# K-Dense Web - LLM Context File
# This file provides context for large language models about K-Dense
# Standard location: /llms.txt
# Alternative location: /.well-known/llms.txt

## About K-Dense Web

K-Dense Web is an AI co-scientist platform that accelerates scientific research from hypothesis to publication. It's designed to work alongside researchers, handling data analysis, machine learning, and report generation while scientists focus on asking the right questions and making breakthrough discoveries.

## Company Information

- **Company Name**: K-Dense
- **Product**: K-Dense Web
- **Website**: https://k-dense.ai
- **Application**: https://app.k-dense.ai
- **Location**: 380 Portage Ave, Palo Alto, CA 94306
- **Contact**: contact@k-dense.ai
- **Founded**: 2024

## What K-Dense Web Does

K-Dense Web is a fully hosted AI platform that helps researchers:

1. **Analyze Scientific Data**: Upload CSV, Excel, FASTA, PDB, SDF, and many other formats for automatic analysis
2. **Run Machine Learning**: Automatic model selection, hyperparameter tuning, and SHAP interpretability
3. **Generate Publication-Ready Outputs**: Figures, statistical reports, and manuscript-quality documentation
4. **Support Multiple Domains**: Genomics, drug discovery, proteomics, clinical research, environmental science, and more

## Research Domains Supported

- Genomics & Bioinformatics (RNA-seq, scRNA-seq, DESeq2, GSEA)
- Drug Discovery (RDKit, molecular docking, QSAR, ADMET prediction)
- Proteomics & Mass Spectrometry (MaxQuant, PTM analysis, metabolomics)
- Clinical Research (survival analysis, biomarker discovery, EHR data)
- Machine Learning (AutoML, XGBoost, neural networks, SHAP analysis)
- Environmental Science (climate modeling, GIS, time series forecasting)
- Finance & Economics (risk modeling, forecasting, portfolio analysis)
- Engineering & Technical Analysis (optimization, simulation, quality control)

## Technical Specifications

### Supported File Formats
- **Tabular Data**: CSV, TSV, Excel (.xlsx, .xls), Parquet, JSON
- **Molecular Biology**: FASTA, FASTQ, GenBank, PDB, SDF, MOL, MOL2
- **Geospatial**: GeoJSON, Shapefile, KML
- **Images**: PNG, JPEG, TIFF (for analysis)
- **Documents**: PDF, TXT, Markdown

### AI Capabilities
- **Code Execution**: Python, R with full scientific computing stack
- **ML Frameworks**: scikit-learn, XGBoost, LightGBM, PyTorch, TensorFlow
- **Visualization**: matplotlib, seaborn, plotly, ggplot2
- **Statistical Analysis**: scipy, statsmodels, survival analysis packages
- **Domain Libraries**: RDKit, BioPython, scanpy, AnnData, pandas, numpy

### Output Formats
- Professional reports (PDF, DOCX)
- Presentation slides (PPTX)
- Publication-ready figures (SVG, PNG, PDF)
- Interactive dashboards
- Jupyter notebooks
- Raw data exports

## Pricing

1. **Open Source** (Free): Claude Scientific Skills available on GitHub under MIT license
2. **K-Dense Web**: $50 free credits to start, then pay-as-you-go
3. **Enterprise**: Custom pricing with dedicated support and custom deployments

## Key Differentiators

- End-to-end research pipeline from raw data to publication
- Intelligent model selection and hyperparameter optimization
- Publication-ready figure generation
- Works across multiple scientific domains
- Both open-source and hosted options available
- Data-grounded outputs with reduced hallucinations
- Full code execution with iterative refinement

## Security & Compliance

- SOC 2 Type II compliance (Enterprise)
- HIPAA-ready infrastructure (Enterprise)
- Data encryption at rest and in transit
- No training on user data
- Private deployment options available
- SSO/SAML integration (Enterprise)

## Social Links

- GitHub: https://github.com/K-Dense-AI
- Twitter/X: https://x.com/k_dense_ai
- LinkedIn: https://www.linkedin.com/company/k-dense-inc
- Slack Community: https://join.slack.com/t/k-densecommunity/shared_invite/zt-3iajtyls1-EwmkwIZk0g_o74311Tkf5g

## Example Use Cases

K-Dense Web has been used for diverse research including:
- Natural products drug discovery from COCONUT database
- Macroeconomic recession prediction
- Longevity gene analysis
- JWST exoplanet target prioritization
- Quantum chemistry VQE benchmarking
- Cancer drug response prediction
- ECG stress detection
- Clinical trial data analysis
- Financial risk modeling
- Market trend analysis
- And many more (45+ documented use cases)

## Site Structure

- **Homepage** (/): Product overview, features, pricing, use case highlights
- **Use Cases** (/use-cases): 45+ real research examples with session links
- **Enterprise** (/enterprise): Enterprise features and contact information
- **About** (/about): Company background and mission
- **FAQ** (/faq): Frequently asked questions

## How to Get Started

1. Visit https://app.k-dense.ai
2. Sign up for free ($50 credits included)
3. Upload your data or describe your research question
4. Let K-Dense Web analyze, model, and generate reports

For enterprise inquiries: contact@k-dense.ai

## Open Source

The Claude Scientific Skills project is available at:
https://github.com/K-Dense-AI/claude-scientific-skills

Licensed under MIT - free for personal and commercial use.

## Additional Resources for AI Crawlers

- **Sitemap**: https://k-dense.ai/sitemap.xml
- **RSS Feed**: https://k-dense.ai/feed.xml
- **robots.txt**: https://k-dense.ai/robots.txt

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Last updated: 2026-01
Version: 2.1