Business Analyst
- Turn spreadsheet data into clear charts for weekly reports
- Compare KPIs across teams, regions, or time periods
- Create executive-ready visuals without manual formatting
- Summarize trends, outliers, and key takeaways from datasets
Discover i10X AI charting agents that turn prompts, spreadsheets, and datasets into clear charts, graphs, dashboards, and presentation-ready visuals—no coding or design skills required.
i10X cut chart creation from four hours to fifteen minutes, ending our Excel-Canva-PowerPoint shuffle and freeing the team for real campaign work.
We replaced three paid viz tools with i10X and cut monthly costs two hundred dollars while delivering board forecasts twice as fast.
Ditching our multi-tool stack for i10X lets us build real-time ops dashboards in under five minutes instead of half a day.
Один Superagent и специализированные субагенты для каждой задачи.
AI-powered scanning with OCR, image enhancement, and structured data extraction.
AI-powered PDF editing with OCR, summarization, rewriting, and data extraction.
Generate spreadsheet formulas from plain-language descriptions.
Converts meetings to searchable transcripts, summaries, and action items.
Summarizes threads and drafts contextual email replies using AI.
Transcribes meetings and extracts summaries, decisions, and action items.
You add a dataset or prompt; i10X reads structure, fields, and visualization goals.
You choose chart type, audience, and style; i10X recommends axes, filters, and layout.
You click create; i10X Super Agent builds charts, summaries, and export-ready visuals automatically.
You request edits or formats; i10X adjusts details and prepares shareable files.
Создано под конкретные задачи, которые люди решают каждый день.
| Возможность | Superagent | Отдельные инструменты |
|---|---|---|
| Setup and onboarding | i10X can run chart creation, narrative generation, formatting, and export from one AI-agent workflow after connecting the required data source or uploading a file. | Point tools are usually quick for a single chart, but each separate app still needs its own account, data import, permissions, templates, and export settings. |
| Number of tools in the workflow | i10X replaces separate spreadsheet cleanup, chart generation, copywriting, and presentation-formatting steps with one coordinated workflow. | Point-tool stacks commonly require one tool for data prep, one for charting, another for AI text summaries, and another for slides or dashboards. |
| Data consistency across outputs | i10X uses the same connected dataset or uploaded file across charts, summaries, and report text, reducing manual copy-paste mismatches. | Point tools often create separate copies of the same data in each app, so updates must be re-imported or manually synchronized. |
| Cost and plan limits | i10X consolidates AI charting plus adjacent reporting tasks into one platform subscription, so teams are not paying for multiple overlapping point tools. | Free or low-cost point tools can work for small projects, but export quality, dataset size, collaboration, branding, or integrations are often locked behind separate paid plans. |
| Learning curve and ongoing maintenance | i10X gives users a guided natural-language workflow, so non-technical users can request chart type, axes, filters, and summaries without learning several separate interfaces. | Point tools may be simple individually, but teams must learn each tool’s prompt style, chart controls, data limits, sharing model, and export behavior. |
Реальные промты, которые можно скопировать в агента выше.
You are an AI charting assistant. Help me create a free, professional-quality business dashboard from the dataset below. Goal: Convert raw sales data into clear charts for a weekly business report. Dataset: Month,Product,Revenue,Units Sold,Region Jan,Product A,12500,420,North Jan,Product B,9800,310,South Feb,Product A,14200,460,North Feb,Product B,10400,330,South Mar,Product A,15800,510,North Mar,Product B,9700,295,South Apr,Product A,17100,540,North Apr,Product B,11300,350,South Please generate: 1. The best chart types for this data. 2. A line chart showing monthly revenue by product. 3. A bar chart comparing units sold by product and month. 4. A short AI-generated insight summary highlighting trends, anomalies, and business recommendations. 5. Styling recommendations for a clean dashboard using free AI charting tools. 6. Export recommendations for PNG, SVG, PDF, or PPTX. Return the final answer as a JSON array with objects containing: chart_name, chart_type, data_fields, purpose, key_insight, recommended_style, export_format.
[{"chart_name":"Monthly Revenue by Product","chart_type":"Line chart","data_fields":["Month","Product","Revenue"],"purpose":"Show revenue trends across time for each product.","key_insight":"Product A shows consistent month-over-month revenue growth, while Product B fluctuates with a dip in March and recovery in April.","recommended_style":"Use a clean white dashboard background, blue for Product A, orange for Product B, visible data labels at April endpoints, and a concise title such as 'Monthly Revenue Trend by Product'.","export_format":"PNG for reports, SVG for editable design use, PPTX for presentations"},{"chart_name":"Units Sold by Product and Month","chart_type":"Grouped bar chart","data_fields":["Month","Product","Units Sold"],"purpose":"Compare monthly unit sales performance between Product A and Product B.","key_insight":"Product A consistently outsells Product B each month, with both products reaching their highest unit sales in April.","recommended_style":"Use grouped vertical bars, consistent product colors, light gridlines, and axis labels with units sold clearly marked.","export_format":"PNG or PDF"},{"chart_name":"Weekly Sales KPI Dashboard","chart_type":"Dashboard summary with line and bar charts","data_fields":["Revenue","Units Sold","Product","Month","Region"],"purpose":"Provide a quick executive overview of revenue and sales volume performance.","key_insight":"Revenue growth is mainly driven by Product A in the North region; Product B may need promotional support after its March decline.","recommended_style":"Use two main charts, KPI cards for total revenue and total units, consistent formatting, and a short insight box under the visuals.","export_format":"PPTX for meetings, PDF for distribution"}]
You are an AI charting assistant for academic and research visualization. I need to transform a small research dataset into presentation-ready charts using a free AI charting tool. Research topic: Student study hours and exam performance. Dataset: Student Group,Average Study Hours,Average Exam Score,Attendance Rate Group A,4.5,72,81 Group B,6.2,79,86 Group C,7.8,88,91 Group D,3.1,65,74 Group E,8.4,91,94 Create a visualization plan that includes: 1. A scatter plot showing the relationship between study hours and exam score. 2. A bar chart comparing attendance rate by student group. 3. A short narrative explaining whether more study hours appear associated with higher scores. 4. Suggestions for chart labels, titles, colors, and annotations. 5. A warning about limitations, including small sample size and correlation not proving causation. Return the result as a JSON array with objects containing: chart_name, chart_type, x_axis, y_axis, visual_message, annotation, limitation_note, export_format.
