definite explain metric assumptions and caveats?** Yes. Definite can explain how it interprets business metrics and show caveats when the result depends on workflow assumptions. In testing, it separated delivered vs cancelled percentages into percentage of all orders and percentage of resolved-only orders, and noted that “Completed” orders could count as a successful end state depending on the workflow. **Q: Was Definite tested on a free plan or a trial?** Testing was completed on Definite’s 14-day free trial. The plan tested was the Free Plan. **Q: Is Definite better as a reusable dashboard tool or a lightweight SQL chatbot?** Definite is strongest when the user wants a reusable dashboard, not when they want the fastest lightweight NL2SQL chat experience. ## Similar Tools AI tools similar to Definite: - [AskYourDatabase](https://aidemos.com/tools/askyourdatabase) — AskYourDatabase Review: NL2SQL AI Database Chatbot Tested (2026) - [Basedash](https://aidemos.com/tools/basedash) — AI-Native BI · NL2SQL · Data Analyst Chat · June 2026 - [Draxlr](https://aidemos.com/tools/draxlr) — AI Data Analyst · NL2SQL · Data Visualization · June 2026 - [FutureSmart Agent Platform](https://aidemos.com/tools/futuresmart-agent) — FutureSmart Agent Platform Review: RAG AI Agents & NL2SQL Tested (2026) - [Querio](https://aidemos.com/tools/querio) — AI Data Analyst · NL2SQL · Data Visualization · June 2026