# K-Dense

> K-Dense is an AI company that builds agents for real research: a hosted platform, a lab instrument, enterprise deployments, and open-source tools. Its product portfolio spans K-Dense Web (a hosted AI research agent for individuals, labs and teams), Faraday (an AI co-scientist built into a benchtop lab instrument), K-Dense Enterprise (K-Dense Web deployed in a dedicated K-Dense cloud, your own cloud, or on-premises), and K-Dense BYOK (a free, MIT-licensed desktop app that runs on your own computer with the models you choose), plus more open-source projects. K-Dense also offers free hosted research tools (Rigor Scan, Claimscape and Pantheon), which are free to use but not open source. K-Dense agents autonomously execute complex tasks across science, engineering, healthcare, finance, and beyond.

For the comprehensive machine-readable context, see: https://www.k-dense.ai/llms-full.txt

## Quick facts

- **Company**: K-Dense Inc. — Palo Alto, CA (380 Portage Ave, Palo Alto, CA 94306)
- **Website**: https://www.k-dense.ai
- **Products**: K-Dense Web (https://app.k-dense.ai), Faraday (https://www.k-dense.ai/products/faraday), K-Dense Enterprise, and 10 open-source projects, including K-Dense BYOK
- **Free research tools** (free to use, not open source): Rigor Scan, Claimscape, Pantheon
- **Flagship product tagline**: Research. Analyze. Synthesize. (K-Dense Web)
- **Contact**: contact@k-dense.ai
- **Founded**: October 2025
- **Documented use cases**: 177+
- **Blog posts**: 71+

## Product portfolio

- **K-Dense Web** (Paid) — Research. Analyze. Synthesize. https://www.k-dense.ai/products/k-dense-web
- **Faraday** (Custom) — The AI co-scientist that lives in your lab. https://www.k-dense.ai/products/faraday
- **K-Dense Enterprise** (Custom) — The research agent, deployed your way. https://www.k-dense.ai/enterprise
- **K-Dense BYOK** (Free & Open Source) — Your local AI co-scientist. https://github.com/K-Dense-AI/k-dense-byok
- **Claude Scientific Writer** (Free & Open Source) — Research-backed scientific writing. https://github.com/K-Dense-AI/claude-scientific-writer
- **Scientific Agent Skills** (Free & Open Source) — 160+ ready-to-use scientific skills. https://github.com/K-Dense-AI/scientific-agent-skills
- **Open-source ecosystem** (Free) — additional libraries, skills, and tools. https://www.k-dense.ai/products#open-source

## How Faraday, K-Dense Web, K-Dense BYOK and K-Dense Enterprise differ

The essentials from the comparison table at https://www.k-dense.ai/products#compare . The full comparison is in https://www.k-dense.ai/llms-full.txt .

### Faraday

- URL: https://www.k-dense.ai/products/faraday
- What it is: An AI co-scientist built into a benchtop instrument.
- Best for: Labs whose data cannot leave the building.
- Price and license: Quote on request.
- Where it runs: On the instrument, on your bench.
- Where your data goes: Stays on the box. Every outbound request is sanitized by the gate, and expert questions wait for your approval.

### K-Dense Web

- URL: https://www.k-dense.ai/products/k-dense-web
- What it is: A hosted AI research agent in your browser.
- Best for: Finished deliverables with nothing to install.
- Price and license: Instant answers free, then pay as you go. Plus $199/mo, Team $499/mo.
- Where it runs: K-Dense's managed cloud.
- Where your data goes: Uploaded to K-Dense's cloud and sent to frontier model providers. Encrypted, never used for training.

### K-Dense BYOK

- URL: https://github.com/K-Dense-AI/k-dense-byok
- What it is: A free, open-source app on your own computer.
- Best for: Hands-on control over models, keys and cost.
- Price and license: Free, MIT license. You pay your model provider.
- Where it runs: Your own computer.
- Where your data goes: Stays in folders on your computer. Each request goes to the model provider you pick.

### K-Dense Enterprise

- URL: https://www.k-dense.ai/enterprise
- What it is: K-Dense Web, deployed for your organization.
- Best for: Organizations that need their own cloud, SSO and SLAs.
- Price and license: Custom quote.
- Where it runs: A dedicated K-Dense cloud, your AWS, GCP or Azure, or your data center.
- Where your data goes: Stays inside your own cloud or data center, with models on endpoints you control.

