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Faraday · The intelligence of your lab

Your best scientist never leaves the building.

Faraday is an AI co-scientist built into a benchtop instrument, and the brain your lab has been missing. It analyzes your data, reads the full-text literature, checks its own statistics and writes up the methods, on hardware that sits in your lab.

Request a demoSee how the gate works

From $30,000, owned outright, with an annual support and software subscription.

FP4 on NVIDIA Grace Blackwell
1 PFLOPFP4 on NVIDIA Grace Blackwell
Unified memory
128 GBUnified memory
Token context, on the box
256kToken context, on the box
Runs with no network at all
SealedRuns with no network at all

Named for the cage

Michael Faraday’s enclosure let nothing through. Neither does this one, unless you say so.

140+

Scientific skills

installed on the box

326

Workflows

across 22 fields

110

Scientific databases

UniProt to Materials Project

21

Specialist agents

reviewing its work

The intelligence of your lab

One co-scientist, wired into the whole lab

Faraday sits at the center of your science: reading what your instruments produce, knowing where your data lives, and working alongside every scientist on the team.

  • Instruments

    Mass-spec runs and instrument exports open natively, and the camera reads a display it cannot plug into.

  • Lab automation

    Opentrons and PyLabRobot skills draft and check the protocol for your next run.

  • Records and ELNs

    Skills for Benchling, LabArchives and protocols.io, plus exports from any ELN or LIMS.

Faraday

On your bench, on your network

  • Your data

    Read-only connectors to Amazon S3, Google Cloud Storage and drives on the bench, every import audited.

  • The literature

    Full-text papers, regulatory documents, clinical trials and 110 scientific databases.

  • Your tools

    MCP servers connect GitHub, reference managers and hundreds of other tools.

Where Faraday is going

The brain of the lab, at the bench and at the desk

  • Live links to the instruments, ELNs and LIMS in your building
  • The same co-scientist at every scientist's desk, not only at the bench
  • One memory of every run your lab has ever done

Want it at your desk today? Faraday runs a privacy-hardened build of K-Dense BYOK, our open-source AI co-scientist, which installs on your own computer in minutes.

How it works

From a question to a methods section

Ask the way you would ask a colleague. Faraday runs the analysis in real code, has it checked, and writes down exactly what it did.

  1. 01

    Ask in plain language

    Type, tap or dictate. Speech is transcribed on the box in 25 languages, and the articulating camera puts a notebook page, a reagent label or an instrument readout straight into the conversation.

  2. 02

    It works in real code, on your files

    Python with pandas, SciPy, statsmodels and the rest of the scientific stack, run against your data. It is built to ask before it assumes, and never to substitute placeholder data or overwrite a source file. Redirect it mid-run without starting over.

  3. 03

    It checks itself before you see it

    Specialist agents audit the statistics, the methodology and the references. A citation that cannot be verified is marked unverifiable, never waved through.

  4. 04

    It writes it up as it goes

    Every prompt becomes a dated lab notebook entry: the data touched, the code run, the figures made and the sources read, in methods-style prose composed on the box. Export it to Jupyter or Markdown.

You ask

“Run differential expression on counts.csv, treated versus control, and plot a volcano. Flag anything that disagrees with the 2019 result.”

Entry 014

20 Aug 2026 · 14:22

Recorded · 4m 12s

  1. Loaded counts.csv18,412 rows
  2. Ran differential expressionDESeq2
  3. Wrote volcano.pngfigures/
  4. Delegated statistical-reviewerpassed
  5. Consulted frontier expertyou approved
  6. 9 routine steps folded
figures/volcano.png
a3f1c97b20dee41a08Chain intact

Fig. 1The notebook entry that comes back, written while the run happens. Illustrative, synthetic data.

What it does

The four jobs that fill a research week

Each one ends in something you can hand to a colleague or put in a report, not a chat transcript.

Data analysis

A notebook that reruns

Differential expression, survival models, dose-response fits, single-cell pipelines. Every number in the write-up traces back to the code that produced it.

Hypothesis generation

Ranked, with evidence

Testable, falsifiable hypotheses grounded in your data and the literature, each argued with the evidence for and against it.

