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Cognitive Chemistry Labs

Focus on the science. Let us handle the rest.

Ready-made workflows and an Assistant that explains every step. Start at $0 and pay as you go for the compute you use.

Or schedule a demo
  • 42

    Ready-made workflows

  • 8

    Problem families

  • 100

    Tools

  • 10

    CPU & GPU types

[Virtual screening]Fig. 01
  • Screen a compound library against a targetSMILES → 3D embed → dock
  • Train a target rescorer on your measured compoundsVina + GNINA + PLIP → target rescorer
  • Screen a library with your target rescorerVina + GNINA + PLIP → rescore with your model → top 20
  • Find top binding poses with diffusion dockingSMILES → DiffDock → top poses
  • Screen an ultra-large combinatorial libraryThompson Sampling → 3D embed → dock
  • Rescore docking hits with a CNN scoring functionVina triage → GNINA rescore
  • Re-predict docking hits with Boltz-2 affinitiesVina triage → Boltz-2 re-predict (batch)
  • Re-dock top hits with surface-aware diffusionVina triage → SurfDock (scatter)
  • Validate docking protocol, then screenValidate docking protocol → screen
Workflows
9
Stages
6
Longest pipeline
7 steps
Find the compounds in a library most likely to bind your target, then rescore the best hits with a stronger method. Each line is a ready-made workflow; lines share a station where they run the same step. See the virtual screening workflows

Workflows

Start from the problem, not the plumbing.

Each workflow is a tested pipeline, named for the problem it solves. Bring your inputs: the steps, file formats, and hand-offs between tools are already connected.

Family 01 · 9 workflows

Virtual screening

Find the compounds in a library most likely to bind your target, then rescore the best hits with a stronger method.

Explore virtual screening
  • Screen a compound library against a target

    SMILES → 3D embed → dock

    3 steps
  • Train a target rescorer on your measured compounds

    Vina + GNINA + PLIP → target rescorer

    6 steps
  • Screen a library with your target rescorer

    Vina + GNINA + PLIP → rescore with your model → top 20

    7 steps
  • Find top binding poses with diffusion docking

    SMILES → DiffDock → top poses

    2 steps
  • Screen an ultra-large combinatorial library

    Thompson Sampling → 3D embed → dock

    4 steps
  • Rescore docking hits with a CNN scoring function

    Vina triage → GNINA rescore

    5 steps
  • Re-predict docking hits with Boltz-2 affinities

    Vina triage → Boltz-2 re-predict (batch)

    5 steps
  • Re-dock top hits with surface-aware diffusion

    Vina triage → SurfDock (scatter)

    6 steps
  • Validate docking protocol, then screen

    Validate docking protocol → screen

    7 steps

Mapped in Fig. 01 above.

  • Build your own

    Open any template in the visual builder and change its steps, or start from a blank canvas. The builder checks each connection as you make it.

    Open the builder
  • Or let the Assistant build it

    No template fits? Describe the problem, and the Assistant chains the steps itself, checks the connections, and prices the plan. It runs only when you approve.

    Describe your problem

A different model

Computational chemistry, without the seat license.

Commercial modeling suites are typically sold as annual per-seat licenses. CogniChem runs in your browser and bills only the compute you use.

See plans and rates
Cost to startThe old way · An annual seat license, often priced only by quoteCogniChem · $0. A plan is optional: it lowers your rates.
Getting startedThe old way · Procurement, a sales call, then an install on every workstationCogniChem · Sign up and run in your browser today
HardwareThe old way · Your own workstations or cluster, GPUs includedCogniChem · CPU to Nvidia B200, on demand, chosen per step
What you pay forThe old way · Seats, whether or not anyone runs anythingCogniChem · The compute you use, from your wallet
PipelinesThe old way · Wiring tools and file formats together yourselfCogniChem · 42 ready-made workflows, every step connected and tested
Learning the methodsThe old way · Training courses and manualsCogniChem · An Assistant that explains each step and cites the method papers

What it costs

A run costs cents to dollars, not a contract.

What a typical run reserves on the free Basic plan: the catalog's expected runtime × the per-second rate. You're charged only for the seconds it actually runs, and higher plans pay less.

All compute rates

Bigger jobs: an Nvidia H100 is $13.82 an hour on Basic and $7.88 on Pro, billed by the second.

CogniChem Assistant

Ask it why.

Tell the Assistant what you want to find out. It picks a ready-made workflow or builds one for the job, explains why each step is there, points you to the papers behind each method, and prices the plan. It shows the structures it talks about: molecules drawn with their properties, binding sites in 3D, your files as a compound grid. Nothing runs until you click Approve.

  • Answers with sources

    Ask why a step is there and the answer comes from the papers behind the method. Every compound or target it looks up links to the source record.

  • It proposes; you approve

    The Assistant can plan, estimate, and propose, but it cannot start, cancel, or delete anything. Your Approve click starts the run, re-priced at that moment.

  • Shows the chemistry

    Molecules come back drawn, with their computed properties. PDB and AlphaFold structures open in 3D, set up the way you asked; reactions and retrosynthesis routes are drawn step by step.

  • Draw it or attach it

    Sketch a molecule, or attach structure files, a CSV that opens as a compound grid you can hand to SAR tools, or an image to read structures from. Live lookups in PubChem, ChEMBL, Open Targets, UniProt, the PDB, and Europe PMC.

  • Follows the run

    After you approve, it tracks the run in the same conversation, summarizes the results with their top rows, opens result structures in 3D, and exports the thread as a notebook.