## What K-Dense Web does

K-Dense Web, the flagship product, is a fully hosted AI platform that autonomously:

1. **Analyzes data**: CSV, Excel, FASTA, PDB, SDF, and 200+ scientific formats.
2. **Searches and retrieves context**: 250+ databases plus hundreds of thousands of on-demand tools.
3. **Runs machine learning**: automatic model selection, hyperparameter tuning, SHAP interpretability.
4. **Generates professional outputs**: papers, slides, figures, manuscript-quality documentation.
5. **Supports multiple domains**: science, engineering, healthcare, finance, market research, and more.
6. **Works with AI agents through WebMCP**: an agent in the user's browser can start research sessions, follow runs, read reports and output files, reply, and organize sessions through typed tools. Details: https://www.k-dense.ai/docs/webmcp

## Key differentiators

- End-to-end pipeline from raw data to publication.
- Executes real Python/R/ML code (not just generates text).
- Intelligent model selection and hyperparameter optimization.
- Grounded outputs with reduced hallucinations.
- 177+ documented real-world use cases.
- Both open-source and hosted offerings.
- WebMCP support, so in-browser AI agents use K-Dense Web through its own tools rather than screenshots and clicks.

## Pricing overview

- **Open-source packages**: Free. See "Open source" section below and each repository for license details.
- **K-Dense BYOK**: Free, MIT license. You pay your model provider.
- **K-Dense Web Personal**: Pay-as-you-go, with free Instant answers.
- **K-Dense Web Plus**: $199/month (300 credits/month).
- **K-Dense Web Team**: $499/month (800 credits/month, unlimited seats).
- **Faraday**: Quote on request. Early access; request a demo at mailto:contact@k-dense.ai?subject=Faraday%20demo%20request
- **K-Dense Enterprise**: Custom pricing, integrations, SSO, audit logging, on-prem options.
- **Research Grant Program**: 90% off the annual Team plan for non-commercial research by academic labs and non-profit researchers.
- **Hypothesis-to-Evidence Grant**: Fully-funded pilot (up to $5,000) for three Fellows taking a computational hypothesis to wet-lab evidence with K-Dense Web and Litmus Science.

## Open source

K-Dense ships 10 selected open-source libraries, skills, and tools for scientific agents, research automation, writing, data science, molecular optimization, and machine learning:

- **scientific-agent-skills** — 160+ ready-to-use scientific and research Agent Skills for biology, chemistry, medicine, scientific computing, and 78+ databases. → https://github.com/K-Dense-AI/scientific-agent-skills
- **claude-scientific-writer** — Deep research and scientific writing tool for publication-ready academic documents with literature lookup, citation verification, and CLI/plugin workflows. → https://github.com/K-Dense-AI/claude-scientific-writer
- **k-dense-byok** — Desktop AI research assistant that runs on your own computer with OpenRouter, your own API keys, supported subscriptions, or local models, plus specialist agents and parallel chats. → https://github.com/K-Dense-AI/k-dense-byok
- **mimeo** — CLI that researches an expert's public work, clusters their mental models, and emits a SKILL.md or AGENTS.md for coding agents. → https://github.com/K-Dense-AI/mimeo
- **mimeographs** — 80 ready-to-use expert SKILL.md and AGENTS.md profiles for founders, philosophers, scientists, and AI researchers. → https://github.com/K-Dense-AI/mimeographs
- **scientific-agents** — Research-grounded AGENTS.md profiles that turn generic agents into domain-aware scientific and engineering practitioners. → https://github.com/K-Dense-AI/scientific-agents
- **science-superpowers** — Composable methodology skills that guide research agents through question framing, literature grounding, analysis design, and pre-registration. → https://github.com/K-Dense-AI/science-superpowers
- **rowan-autosearch** — Agent-driven molecular optimization harness for Rowan workflows, RDKit constraints, auditable candidate logs, and HTML reports. → https://github.com/K-Dense-AI/rowan-autosearch
- **karpathy** — Agentic machine learning engineer built with the Claude Agent SDK, Google ADK, and Scientific Agent Skills. → https://github.com/K-Dense-AI/karpathy
- **agentic-data-scientist** — Adaptive multi-agent data science framework with planning, execution, validation, reflection, MCP integration, and Scientific Agent Skills. → https://github.com/K-Dense-AI/agentic-data-scientist

All repositories live under the K-Dense GitHub organization: https://github.com/K-Dense-AI

## Common questions

- **What is K-Dense?** An AI company that builds agents for real research: K-Dense Web (hosted), Faraday (a lab instrument), K-Dense Enterprise (private deployments), and open-source tools including K-Dense BYOK.
- **Who is it for?** Researchers, analysts, engineers, and operators who need to turn data and questions into decisions and publication-ready outputs.
- **How does billing work?** Pay-as-you-go credits (non-expiring) or monthly/annual subscriptions with refreshing credits.
- **Can an AI agent use K-Dense Web for me?** Yes. K-Dense Web supports WebMCP, so an agent running in a WebMCP-capable browser can drive it through typed tools after the user signs in. See https://www.k-dense.ai/docs/webmcp .
- **Is my data private?** Yes. Data is encrypted in transit and at rest; we do not train on user data. Enterprise offers private cloud and on-prem options.
- **What about open source?** K-Dense publishes selected open-source projects for Agent Skills-compatible tools, research agents, data science, machine learning, and scientific writing — see the "Open source" section above.