Deep research

A report with citations

A specific question answered in depth, with a citation checker confirming each reference exists and says what the report claims it says.

Literature review

Full text, not abstracts

Full-text search across bioRxiv, medRxiv, arXiv and PubMed Central, plus regulatory documents and clinical trials, synthesized with proper citations.

Built-in review

A review panel on every run

Faraday delegates to 21 specialist agents: one at a time, in parallel, or in a chain where one's findings feed the next. Edit any of them, or add your own.

Code and computation

  • statistical-reviewer

    Test choice, assumptions, power, multiplicity

  • code-reviewer

    Correctness bugs and numerical pitfalls

  • data-validator

    Schema, missingness, outliers, duplicates

  • reproducibility-auditor

    Seeds, versions and a clean rerun

  • ml-auditor

    Leakage, splits, baselines, evaluation

  • math-checker

    Derivations, units, dimensional consistency

  • simulation-reviewer

    Discretization, convergence, stability

  • pipeline-engineer

    Pipelines that run end to end

  • data-visualizer

    Publication-quality figures

Literature

  • literature-researcher

    Surveys and synthesizes prior work

  • citation-checker

    Each reference exists and supports its claim

  • fact-checker

    Claims against authoritative sources

  • methodology-reviewer

    Threats to validity in the design

  • peer-reviewer

    A full, adversarial journal-style review

Writing

  • manuscript-editor

    Clarity, structure, precision

  • abstract-writer

    Abstracts, summaries, lay versions

  • ethics-reviewer

    Research ethics, privacy, dual use

Study design

  • hypothesis-generator

    Testable, falsifiable hypotheses

  • experiment-designer

    Controls, randomization, sample size

  • protocol-writer

    Step-by-step protocols and SOPs

  • results-interpreter

    Cautious reading, alternative explanations

Honest by instruction

The citation checker must call a reference it cannot confirm unverifiable, never fine. The results interpreter has to offer the alternative explanations before the conclusion.

Scientific depth

Fluent in your field on day one

140+ scientific skills and 326 ready-made workflows arrive installed, with 110 scientific databases a query away, so the box knows your tools before it ever sees your data.

140+

Scientific skills

The libraries your field already uses, with the know-how to use them well. They load on their own, or type / to call one by name.

  • scanpy
  • pydeseq2
  • scvi-tools
  • RDKit
  • DeepChem
  • PyTDC
  • ESM
  • pyOpenMS
  • matchms
  • pymatgen
  • Qiskit
  • Astropy
  • PyMC
  • statsmodels
  • PathML
  • pydicom
  • NeuroKit2
  • Opentrons

Plus NVIDIA BioNeMo

  • Boltz-2
  • OpenFold3
  • RFdiffusion
  • ProteinMPNN
  • DiffDock
  • Evo 2
  • GenMol
  • MolMIM

326

Workflows

Ready-made protocols for the analyses labs run most. Pick one, fill in the blanks, go. Save your own for the team.

  • Single-Cell RNA-seq Pipeline
  • Perturbation / CRISPR Screen Analysis
  • Retrosynthesis Planning
  • ADMET Prediction
  • Molecular Docking
  • Neuropixels Data Processing
  • Digital Pathology Analysis
  • Battery Material Analysis
  • Gravitational Wave Analysis
  • Species Distribution Model
  • Reproduce an Analysis
  • Write a Specific Aim

110

Scientific databases

Sequence, structure, chemistry, clinical, materials and earth data, queried directly, with the query itself screened by the gate.

  • UniProt
  • RCSB PDB
  • ChEMBL
  • PubChem
  • Ensembl
  • NCBI Entrez
  • gnomAD
  • GTEx
  • KEGG
  • Reactome
  • STRING
  • ClinicalTrials.gov
  • openFDA
  • Materials Project
  • NIST WebBook
  • Europe PMC
  • OpenAlex
  • GBIF
  • PhysioNet
  • Copernicus CDS

Workflows across 22 fields, including

  • Genomics and transcriptomics
  • Cell biology and single-cell
  • Proteomics and structural biology
  • Chemistry
  • Drug discovery and pharmacology
  • Clinical and health sciences
  • Neuroscience
  • Materials science
  • Physics and quantum computing
  • Astronomy and space science
  • Ecology and environmental science
  • Mathematics and modeling
  • Engineering and simulation
  • Machine learning
  • Social sciences
  • Economics and finance

BioNeMo skills call NVIDIA-hosted models and are enabled with your own NGC key.