[{"chart_name":"Study Hours vs Exam Score","chart_type":"Scatter plot","x_axis":"Average Study Hours","y_axis":"Average Exam Score","visual_message":"Groups with higher average study hours generally show higher average exam scores.","annotation":"Highlight Group E as the highest study-hour and highest-score group.","limitation_note":"The dataset is small, and the visual suggests correlation only; it does not prove study hours caused higher scores.","export_format":"SVG for academic slides or PNG for quick insertion"},{"chart_name":"Attendance Rate by Student Group","chart_type":"Bar chart","x_axis":"Student Group","y_axis":"Attendance Rate","visual_message":"Attendance appears higher among groups with stronger exam performance.","annotation":"Use a label above Group E showing 94% attendance and Group D showing 74% attendance.","limitation_note":"Attendance may be one of several contributing factors; additional variables would be needed for a stronger conclusion.","export_format":"PNG or PPTX"},{"chart_name":"Research Presentation Summary Visual","chart_type":"Two-chart slide layout","x_axis":"Student groups and study hours","y_axis":"Exam score and attendance rate","visual_message":"The overall pattern suggests that stronger study habits and higher attendance are associated with better exam outcomes.","annotation":"Add a short callout: 'Higher study hours align with higher average scores in this sample.'","limitation_note":"Avoid overstating findings because the sample contains only five groups and lacks statistical testing.","export_format":"PPTX or PDF"}]
You are an AI charting and infographic assistant. Create social-media-friendly charts from the plain-English metrics below using a free AI charting workflow. Objective: Build a simple infographic for a LinkedIn post about website performance. Metrics: - Website visits increased from 42,000 in Q1 to 58,000 in Q2. - Conversion rate improved from 2.8% to 3.6%. - Bounce rate decreased from 51% to 44%. - Email signups grew from 1,176 to 2,088. Please generate: 1. The best chart or infographic layout for these metrics. 2. A before-vs-after comparison chart for Q1 vs Q2. 3. A concise insight summary suitable for a caption. 4. Recommended colors, labels, and icons. 5. A free-tool-friendly export plan for social media. Return the final response as a JSON array with objects containing: visual_name, chart_type, metric_compared, q1_value, q2_value, insight, design_direction, social_caption, export_format.
[{"visual_name":"Q1 vs Q2 Website Performance Snapshot","chart_type":"Before-vs-after KPI infographic","metric_compared":"Website visits, conversion rate, bounce rate, and email signups","q1_value":"Visits: 42,000; Conversion rate: 2.8%; Bounce rate: 51%; Email signups: 1,176","q2_value":"Visits: 58,000; Conversion rate: 3.6%; Bounce rate: 44%; Email signups: 2,088","insight":"Website performance improved across all key metrics, with more traffic, better conversion, lower bounce rate, and nearly doubled email signups.","design_direction":"Use green upward indicators for visits, conversion rate, and signups; use a blue downward indicator for bounce rate to show improvement. Apply a clean LinkedIn-friendly layout with bold numbers and minimal text.","social_caption":"Q2 delivered stronger website performance: visits rose to 58K, conversion improved to 3.6%, bounce rate dropped to 44%, and email signups grew to 2,088.","export_format":"PNG at 1200x1200 for LinkedIn feed"},{"visual_name":"Website Visits Growth Chart","chart_type":"Two-column bar chart","metric_compared":"Website visits","q1_value":"42,000","q2_value":"58,000","insight":"Website visits increased by 16,000, indicating stronger reach or acquisition performance in Q2.","design_direction":"Use two bold bars with Q2 highlighted in a brighter color and a '+38%' callout above the second bar.","social_caption":"Traffic momentum improved significantly in Q2, with visits increasing from 42K to 58K.","export_format":"PNG or SVG"},{"visual_name":"Conversion and Signup Improvement Panel","chart_type":"Compact KPI cards","metric_compared":"Conversion rate and email signups","q1_value":"Conversion: 2.8%; Signups: 1,176","q2_value":"Conversion: 3.6%; Signups: 2,088","insight":"The site converted a larger share of visitors and generated substantially more email signups in Q2.","design_direction":"Use two KPI cards with large percentage and signup numbers, simple icons, and short trend arrows.","social_caption":"Better traffic quality and stronger conversion helped drive email signup growth in Q2.","export_format":"PNG for social posting, PDF for internal recap"}]
Справка
Отдельные решения, закрывающие часть этого сценария. Агент выше справляется со всеми ними в одном диалоге.
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