## Key pages

- [Homepage](https://www.k-dense.ai): Company overview and product portfolio
- [Products](https://www.k-dense.ai/products): Full product portfolio — paid platforms and open-source tools
- [K-Dense Web](https://www.k-dense.ai/products/k-dense-web): Flagship hosted AI research agent
- [Faraday](https://www.k-dense.ai/products/faraday): AI co-scientist delivered as a laboratory instrument, run on hardware you own
- [About](https://www.k-dense.ai/about): Company mission, team, values
- [Use Cases](https://www.k-dense.ai/use-cases): 177+ real research examples, one page each
  - [Science use cases](https://www.k-dense.ai/use-cases/area/science): 72 projects — Life sciences, biomedical research, and physical sciences
  - [Finance & Investment use cases](https://www.k-dense.ai/use-cases/area/finance): 28 projects — Economics, investment analysis, and financial modeling
  - [Engineering & Technology use cases](https://www.k-dense.ai/use-cases/area/engineering): 31 projects — Technical systems, AI, robotics, and energy
  - [Health & Climate use cases](https://www.k-dense.ai/use-cases/area/environment): 30 projects — Public health, air quality, agriculture, and climate modeling
  - [Geopolitics & Strategy use cases](https://www.k-dense.ai/use-cases/area/society): 16 projects — Demographics, policy analysis, cultural studies, and strategic planning
- [Pricing](https://www.k-dense.ai/pricing): Personal, Plus, Team, Enterprise, and open-source
- [Enterprise](https://www.k-dense.ai/enterprise): Custom integrations & deployment
- [Research Grant Program](https://www.k-dense.ai/research-program): 90% off Team plan for research orgs
- [Hypothesis-to-Evidence Grant](https://www.k-dense.ai/hypothesis-to-evidence-grant): Fully-funded pilot — computational hypothesis to wet-lab evidence
- [Blog](https://www.k-dense.ai/blog): Insights & updates
- [Docs](https://www.k-dense.ai/docs): Prompting guide, effort levels, WebMCP for AI agents, security, tutorials
- [Effort Levels](https://www.k-dense.ai/docs/effort-levels): Instant (free), Standard ($9 cap), Pro ($29 cap) — behavior, validation depth, how to choose
- [WebMCP for AI Agents](https://www.k-dense.ai/docs/webmcp): The tools K-Dense Web offers AI agents in the browser, page by page, what is never exposed (payments, sharing, deleting, account settings), and the safeguards on credit-spending actions
- [Security](https://www.k-dense.ai/security): Data handling, retention, deployment options, compliance position
- [Rigor Scan](https://www.k-dense.ai/tools/rigor-scan): Free reporting check for research papers. 74 published checks, each linked to its evidence, plus software checks that recalculate statistics, flag retracted references and problem cell lines, and open data links. The PDF is read in the browser and never uploaded as a file; its extracted text is sent for checking and isn't saved.
- [Claimscape](https://www.k-dense.ai/tools/claimscape): Free evidence map for any research claim. Reads up to 300 of the most relevant PubMed abstracts, sorts them by study design, plots them by year and summarizes each design with a 95% interval; every paper opens with the sentence its verdict rests on.
- [Citation Telephone](https://www.k-dense.ai/tools/citation-telephone): Free tool that follows a cited claim back through the papers it cites. Each cited paper is read (in full when open access in Europe PMC, otherwise its abstract), the passage it is cited for is found among its own sentences, and each hop says whether the citing sentence matches its source, goes further or changes it, until the trail reaches an origin, a paper that doesn't say it, or a closed paper.
- [Pantheon](https://pantheon.k-dense.ai/): Free tool that puts one science or research question to 80 AI personas (scientists, founders, philosophers and AI researchers) built from each person's public writing. They answer in parallel in their own voices, grounded in cited web sources, followed by a consensus of where the panel agrees, where it diverges and what to do next. Replies do not come from the real people.
- [Benchmarks](https://www.k-dense.ai/benchmarks): Published benchmark results, including unfavorable ones
- [Publications](https://www.k-dense.ai/publications): Research papers and pre-prints from the K-Dense team
- [Compare](https://www.k-dense.ai/compare): K-Dense Web vs Claude Science, ChatGPT, Claude Code, OpenAI Prism, and our open-source skills
- [Tutorials](https://www.k-dense.ai/tutorials): Step-by-step video tutorials
- [Newsletter](https://www.k-dense.ai/newsletter): AI research updates
- [FAQ](https://www.k-dense.ai/faq): Frequently asked questions

