An AI agent with access to 250+ databases, hundreds of thousands of on-demand tools, and native support for 200+ scientific data formats. Autonomously executes complex tasks across science, engineering, healthcare, finance, and beyond.
Pay-as-you-go pricing
See It In Action
Explore 79 real research sessions powered by K‑Dense Web, organized by domain
Analyze 10,000 FDA MAUDE reports for implantable cardioverter defibrillators to identify failure modes by manufacturer.
Comprehensive review of germline and somatic variant callers for clinical genomics with ACMG/AMP classification frameworks.
A graph-topology comparison of NASA's newly released COSMOS-Web map of 164,000 galaxies.
Multi-omic biomarker analysis for glofitamab/mosunetuzumab stratification in DLBCL using cBioPortal, DepMap, and FAERS with Phase III SAP recommendations.
Predict ion suppression factors in LC-MS metabolomics using chromatographic context features and SHAP interpretability.
Emergency response guide for the 5 deadliest venoms: cone snail, box jellyfish, wandering spider, inland taipan, and funnel-web.
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Platform Capabilities
Not a chatbot with a science skin. K‑Dense Web writes and executes real code, connects to real databases, reads your actual instrument files, and produces outputs you can publish.
Direct access to scientific, clinical, financial, and chemical databases. Dedicated integrations for PubMed, ChEMBL, UniProt, SEC EDGAR, FRED, and dozens more, plus multi-database packages like BioServices and BioPython that each unlock 30‑40 additional sources.
K‑Dense writes and executes code on the fly, turning every function in every Python package into a callable tool. Pre-built optimizations cover the most common workflows, but the system is never limited to what is pre-defined. Hundreds of thousands of capabilities, generated on demand.
Use any of the 500,000+ packages on PyPI. Ships with curated optimizations for 200+ of the most common scientific, research, and financial packages including RDKit, Scanpy, scikit-learn, PyTorch, BioPython, statsmodels, and more.
Native support for instrument files, data formats, and outputs across every major scientific domain. From FASTA and BAM in genomics to DICOM and SVS in medical imaging, mzML in mass spectrometry, FITS in astronomy, CIF and POSCAR in materials science, FCS in flow cytometry, and hundreds more.
Generate manuscript-ready papers, presentation slides, LaTeX and PowerPoint posters, PDF reports, interactive visualizations, scientific schematics, and figures. Not just code: deliverables you can submit, present, or share.
Real research sessions across science, finance, engineering, health, and society — each with shareable outputs, and most with downloadable PDF reports.
Data Compatibility
From raw instrument output to publication-ready deliverables, K‑Dense handles the formats your research actually uses. Native support across 14 scientific domains.
The Difference
Traditional LLMs are great at answering questions. K‑Dense Web is built to do the research.
Open Source
We ship a growing suite of open-source libraries, skills, and tools that anyone can use — with or without a K‑Dense account.
141 ready-to-use scientific skills
A comprehensive collection of scientific and research skills for any AI agent that supports the open Agent Skills standard. Covers biology, chemistry, medicine, cancer genomics, drug-target binding, molecular dynamics, RNA velocity, geospatial science, time series forecasting, 78+ scientific databases, and more.
Research-backed scientific writing
A deep research and writing tool for publication-ready papers, reports, posters, grant proposals, literature reviews, and other academic documents. It researches before writing, supports real-time literature lookup, verifies citations, converts documents, and can run as a Claude Code plugin, Python package, or native CLI.
Your local AI co-scientist
A free, open-source research assistant called Kady that runs on your desktop and uses your own API keys. It can answer directly, delegate bigger tasks to specialist agents, run multiple chats in parallel, and switch across tool-capable OpenRouter or local Ollama models.
Clone an expert into your agent
Point it at an expert and mimeo reads the internet on your behalf, including talks, essays, interviews, papers, letters, and other canonical sources. It distills the recurring mental models into a production-ready SKILL.md or AGENTS.md your coding agent can load.
80 pre-built expert skills
A collection of 80 ready-to-use expert skills that clone the thinking of founders, philosophers, scientists, and AI researchers into your agent. Each folder contains SKILL.md and AGENTS.md files generated with mimeo and ready to drop into a project.
Try Pantheon liveExpert AGENTS.md profiles
Expert-thinking AGENTS.md profiles that teach AI agents to reason like senior scientific and engineering practitioners. Each profile captures how a domain expert frames problems, chooses tools and data, stress-tests claims, troubleshoots, and reports findings.
Pre-registration for research agents
A computational-science methodology for research agents, built from composable skills plus bootstrap instructions that make agents actually use them. It adapts the Superpowers workflow to science by emphasizing falsifiable questions, literature grounding, analysis design, and pre-registration before looking at outcomes.
Agent-driven molecular optimization
A scoring harness and lab notebook for agent-driven molecular property optimization with Rowan quantum and ML workflows. Agents propose analogs, score candidates, check drug-likeness with RDKit, and leave an auditable JSON and HTML trail for every candidate, constraint, payload, and rationale.
An agentic ML engineer
An agentic machine learning engineer that trains state-of-the-art ML models using the Claude Agent SDK and Google ADK. It demonstrates how Scientific Agent Skills can power machine-learning workflows with a simple, reproducible agent implementation.
Adaptive multi-agent data science
An open-source framework for complex data science tasks built on Google's Agent Development Kit and the Claude Agent SDK. It separates planning from execution, validates work continuously, reflects on progress, and adapts the analysis plan as discoveries emerge.
From the Blog
Stay up to date with AI research automation tips and product updates
A reproducible 250-run study of feature detection, adduct grouping, quantification, and identification, run by an AI agent with and without the pyOpenMS skill.
Fable 5 and GPT-Rosalind show frontier AI moving into scientific workflows. The next bottleneck is not intelligence, but evidence.
A reproducible study of pKa, logD, tautomers, ADME, and docking run by an AI agent with the Rowan skill, measured against RDKit and experimental ground truth.
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