Native viewers

See your science, not just its files

Structures, spectra and alignments open natively on the workspace screen. Every viewer renders on the box, which is why they still work sealed.

Structure

complex_ab.cif

4,812 atoms · cartoon

Mass spec

sample_04.mzML

487.2 m/zstreamed · 2.4 GB

Alignment

orthologs.a3m

shaded by conservation

Fig. 2Three of the on-box viewers: a protein structure, a mass-spectrometry run and a multiple-sequence alignment. Illustrative renderings.

Molecular structures

PDB · mmCIF · SDF · MOL2 · XYZ · GRO · PDBQT

Chemistry

SMILES · 2D depiction

Sequences and alignments

FASTA · FASTQ · Clustal · Stockholm · A3M

Genomics

VCF · BED · GFF · GTF · SAM · AnnData .h5ad

Mass spectrometry

mzML · mzXML · MGF · imzML imaging

Documents

PDF with OCR · Word · PowerPoint · Excel · LaTeX · Jupyter

Sovereignty

Nothing leaves except through a gate you can read

Faraday does its work on the box. When it wants a frontier model's opinion, the request is sanitized, shown to you, and sent only when you approve it.

Outbound payload

Awaiting your approval

Does the vc-PAB linker on [COMPOUND_1] explain the loss of serum stability we measured at DAR 4? [PERSON_1] ran the plates, copy her at [EMAIL_1].

Sanitizer fails closed. If a layer errors, the payload is blocked.

3 spans masked

  • KD-7781[COMPOUND_1]Site terms
  • Sofia Marchetti[PERSON_1]On-box review
  • s.marchetti@northfield-bio.com[EMAIL_1]Pattern

Fig. 3An outbound request, masked by all three layers and waiting for approval.

Three layers, in order

  1. 01

    Patterns

    Emails, keys, record numbers, lot codes, InChI and SMILES strings, sequence runs.

  2. 02

    Your vocabulary

    Compound codes, targets, cell lines and project names. Your list always wins.

  3. 03

    On-box clean-room review

    The local model reads only the outbound text, never the conversation, and can veto it.

It fails closed: if any layer errors, nothing is sent. Approve the masked text unchanged and exactly that text leaves, byte for byte, as a single message with no system prompt and no chat history. Edit it and the sanitizer runs again, so a block can never be approved through.

Three ways out, all of them gated

Expert questions

Sanitized text to a frontier model, sent only after you approve the exact payload.

Web searches

Clean queries run. A query that carries anything proprietary waits for you to edit it.

Images

Pixels cannot be masked, so every image needs your explicit approval. Every time.

A dial, not a switch

Set how much can leave, per session, from freely connected to fully sealed. Every change is on the record.

Faraday’s data perimeterThe agent, the local models, your data and the audit log all sit inside your facility. Data can be imported read-only. The only outbound path runs through the sovereignty gate to a frontier expert model, carrying sanitized text you approved.YOUR FACILITYFaradayagent + local modelsYour dataread-only inAudit loghash-chainedLab notebookwritten on-boxScientific viewersrender locallyGatesanitizedyou approved itFrontierexpert
Everything that does the work stays inside. One outbound path, gated and logged.

Egress

Seal the box: local models only, no web, nothing out.

Sanitize

Every outbound request masked before it goes.

Preview

You approve each expert request. Flagged searches wait for you.

Tightening is always allowed. Loosening the gate takes an administrator, and the role comes from the operating system on the box rather than the screen. Sealed, Faraday makes no outside connections of its own and still runs voice, document parsing, every viewer and the notebook.

Provenance

Every result arrives with its paper trail

Faraday treats an answer the way you treat a measurement: traceable to its inputs, its method and the instrument that produced it.

01

A lab notebook that writes itself

One dated, numbered entry per prompt, with the data, code, figures, citations and gate crossings captured as they happen. Add margin notes and flags, then export to Jupyter with one code cell per step.