## Blog posts

- [Meet the Fellows Running End-to-End Agentic Science](https://www.k-dense.ai/blog/introducing-hypothesis-to-evidence-fellows) — Hypothesis-to-Evidence Grant fellows Joy-Yan Lam, Alexander Reading, and Daniel Pascal will pilot closed-loop experimentation with K-Dense and Litmus Science.
- [Same Cells, Different Answers: K-Dense Web Re-Tests the Kang 2018 Interferon Response for Pseudoreplication](https://www.k-dense.ai/blog/kang-2018-interferon-pseudoreplication-reanalysis) — K-Dense Web reproduced the Kang 2018 interferon PBMC study three ways and found 2,632 cell-level effects that fade once each donor counts as one replicate.
- [If AI Wants the Public's Trust, It Should Cure Something](https://www.k-dense.ai/blog/ai-should-cure-something) — Public fear of AI keeps rising, and much of it is earned. The way back is not another math milestone. It is AI that visibly improves health and science.
- [Introducing Citation Telephone: Trace a Cited Claim Back to Its Source](https://www.k-dense.ai/blog/introducing-citation-telephone) — Citation Telephone follows a cited claim back through the papers it cites, reads each one, and shows where the claim came from and what changed on the way.
- [Where Structure Stops Explaining TP53: K-Dense Web Maps 3,629 Missense Mutations Against Function and ClinVar](https://www.k-dense.ai/blog/tp53-structure-vs-function-3629-missense-mutations) — K-Dense Web tested all 3,629 TP53 DNA-binding domain missense variants against structure, function and ClinVar, and exposed a circular pathogenicity benchmark.
- [Is the 4% Rule Safe? K-Dense Web Stress-Tests 155 Years of US Retirement Outcomes](https://www.k-dense.ai/blog/four-percent-rule-155-years-retirement-outcomes) — K-Dense Web simulated every 30-year US retirement since 1871. The 4% rule failed 3% of the time, and more realistic assumptions pushed that rate higher.
- [Normal Hemoglobin, Empty Tank: How Common Is Hidden Iron Deficiency in US Women?](https://www.k-dense.ai/blog/hidden-iron-deficiency-us-women-nhanes) — K-Dense Web analyzed CDC NHANES data and found that 3 in 4 iron-deficient US women have normal hemoglobin. Then an independent reviewer checked the report.
- [Every Instrument Speaks Its Own Language: Introducing LabMCP](https://www.k-dense.ai/blog/introducing-labmcp) — LabMCP is a free, open-source set of 32 connectors that let AI assistants run your lab instruments in plain language, inside the safety limits you set.
- [A Traffic Jam With No Cause: K-Dense Web Rebuilds the Sugiyama Ring-Road Experiment](https://www.k-dense.ai/blog/phantom-traffic-jam-ring-road-simulation) — K-Dense Web reproduced the famous 22-car ring-road jam in simulation, then checked every result against linear theory and the original paper before trusting it.
- [Reading AlphaFold Confidence Correctly: A Structural Census of All 21 Human CDKs](https://www.k-dense.ai/blog/alphafold-cdk-family-structural-census) — K-Dense Web analyzed AlphaFold models for all 21 human CDKs and found that chain-level confidence says almost nothing about the kinase domain drug hunters target.
- [Introducing Claimscape: See Where the Literature Stands on Any Claim](https://www.k-dense.ai/blog/introducing-claimscape) — Claimscape reads the most relevant PubMed abstracts on a claim, sorts them by study design and plots them over time, so you can see where the evidence stands.
- [Introducing Rigor Scan: A Free Reporting Check for Research Papers, Built on Jev](https://www.k-dense.ai/blog/introducing-rigor-scan) — Rigor Scan checks how completely a paper reports its design, statistics, materials, data and claims, using Jev to tie every result to the sentence behind it.
- [K-Dense BYOK on CompBioBench: Three Models, One Harness](https://www.k-dense.ai/blog/compbiobench-three-runs) — Gemini 3.8 Flash scored 94% and GPT-5.6 SOL 92% on CompBioBench v1, a statistical tie. DeepSeek V4 Pro scored 81% on the same K-Dense BYOK harness (n=100).
- [Introducing Data Connectors: Import Directly from Amazon S3 and Google Cloud Storage](https://www.k-dense.ai/blog/introducing-data-connectors) — Connect your own Amazon S3 or Google Cloud Storage bucket to K-Dense Web and import files straight into a research session, read-only and encrypted.
