Skip to main content

K‑Dense Web

Research. Analyze. Synthesize.

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.

Get Started

Instant answers are free · research runs are pay-as-you-go

How It Works

Describe the Work, Come Back to Deliverables

You are not prompting a chatbot turn by turn. You give K‑Dense an objective and your data, approve a plan, and it executes the whole thing — writing code, querying databases, training models, and producing figures along the way.

01

Describe the objective

Upload your data or point at a public dataset, then say what you want and what the deliverable should look like. The more specific the brief, the closer the first draft lands.

02

Approve the plan

K-Dense asks a handful of clarifying questions, then proposes an execution plan. You can change it before anything runs.

03

It executes

The agent writes and runs code, pulls from 250+ databases, trains and tunes models, generates figures, and validates its own work as it goes — for hours if the task warrants it.

04

You collect the outputs

Manuscripts, slides, posters, PDF reports, figures, and the underlying code and data — all downloadable, and all iterable if you want a section changed.

One dial controls depth, cost, and runtime

Every run happens at one of three effort levels. It is the biggest lever on output quality, and the one most new users miss.

Instant

A direct answer, the way a chat assistant would give it. No code, no execution plan, no research run.

Standard

A full research run from a single execution plan. The workhorse for most tasks.

Pro

Maximum compute, full validation, and a plan the agent revises as it learns. For work you intend to publish, submit, or act on.

Validation

Results You Can Check

A confident wrong answer is worse than no answer. Most of K‑Dense’s runtime goes not into producing output but into checking it: separate agents review the code, the sources, and the science before you ever see a result.

Code review

Every script the agent writes is checked and tested before its results are used downstream. A silent numerical error in step two would otherwise propagate through everything after it.

Citation verification

References are resolved against the literature rather than generated from memory: the paper has to exist, and it has to actually support the claim being made. This is where most AI research tools fail hardest.

Methodology critique

A reviewer agent argues with the scientific approach — whether the statistics are appropriate, whether the assumptions hold, whether the conclusion follows from the data — and the system revises based on that feedback.

How much of this runs depends on the effort level — Pro runs the full suite and acts on its own critique, which is why it is slower and why it is the right choice for anything you intend to publish or act on. It is not perfect, and we publish the benchmarks rather than asking you to take our word for it.

See It In Action

Example Use Cases

Explore 177 real research sessions powered by K‑Dense Web, organized by domain

We costed 67 of them against what a specialist would charge to produce the same deliverable alone: $3.1M of work for $5,670 in credits, a median of 107× faster — and that credit figure is the ceiling, since what you are charged caps at $29 per run. See the audit.

Nanomedicine

Nanoparticle Protein Corona Prediction

Build ML models to predict protein corona composition on gold nanoparticles using physicochemical properties.

Proteomics

TMT Proteomics Spike-in Validation

Validate TMT 6-plex quantification accuracy using Erwinia carotovora spike-in proteins with 97% correlation to ground truth.

Synthetic Biology

Lycopene Biosynthesis Optimization

Optimize enzyme expression ratios for lycopene production in E. coli using FBA and kinetic bottleneck analysis.

Immunology

Clustering and mapping of CyTOF bone marrow cells

Cluster and map CyTOF bone marrow cells with UMAP comparisons across clustering methods.

Immunology

Systematic analysis of Tdap vaccine immune responses

Systematically analyze Tdap vaccine immune responses including IgG fold-rise by clinical covariates.

Toxicology

PFOS Placental Toxicogenomics

Integrate EPA ToxCast with a 64,734-cell maternal-fetal interface atlas to nominate PFOS–PPARγ signaling in extravillous trophoblasts for mechanistic testing.

Platform Capabilities

Built for Real Research at Scale

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.

250+

Databases

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.

Unlimited

Tools, Generated on Demand

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.

500K+

Python Packages Available

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.

200+

Scientific Data Formats

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.

Publish

Ready Outputs

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.

177+

Documented Use Cases

Real research sessions across science, finance, engineering, health, and society — each with shareable outputs, and most with downloadable PDF reports.

Data Compatibility

Every Format Your Instruments Produce

From raw instrument output to publication-ready deliverables, K‑Dense handles the formats your research actually uses. Native support across 14 scientific domains.