02

A hash-chained audit log

Everything that crosses the boundary, out and back in, is written to an append-only SHA-256 chain before it is sent. An independent verifier, sharing no code with the product, re-checks every hash.

03

Per-person accountability

Each record carries the operator's own account on the box, so the trail is per scientist without a separate identity system to administer.

04

Runs that end honestly

Every reply closes as Complete, Stopped or Failed, with its duration and step count, so a quiet minute never passes for a finished analysis.

The instrument

Operated, not installed

Results and the record on the large screen, the conversation on the small one. No desktop and no terminal for lab users, just the instrument.

Fig. 4The instrument, from the front right.

  1. 1

    15.6" workspace touchscreen

    Files, data previews, the scientific viewers and the live lab notebook.

  2. 2

    11.6" chat touchscreen

    The conversation, the composer and every approval the gate asks for.

  3. 3

    Twin side fans

    Cooling for long, sustained analyses on the Grace Blackwell chip.

  4. 4

    Optional keyboard

    With a built-in touchpad, for editing code and notebooks.

Touch first

Every control sized for a fingertip, and a text-size control from 80 to 140 percent for reading at arm's length.

Voice, on the box

Dictation is transcribed locally by NVIDIA Parakeet in 25 languages. The audio never leaves.

A camera for the bench

Digitize a notebook page, identify a reagent, read an instrument display or document a setup in one capture.

Always warm

The model stays loaded across logouts, reboots and updates, so the instrument is ready when you walk up to it.

Datasheet

Specifications

Compute
NVIDIA GB10 Grace Blackwell superchip
AI performance
Up to 1 PFLOP FP4
Memory
128 GB unified LPDDR5x
Co-scientist model
Gemma 4
Model options
NVIDIA Nemotron, other local models
On-box context
256k tokens
Also on the box
Speech-to-text, OCR, document parsing
Frontier expert
Optional, only through the gate
Displays
15.6" workspace and 11.6" chat touchscreens
Capture
Articulating camera, microphone
Input
Touch and voice, optional keyboard
Storage
USB or Thunderbolt, typically 2 to 8 TB
Connectors
Amazon S3, Google Cloud Storage, local drives
Accounts
Per-user, Admin and User roles
Software
Privacy-hardened build of K-Dense BYOK
Interface
Locked kiosk across both screens
Siting
Benchtop, standard wall power

Powered by Gemma 4, running entirely on the box. If your group has standardized on a different model, Faraday also runs NVIDIA Nemotron and other local models.

Delivery

Results in week one

We do the siting, the integration and the training. You get a result before the invoice is due.

Week 0

We site it

Standard bench, standard wall power. No rack, no room works.

Day 1

Your data, read-only

Imported through the connectors, and your own vocabulary loaded into the gate.

Day 2

First analysis

Your team asks in plain language. The notebook starts writing itself.

Week 1

Measured, not asserted

Your pre-registered baseline against what actually happened on the bench.

Next-business-day response, same day if the box is down, a weekly check-in and a dedicated channel to your team. Updates install from Settings with a single button, and both screens come back exactly where they were.

Compared

The four ways this problem gets solved

Faraday does not win every row. It wins the two that usually decide it.

How Faraday compares with hiring for the role, waiting in an internal data-science queue, and deploying AI into your own cloud tenant
DimensionFaradayHire for itInternal queueAI in your cloud tenant
Time to first resultSame dayMonths to recruitWeeks in the backlogDays to provision
Breadth of domains22 fields, 140+ skillsOne person's expertiseWhatever the team knowsBroad
Where your data sitsYour buildingYour buildingYour buildingA hyperscaler region
What leaves during a runOnly what you approvedNothingNothingYour data
Several questions at onceParallel chats, in the backgroundOne at a timeThe queue growsElastic
Cost shapeCapital, once, plus supportRecurring salaryOpportunity costRecurring, and per run

For your security review

What we claim, and what we do not

Trust in the gate is the product, so we would rather your reviewers hear the boundaries from us.