- [Introducing K-Bench 01: Nine Frontier Models, 178 Real Scientific Tasks, and a Lot of Confident Wrong Answers](https://www.k-dense.ai/blog/introducing-k-bench-01-internal-benchmark) — K-Bench 01 is our internal benchmark built from 178 real scientific tasks. Nine frontier models ran them end to end; only one clears the acceptability bar.
- [The Silent 97%: Introducing the waypoint-bio Agent Skill](https://www.k-dense.ai/blog/introducing-waypoint-agent-skill) — A microbiome foundation model silently discards 97% of a malformed table and returns a valid embedding. We measured what an Agent Skill does about that.
- [How to Use Multica for Scientific Research](https://www.k-dense.ai/blog/multica-scientific-research) — Real research runs on a self-hosted Multica workspace using K-Dense Scientific Agent Skills: trials, variants, literature, and cross-model review.
- [The Millimeter Problem: Introducing the lab-hardware-cad Agent Skill](https://www.k-dense.ai/blog/lab-hardware-cad-skill) — Introducing lab-hardware-cad, an open-source Agent Skill that turns any AI agent into a CAD engineer for lab hardware, benchmarked over 98 geometry-scored runs.
- [K-Dense Web and Litmus Science: Closing the Loop from Hypothesis to Experiment](https://www.k-dense.ai/blog/k-dense-litmus-closing-the-loop) — K-Dense and Litmus Science are connecting AI-powered research with on-demand lab execution, helping scientists move from questions to evidence faster.
- [AI Co-Scientists, Answered: 20 Questions from a Live Session with a University Research Center](https://www.k-dense.ai/blog/ai-co-scientists-answered-20-questions) — Twenty questions from a live session with a university multiomics center on what K-Dense does, where AI for science helps today, and where it still falls short.
- [K-Dense Web vs. Claude Science: K-Dense Leads on Execution and Overall Score](https://www.k-dense.ai/blog/k-dense-web-vs-claude-science) — A 20-task benchmark found K-Dense Web stronger at producing auditable research bundles, while Claude Science held a narrow scientific-quality lead.
- [Benchmarking Google's Omni Flash for Scientific Video](https://www.k-dense.ai/blog/benchmarking-google-omni-flash-scientific-video) — A 35-case K-Dense benchmark of Google's Omni Flash shows stunning scientific video quality, but unreliable text, physics, and factual correctness.
- [Benchmarking Nano Banana 2 Lite for Scientific Image Generation](https://www.k-dense.ai/blog/benchmarking-nano-banana-2-lite-scientific-image-model) — A 240-image benchmark of four scientific image models shows Nano Banana 2 Lite is fastest, while GPT Image 2 still leads on raw figure quality.
- [AI Scientists Need Lab Escape Rooms, Not More Exams](https://www.k-dense.ai/blog/science-needs-better-black-boxes) — The next AI scientist benchmark should be a lab escape room: a fresh hidden world, limited probes, real evidence, and no place for science theater to hide.
- [Benchmarking NVIDIA BioNeMo Agent Toolkit Skills for NIM microservices](https://www.k-dense.ai/blog/benchmarking-nvidia-bionemo-nim-skill) — A controlled benchmark of 10 NVIDIA BioNeMo Agent Toolkit skills for NIM microservices shows where skills win: routing, cost, scale, and weak-model reliability.
- [Reproduction, Not Generation, Is AI's Killer App for Science](https://www.k-dense.ai/blog/reproduction-not-generation-ai-for-science) — AI is flooding science with claims no one can check. The quieter story: agents now reproduce most published findings — and that is the bigger deal.
- [Can an AI Agent Run Your Mass Spec Pipeline? Benchmarking the PyOpenMS Skill](https://www.k-dense.ai/blog/benchmarking-pyopenms-skill-mass-spectrometry) — A reproducible 250-run study of feature detection, adduct grouping, quantification, and identification, run by an AI agent with and without the pyOpenMS skill.
- [The Week Science Models Became Real](https://www.k-dense.ai/blog/frontier-science-models-arrive) — Fable 5 and GPT-Rosalind show frontier AI moving into scientific workflows. The next bottleneck is not intelligence, but evidence.
- [Beyond RDKit: Benchmarking the Rowan Agent Skill Against Experiment](https://www.k-dense.ai/blog/benchmarking-rowan-skill-chemistry) — 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.
- [The Model Is No Longer the Bottleneck](https://www.k-dense.ai/blog/the-model-is-no-longer-the-bottleneck) — Anthropic showed a general model can rival ChemDraw at NMR. The real story for scientists: the bottleneck has moved from the model to the workflow around it.
