Review an Emotion AI startup portfolio across 500 sample records, five dashboard pages and 28 source-data fields. The Emotion AI Startups Dashboard in Excel brings deployment scale, prediction volume, enterprise clients, contract value, model accuracy, latency, sector adoption, commercial performance and delivery health into one filterable workbook. The sample Overview displays 500 deployments, 3.4M predictions, 6,516 enterprise clients, $32.8M contract value and 89.0% model accuracy. Replace the fictional demonstration data with your own governed dataset and use the workbook as an analytical reporting layer, not as an emotion-recognition model.
Key Features of Emotion AI Startups Dashboard in Excel
- Five visual pages: Overview, Model Performance, Sector Adoption, Commercial Analysis and Deployment Health.
- Four interactive slicer groups: filter by Month, Emotion Modality, Application Sector and Deployment Type.
- Core portfolio KPIs: deployments, predictions, enterprise clients, contract value, satisfaction and accuracy.
- Model operations: compare prediction volume, model latency and accuracy across modalities and deployment types.
- Market adoption: review clients and deployments by sector, region and delivery approach.
- Commercial context: analyse contract value, delivery cost, margin, funding stage, startup and quarter.
- Deployment health: monitor completion rates, deployment volume and client satisfaction.
- Editable source table: 500 sample rows with 28 columns in a structured Excel table.
What’s Inside This Excel Dashboard
Overview
The main page is the executive entry point. It combines six headline measures with Model Accuracy by Deployment Type, Model Accuracy by Emotion Modality and Model Accuracy by Month. The sample covers biosignals, facial vision, multimodal, text sentiment and voice tone across cloud API, hybrid, on-device edge and on-premise deployments.


Overview dashboard with portfolio KPIs and model-accuracy analysis
Model Performance
This page examines Total Predictions by Emotion Modality, Average Model Latency by Emotion Modality, Average Model Latency by Deployment Type and Model Accuracy by Month. It supports operational comparison; it does not test a model, validate emotion labels or certify accuracy.


Model Performance across modality, deployment type and month
Sector Adoption
Compare deployments by deployment type, enterprise clients by application sector, enterprise clients by region and average satisfaction by sector. Sample sectors include automotive, customer care, education, gaming and media, healthcare and recruitment.


Sector Adoption and regional client distribution
Commercial Analysis
This view compares contract value with delivery cost by funding stage, total contract value by startup, net contract margin by region and total contract value by quarter. Treat the sample figures as fictional demonstration data rather than market benchmarks.


Commercial performance by funding stage, startup, region and quarter
Deployment Health
Track deployments by funding stage and month, compare completion rate by product lead and review average satisfaction by startup. The page helps organise delivery reporting but does not replace project controls or customer-success records.


Deployment volume, completion and satisfaction indicators
Excel vs. Power BI vs. Paid Analytics SaaS – Where This Fits
| Consideration | This Excel dashboard | Power BI | Paid analytics SaaS |
|---|---|---|---|
| Cost | One-time template purchase | Desktop plus possible sharing licences | Usually recurring subscription |
| Setup | Replace sample rows and refresh | Model and publish a report | Configure vendor workspace |
| Pages | Five dashboards plus Data and Support sheets | Flexible report pages | Plan-dependent |
| Source transparency | Visible 28-column table | Model-driven | Vendor-dependent |
| Collaboration | File-based | Service-based sharing | Usually browser-based |
| AI model execution or emotion detection | Not included | Requires an external model/data source | Product-dependent |
Who This Dashboard Is For – and Who It’s Not For
It suits startup operators, portfolio analysts, innovation teams, accelerators and product leaders who already have approved summary data and need a structured Excel reporting view. It can also support classroom or scenario analysis when all figures are clearly labelled as synthetic.
It is not an emotion-recognition engine, biometric system, real-time monitoring tool, diagnostic product or compliance solution. It should not be used to infer feelings, health, employability or risk about individuals. High-impact uses require appropriate consent, governance, validation and human oversight.
How to Use the Emotion AI Startup Dashboard
- Unzip the download and open the .xlsx file in Microsoft Excel.
- Review the five dashboard pages and the Data sheet structure.
- Replace the 500 fictional sample rows with approved, consistently formatted records.
- Keep column headings and categories consistent so the workbook’s pivots, visuals and slicers remain connected.
- Refresh the workbook, then test Month, Emotion Modality, Application Sector and Deployment Type filters.
- Validate outputs against the source before presenting them.
- Document governance and limitations using the principles in the NIST AI Risk Management Framework.
Real-World Use Cases
An accelerator portfolio review
Leena compares deployment type, funding stage, region and contract value across approved portfolio records, while keeping the sample startup names separate from live reporting.
A product-operations meeting
Marcus reviews latency, accuracy, completion and satisfaction summaries, then returns to controlled source systems for investigation rather than treating the dashboard as model validation.
An innovation-strategy workshop
Asha uses synthetic data to explore how modality and application sector influence the story told by charts without processing personal biometric or emotional data.
Frequently Asked Questions
Does this workbook perform emotion recognition?
No. It visualises data supplied to the workbook and contains no AI model or inference service.
Are the startup names and figures real?
The included 500-row dataset is sample content for demonstration and should not be treated as market research.
What filters are included?
Month, Emotion Modality, Application Sector and Deployment Type slicers are visible across the dashboard pages.
Can I add my own records?
Yes. Replace the sample rows carefully, retain the expected structure and refresh the workbook.
Does it certify model accuracy or fairness?
No. Dashboard calculations do not establish validity, bias, fairness, safety or regulatory compliance.
Which Excel version should I use?
Use a current desktop version of Microsoft Excel that supports the workbook’s pivots, charts and slicers.
About the Author
Built by PK – Microsoft Certified Professional with 15+ years of Excel, Google Sheets, and Power BI experience. Founder of NextGenTemplates, reaching 300K+ subscribers across YouTube channels. Every template is hand-built and tested before release.
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Turn governed startup data into a clear portfolio review. Download the workbook, replace the sample records and validate every result before use.
Last updated: September 2026.

