.sam.vcf.fastq.gtf.tbi.clustal.nexusBIOM.pdbSMILESPOSCARKPOINTSGaussianQ-ChemDICOM.nii.gz.ndpi.qptiff.mzml.msp.idxml.featurexmlVOTable.lf.bin.fcs.mtx.hdf5.npy.gpkg.csv.xml.arrowSBML.docx.bib.svg.eps
.bam.bcf.bed.bigwig.gb.stockholm.newick.mol.cifInChICONTCARvasprun.xmlLAMMPSABINIT.dcm.nrrd.mrxsCODEX.mzxml.traml.mzid.fitsSpikeGLXOpen Ephys.h5ad10X.h5.shp.kml.tsv.yaml.feather.ndjson.pptx.md.png.webp
.cram.fasta.gff.bai.embl.phylip.phyloxml.sdf.xyzmmCIFINCAROUTCARCP2KFEFF.nii.svs.ome.tiffMERFISH.mgf.mztab.pepxml.fits.gz.ap.bin.nwb.loom.zarr.nc.geojsonPostGIS.json.parquet.xlsx.pdf.tex.html.tiff
Genomics & SequencingPhylogeneticsChemistry & MolecularMaterials ScienceMedical ImagingMass SpectrometryAstronomyNeuroscienceSingle-CellGeospatialData & InterchangeDocuments & Outputs

What Researchers Say

From the People Doing the Work

Unedited feedback from K‑Dense Web users across academia, biotech, and the clinic. Names withheld — much of this work is unpublished or under NDA.

This platform is essentially providing me a dozen PhDs and postdocs in my pocket. I see myself as the PI, asking questions to my postdocs, and my postdocs just keep giving me the information. It’s a postdoc that never says ‘I don’t know.’
Interdisciplinary researcherPhysics and biology, deep-tech founder
You upload a bunch of Excel spreadsheets and, without too much description, it figures out where the fold change is and then goes and does all the statistics. I thought it might struggle with figuring out all these columns, but it was remarkably good with that. It’s also much better at finding references than ChatGPT.
Principal investigatorMulti-omics lab, research university
I was very impressed with the original reports it was able to generate — the workflow was solid in terms of the actual analysis it was doing. A workflow like that by hand would take me a week, two weeks. I didn’t mind letting it go off and think for seven hours, because the output was such high quality.
Cancer researcherBioinformatics and wet lab
I dumped in everything I found — Google Sheets, PowerPoints, even images of experiments — and asked for a technical report. It took only 30, 40 minutes, and what I got was a very high quality report. It pulled the materials and methods, and it turned the images into graphs on its own. We kept 98% of the report the same. Otherwise it would have taken me days.
Computational biologistSynthetic biology company
The figures I got from K-Dense were much better in quality, and better at displaying what I wanted, than what I got from Gemini. With Gemini I had to do 15 different iterations just to capture what I wanted. K-Dense got it on the first shot — very crisp and ready to go.
Organism engineerStrain engineering, synthetic biology
I’ve been using K-Dense for this whole month, and so far I love everything about the program. The quality of the paper it gives is awesome. It’s legit — the references are true, there’s no hallucination.
Social scientistAnthropology and field research
To be able to have a good start on the manuscript, all out of the box and ready to use in Overleaf — that’s crazy. That saves weeks and weeks of work, no doubt. I’m dyslexic, and when I finished my PhD I almost gave up on being a researcher because of my inability to write my thoughts. Now I can pour it out and it works.
Founder and CTOProtein design and drug discovery
I quite like the methodical way it goes about doing the work. It’s definitely a much bigger step up from the generic deep research products on Gemini or ChatGPT, and there’s a lot more transparency — it’s more academic. Without it I’d spend a good week or two just accumulating the resources.
Physician and clinical educatorEducation research
It’s really good when it has a clear objective. Reports, slides, all of that — even when you put in a lot of information, it takes forever for a person to do. It’s really good at that, and at interpreting everything. I asked it to explain what was going on mechanistically, with visuals, and that was really nice.
Fermentation scientistIndustrial biotechnology
I told it what we already have, where our strategy is right now, and what we’d like to do. It designed some very detailed assays, which I handed off to our head of biology — who is very excited about following up on those designs.
R&D leadDrug discovery biotech
What I really love is that it lets you explore your curiosity faster and better. I bounced ideas off it for projects I’d been thinking about and explored three or four very different directions — asking it to critique the idea, find the benefits, tell me whether it works. That kind of thing was very cool. And it generates very beautiful figures.
Research group leaderPlasmonics and nanophotonics
It’s exceptionally good. I loved that it gave me the manuscript and a slide presentation together — if you’re going to present the topic to someone, that’s the easiest way, instead of handing them the manuscript from start to finish.
Medical studentDrug discovery side projects
I tested the agent by giving a paper to review and give back improvements and it was quite astonishing as a first time user. Looking forward to test and create even more.
Researcher

Start Your First Research Session

Pay-as-you-go, no subscription required. Or explore Plus and Team plans for refreshing monthly credits.