- [The AI Co-Scientist Is Here. The Bottleneck Is Verification.](https://www.k-dense.ai/blog/ai-co-scientist-verification-bottleneck) — AI agents are moving into real scientific workflows. The question for working scientists is not whether they are powerful, but whether they are verifiable.
- [Your AI Assistant Reasons Like a Generalist. Science Needs a Specialist.](https://www.k-dense.ai/blog/introducing-scientific-agents) — Scientific Agents: 503 open-source AGENTS.md profiles that teach any AI agent to reason like a senior practitioner in a specific science or engineering field.
- [One Skill, 78 Databases: Why We Didn't Build 78 Skills](https://www.k-dense.ai/blog/database-lookup-one-skill-78-databases) — One Agent Skill gives a research agent 78 public scientific and economic databases. Here is the design argument, with real token and routing benchmarks.
- [Introducing Science Superpowers: Scientific Discipline for Your Research Agent](https://www.k-dense.ai/blog/introducing-science-superpowers) — Our new open source methodology makes AI research agents pre-register hypotheses, work reproducibly, and verify before they claim. Pre-registration over TDD.
- [Toward Smarter Scientific Search: Exa Joins the Scientific Agent Skills Library](https://www.k-dense.ai/blog/towards-smarter-scientific-search-exa-scientific-agent-skills) — Exa is now integrated into K-Dense's Scientific Agent Skills library, bringing neural web search and URL extraction to AI-driven scientific research.
- [Mapping the RAS Mutation Landscape in Pancreatic Cancer with K-Dense Web](https://www.k-dense.ai/blog/ras-mutation-landscape-pancreatic-cancer-k-dense) — K-Dense Web analyzed global RAS mutation prevalence, drug eligibility, statistics, and the clinical-trial landscape in pancreatic cancer (PDAC).
- [The Virus in the Dust: How K-Dense Web Can Accelerate Hantavirus Research](https://www.k-dense.ai/blog/hantavirus-research-k-dense-web) — A practical look at how K-Dense Web can help researchers synthesize hantavirus literature, surveillance, ecology, and public health evidence.
- [What 116 Declassified UAP Files Actually Say](https://www.k-dense.ai/blog/pursue-uap-declassified-files-analysis) — K-Dense Web analyzed 116 declassified UAP files in one prompt, producing a 60-page report separating aerial activity from extraterrestrial evidence.
- [What K-Dense Web Actually Saves: A 67-Case ROI Audit](https://www.k-dense.ai/blog/k-dense-web-roi-67-use-cases) — K-Dense Web ROI audit across 67 public use cases: $3.08M of analyst work delivered by K-Dense Web plus a human for $5,670 in credits.
- [From Blank Page to Research Roadmap: How AI Helps Define New Scientific Directions](https://www.k-dense.ai/blog/ai-research-direction-discovery-phd-proposal) — K-Dense Web synthesizes literature, finds research gaps, and generates a 26-page PhD proposal on biologically inspired robot actuators in about 45 minutes.
- [Catalyzing Breakthroughs: A 42-Page ARPA-H Policy Report, Generated in One K-Dense Web Session](https://www.k-dense.ai/blog/arpa-h-policy-report-analysis) — ARPA-H policy analysis: K-Dense Web produced a 42-page report with 14 figures, 71 verified citations, and 7 evidence-based recommendations in one session.
- [AI-Powered Biotech Due Diligence: Structure Therapeutics and the $100B GLP-1 Opportunity](https://www.k-dense.ai/blog/structure-therapeutics-gsbr-1290-due-diligence) — K-Dense Web delivers a 7-step due diligence on Structure Therapeutics' GSBR-1290, an oral GLP-1 agonist targeting a $6.5B peak revenue obesity opportunity.
- [AI Co-Scientist, Not AI Scientist: Why the Name Matters](https://www.k-dense.ai/blog/ai-co-scientist-not-ai-scientist) — Why we put the hyphen in front of every product we build. The case, from Benchling to AlphaFold to Polanyi, for keeping the human scientist front and center.
- [Science is Multimodal: K-Dense and NVIDIA on Nemotron 3 Nano Omni](https://www.k-dense.ai/blog/nvidia-nemotron-nano-omni-multimodal-agentic-science) — K-Dense is evaluating Nemotron 3 Nano Omni — NVIDIA's new open omni-modal model that unifies vision, audio, and language for — agentic scientific workflows.
- [Introducing Pantheon: One Question, 80 Voices](https://www.k-dense.ai/blog/introducing-pantheon-80-voices) — Pantheon is a free K-Dense app that sends one research question to 80 AI personas, streaming diverse perspectives with cited sources and consensus.