True today

  • The gate masks, previews and logs every expert request, and fails closed if any layer errors.
  • The co-scientist, the gate's review and speech-to-text all run on the box. Analysis continues with no network.
  • Connectors are human-driven, cloud storage is read-only, and none of them is exposed to the agent as a tool.
  • Roles come from the operating system identity on the box and are enforced server-side, never claimed by the client.
  • An independent verifier, sharing no code with the product, re-checks every hash in the audit chain.

Stated plainly

  • The gate governs what Faraday itself sends. For a fully sealed site, pair it with your network controls, and we will map exactly where that line sits with your team.
  • The audit chain is tamper-evident, not tamper-proof.
  • Zero data retention at the frontier model is contractual, and we document the terms for your review.
  • Architected toward HIPAA, SOC 2 and GxP. Not yet certified against them.

FAQ

Questions scientists ask us

Does our data ever leave the building?

Not unless you let it. Faraday does its analysis on the box. Its own requests reach an outside model only through the sovereignty gate, which masks sensitive text, shows you exactly what would leave and logs every exchange. Seal the box and Faraday makes no outside connections of its own at all.

Which AI model runs on the box?

Gemma 4 runs locally on the NVIDIA Grace Blackwell chip, and an administrator can switch to NVIDIA Nemotron or another local model. When a question needs a frontier model, Faraday can consult one through the gate, sending only sanitized text you approved.

Can it run fully offline?

Yes. Sealed, Faraday uses local models only, with web access and outside tools removed. Voice dictation, document parsing with OCR, every scientific viewer and the lab notebook keep working, and data comes in on direct-attached drives. Web and full-text literature search need a network, so they pause while the box is sealed.

Is our data used to train anyone's model?

No. Your data stays on hardware you own. The sanitized requests that do go to a frontier expert are sent with logging and training switched off, under zero-data-retention terms we document for your security review.

How do we reproduce an analysis?

Every run leaves its scripts, outputs and a dated notebook entry in the project. Export the notebook to Jupyter and each step becomes its own code cell, ready to rerun.

What file formats does it understand?

Tables, PDFs and Office documents (with OCR for scans), molecular structures such as PDB, mmCIF, SDF and MOL2, SMILES, sequences and alignments in FASTA, FASTQ, Clustal and Stockholm, genomic tracks such as VCF, BED and GFF, AnnData, mass-spectrometry runs in mzML, mzXML, MGF and imzML, LaTeX and Jupyter notebooks.

How many people can use one unit?

Faraday is built for a small team. Each person gets their own account and their own audit trail, with Admin and User roles. One person drives the instrument at a time, and can run several chats in parallel.

Is it validated for GxP, HIPAA or SOC 2?

Faraday is architected toward HIPAA, SOC 2 and GxP, including 21 CFR Part 11, with hash-chained audit records, role-based access and controlled updates. It is not yet certified against them, and we will walk your quality and security teams through exactly where it stands.

Can we try it before we buy?

Yes. Faraday runs a custom build of K-Dense BYOK, our free, open-source AI co-scientist. Install BYOK on your own computer to try the same research agent, skills and workflows today. Faraday's build puts privacy and data security first, adding on-box models, the sovereignty gate, the hash-chained record and the locked instrument around it.

What does it cost?

From $30,000 for the instrument, which you own outright, plus an annual subscription covering support, software and skills updates, training and frontier-model access. Frontier consultations are billed by usage.

Same research stack

Three ways to run it

Faraday runs a privacy-hardened build of K-Dense BYOK, our open-source AI co-scientist. The question is where your work needs to run.

The instrument

Faraday

When the science cannot leave. BYOK rebuilt with privacy and data security first: on-box models, the sovereignty gate, a hash-chained record, on hardware you own.

Request a demo

Managed platform

K‑Dense Web

When you want nothing to site: team collaboration, elastic compute and the newest frontier models, managed for you.

Explore K‑Dense Web

Free and open source

K‑Dense BYOK

Try the software Faraday is built on, today. It runs on your own computer with your own API keys, under an MIT license.

Try BYOK on GitHub

Put an AI co-scientist on your bench

Tell us what your group is working on, and we will show you the instrument running on work like yours.

Request a demo

From $30,000, with an annual support and software subscription

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