- [Introducing mimeo and 80+ Mimeographs: Clone an Expert's Way of Thinking Into Your Agent](https://www.k-dense.ai/blog/introducing-mimeo-and-mimeographs) — mimeo distills how great minds like Jobs, Buffett, and Wittgenstein reason into a SKILL.md or AGENTS.md your agent can load, with 80+ experts ready today.
- [Security in the Science Agent Era: What Every Lab Needs to Know Before Installing Skills](https://www.k-dense.ai/blog/skill-security-before-you-install) — Skills are executable research code with a personality. A practical guide to prompt-injection risks, poisoned SKILL.md files, auditing, and version pinning.
- [The Sandboxed AI Scientist: Pairing NVIDIA OpenShell with Scientific Agent Skills](https://www.k-dense.ai/blog/sandboxed-ai-scientist-openshell-skills) — Pair NVIDIA OpenShell's policy-governed runtime with Scientific Agent Skills to run autonomous research agents that are highly capable and genuinely safe.
- [K-Dense Web Office Hours: Q&A Recap (April 17, 2026)](https://www.k-dense.ai/blog/office-hours-recap-april-2026) — April 2026 Office Hours recap: open source model support, model performance, K-Dense Web platform comparisons, and enterprise deployment options.
- [Pharma Competitive Intelligence in One Session: CT-388 and the GLP-1/GIP Obesity Landscape](https://www.k-dense.ai/blog/ct388-competitive-intelligence-obesity) — K-Dense Web queried 4 databases and ran 7 Python scripts to produce a 44-page competitive intelligence report on CT-388, Roche's GLP-1/GIP obesity agonist.
- [From Prompt to Phase III: Biomarker Discovery for Bispecific Antibodies in DLBCL](https://www.k-dense.ai/blog/dlbcl-biomarker-discovery-bispecific-antibodies) — K-Dense Web integrated 6 databases, ranked 6 candidate biomarkers, and produced Phase III trial design recommendations for CD20xCD3 bispecifics in DLBCL.
- [From Genomics to Vaccine Strategy: Mapping the PDAC Neoantigen Landscape in a Single Session](https://www.k-dense.ai/blog/pdac-neoantigen-landscape-inest-strategy) — K-Dense Web queried 6 databases, modeled KRAS structure, mapped the tumor microenvironment, and built a 36-slide iNeST strategy for PDAC neoantigen vaccines.
- [GPU-Accelerate Your Science: 58x Average Speedup with a Single Skill](https://www.k-dense.ai/blog/optimize-for-gpu-skill) — The optimize-for-gpu skill rewrites CPU-bound Python for NVIDIA GPUs across 12 libraries in data science, ML, and simulation, with 58x average speedup.
- [K-Dense Web Office Hours: Q&A Recap (March 17, 2026)](https://www.k-dense.ai/blog/office-hours-recap-march-2026) — Key takeaways from our March 2026 Office Hours covering data privacy, enterprise features, and system methodology documentation.
- [K-Dense Web Scores 90.0% on BixBench-Verified-50](https://www.k-dense.ai/blog/bixbench-verified-50) — K-Dense Web scored 45/50 on BixBench-Verified-50, a cleaned biology-agent benchmark designed to separate real model mistakes from benchmark noise.
- [How VCs Use K-Dense Web for Due Diligence: CoreWeave and Ramp Case Studies](https://www.k-dense.ai/blog/vc-due-diligence-k-dense-web) — K-Dense Web automates VC due diligence with research, financial modeling, and publication-ready reports, with CoreWeave ($19B) and Ramp ($32B) case studies.
- [The GBM Trial Paradox: 1,913 Trials, Zero Breakthrough Approvals](https://www.k-dense.ai/blog/gbm-clinical-trial-landscape-analysis) — GBM clinical trial analysis: 1,913 trials, yet zero breakthrough approvals. Three insights explain the gap and where glioblastoma research must go next.
- [K-Dense Web vs OpenAI Prism: Task Execution vs Writing Assistance](https://www.k-dense.ai/blog/k-dense-web-vs-openai-prism) — K-Dense Web vs OpenAI Prism: Prism helps you write papers, while K-Dense Web does the research. See why the distinction matters and how to use them together.
- [Accelerating Translational Research: How K-Dense is Transforming Drug Development](https://www.k-dense.ai/blog/accelerating-translational-research-drug-development) — K-Dense is an agentic AI co-scientist platform that turns slow, sequential translational research into an integrated, insight-driven drug development engine.
- [Autonomous Drug Discovery: Mining 700,000 Natural Products for Antimicrobial Candidates](https://www.k-dense.ai/blog/antimicrobial-drug-discovery-natural-products) — How K-Dense Web autonomously processed the COCONUT database to identify 50 prioritized antimicrobial candidates using unsupervised machine learning.
- [Autonomous Medical Device Safety Analysis: Mining 10,000 ICD Adverse Events from the FDA MAUDE Database](https://www.k-dense.ai/blog/icd-adverse-events-fda-analysis) — K-Dense Web autonomously analyzed 10,000 ICD failure reports from the FDA MAUDE database using NLP and statistics, revealing manufacturer-specific patterns.
- [Agent Skills: The Final Piece for AI-Powered Scientific Research](https://www.k-dense.ai/blog/agent-skills-final-piece-for-ai-powered-research) — Agent Skills close the gap between raw AI intelligence and domain expertise, adding 140 open-source capabilities to AI scientific research workflows.
- [Guide to Prompting K-Dense Web: Get Better Results in Minutes](https://www.k-dense.ai/blog/guide-to-prompting-k-dense-web) — Write effective prompts for K-Dense Web. Six key elements turn vague requests into precisely executed tasks with publication-ready outputs.
- [K-Dense Web vs ChatGPT: Why Traditional AI Assistants Fall Short for Research](https://www.k-dense.ai/blog/k-dense-web-vs-chatgpt) — A detailed comparison of K-Dense Web and ChatGPT showing why autonomous task execution beats conversational AI for any complex work.
- [K-Dense Web vs Claude Code: Different Tools for Different Jobs](https://www.k-dense.ai/blog/k-dense-web-vs-claude-code) — K-Dense Web is a multi-agent system orchestrating Opus 4.5, Gemini 3 Pro, and Claude Code on a high-compute backend for complex end-to-end workflows.
- [K-Dense Web vs Scientific Agent Skills: Why We Built Both (And Which One You Should Use)](https://www.k-dense.ai/blog/k-dense-web-vs-scientific-agent-skills) — K-Dense Web vs Scientific Agent Skills: our open-source skills give researchers AI tools; K-Dense Web adds more skills, agents, cloud compute, and zero setup.
- [Agentic Data Scientist: An Open Source AI That Actually Does the Analysis](https://www.k-dense.ai/blog/agentic-data-scientist-open-source) — Agentic Data Scientist is a free, open-source multi-agent framework that plans, runs, and validates full data science workflows autonomously.
- [Building Autonomous ML Pipelines with K-Dense Web](https://www.k-dense.ai/blog/autonomous-ml-pipelines) — How K-Dense Web automates the machine learning workflow, from data prep to model selection and deployment-ready results.
- [Claude Scientific Writer: Our Open Source Tool for AI-Powered Research Writing](https://www.k-dense.ai/blog/claude-scientific-writer-open-source) — Claude Scientific Writer is a free, open-source tool combining deep research with publication-ready papers, grants, posters, and clinical reports.
- [Karpathy: An Open Source Agentic Machine Learning Engineer](https://www.k-dense.ai/blog/karpathy-agentic-ml-engineer) — Karpathy is our open-source AI agent that trains state-of-the-art ML models autonomously, from data preprocessing to hyperparameter optimization.
- [Introducing K-Dense Web: Research. Analyze. Synthesize. for Complex Research](https://www.k-dense.ai/blog/introducing-k-dense-web) — Learn how K-Dense Web transforms complex research tasks into automated workflows, delivering publication-ready results across science, finance, and engineering.

Full post text is available at `https://www.k-dense.ai/blog/<slug>.md` in raw markdown.

## Security & compliance

- Data is encrypted in transit and at rest.
- K-Dense does not train on user data.
- K-Dense is not yet SOC 2 audited. No compliance certification is claimed.
- Enterprise supports SSO/SAML, audit logging, private cloud, and on-premises deployment options.

## Social

- GitHub: https://github.com/K-Dense-AI
- Twitter/X: https://x.com/k_dense_ai
- LinkedIn: https://www.linkedin.com/company/k-dense-inc
- YouTube: https://www.youtube.com/@K-Dense-Inc
- Reddit: https://www.reddit.com/user/-k-dense-/

## Machine-readable resources

- Sitemap: https://www.k-dense.ai/sitemap.xml
- RSS feed: https://www.k-dense.ai/feed.xml
- Summary LLM context: https://www.k-dense.ai/llms.txt
- Well-known LLM context: https://www.k-dense.ai/.well-known/llms.txt
- Full LLM context: https://www.k-dense.ai/llms-full.txt
- Typo-safe LLM context alias: https://www.k-dense.ai/llm.txt
- Blog raw markdown: https://www.k-dense.ai/blog/<slug>.md

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Last updated: 2026-10-20