  • A spend cap on every conversation

    $1.00 of Assistant tokens by default. Only you can raise it, $1.00 at a time.

[assistant exchanges]Fig. 02
Why does this workflow dock everything with Vina, and only then run Boltz-2?

Vina is fast and runs on CPUs (about $0.025 a typical run), so it can screen the whole library. Boltz-2 predicts the full protein–ligand complex and a binding affinity, which tells you more but needs a GPU (about $1.93 a run on an Nvidia A10). So the workflow spends Boltz-2 only on the compounds Vina ranks highest.

Proposed workflow · waiting for you

Re-predict docking hits with Boltz-2 affinities

Vina triage → Boltz-2 re-predict (batch)

Steps
5
Runs on
CPU · A10 GPU
Estimate
Priced for your plan
Illustrations of exchanges. Structures come from PubChem and PDB 2HYY, drawn and described by RDKit; prices and papers are the catalog's. In the app, the plan card shows the estimate the API computed for your plan, and approving re-checks it.

How it works

Three steps from question to results.

  1. Pick a workflow, or describe the problem

    Browse workflows by the problem they solve, build your own in the visual builder, or tell the Assistant what you need and let it pick or build one.
  2. Add your inputs and check the estimate

    Upload a structure and a compound list, or reuse files from earlier runs. The estimate for your plan appears before you launch, and the run pauses at its cost cap instead of overspending.
  3. Run it and collect the results

    Follow each step as it runs. Results are saved as files you can download or feed into your next workflow.

Why CogniChem

You pay for results, not for wiring.

The hard part of computational chemistry is rarely one model. It is getting formats, conversions, and hand-offs right between five of them. That part is done before you arrive.

Working pipelines, not parts

Workflows ship with every step connected and tested, so the first run is a result, not a debugging session.

No infrastructure to run

Jobs run on on-demand CPUs and GPUs, billed by the second at your plan's rate. Nothing to install or keep running.

Priced up front

Every job and workflow is estimated before it starts, and workflow runs pause at their cost cap.

Built for individuals and teams

Individual researchers, academic groups, and small to mid-sized companies get these tools without enterprise pricing. Plans start free.

Pricing

Start free. Pay as you go for compute.

Plans set your rates, monthly credit, and limits. Compute is billed per second from your wallet, at lower rates on higher plans.

Compare plans
  • Basic

    Starting at $0

    Get started with basic features.

    H100 GPU · $13.82 / hour

  • Starter

    $100 / month per seat

    For small teams needing more power.

    H100 GPU · $9.86 / hour

  • Pro

    $500 / month per seat

    Advanced features for research groups and startups.

    H100 GPU · $7.88 / hour

  • Enterprise

    Contact us for pricing

    Custom solutions for large organizations and commercial use.

    H100 GPU · $5.94 / hour

For experts

100 tools when you want one method.

Every model behind the workflows runs on its own too, along with quantum chemistry, thermodynamics, and custom models: train message-passing networks, compare classical QSAR models, or predict reaction yields from your own data.

35 tools · Modeling and analysis tools for biomolecular research

  • Boltz-2

    Accurate in silico screening for early-stage drug discovery

  • BoltzGen

    Design proteins and peptides to bind biomolecular targets

  • DiffDock

    Protein-ligand docking with diffusion models and confidence-ranked poses

  • DrugFlow

    Generate candidate ligands from a protein target and reference ligand using flow matching

  • Sequence Mutator

    Apply point mutations such as T315I to a protein sequence, checking each wild-type residue

  • Antibody Numbering & Humanization

    Number antibody, nanobody and TCR variable domains (IMGT, Kabat, Chothia), mark CDRs and assign the nearest human germline

  • Binding ΔΔG

    Rank antibody variants by predicted change in binding free energy on an antibody-antigen complex

  • Stability ΔΔG Predictor

    Rank point variants of a protein by predicted change in folding stability, or scan residues to alanine

  • MPNN Sequence Design

    Design amino-acid sequences for a fixed protein backbone with ProteinMPNN, LigandMPNN or SolubleMPNN

  • RFdiffusion3

    Generate all-atom protein backbones under motif, ligand, binder and symmetry constraints

  • RFdiffusion3NA

    Design protein, RNA and DNA backbones, and protein-nucleic-acid complexes, under motif, ligand and symmetry constraints

  • RoseTTAFold3

    Predict the structure of protein, DNA, RNA and ligand complexes with all-atom RoseTTAFold3 and an independent confidence score

  • RFOptimization

    Improve a protein binder design by cycling RoseTTAFold3 or Boltz-2 prediction with LigandMPNN redesign

  • ESMFold2

    Predict protein, DNA, RNA, and ligand complex structures with evolutionary scale modeling

  • Evo 2

    Genome modeling and design across all domains of life with the Evo 2 DNA language model

  • AutoDock Vina

    High performance molecular docking and virtual screening for drug discovery

  • Binding-Site Detector

    Find ligandable pockets and emit Vina-shaped docking boxes for fold-to-dock workflows

  • Lacuna

    Find cryptic pockets that open across a normal-mode conformational ensemble and rank their druggability

  • Docking Protocol Validator

    Redock co-crystallized ligands and score pose RMSD and enrichment to validate a docking setup before screening

  • Protein Preparer

    PDBFixer cleanup, PDB2PQR protonation, and dock-ready structures without MD solvation

  • Protein / Antibody Developability Screen

    Screen protein and antibody chains for pI, charge, GRAVY, instability, and sequence liability motifs

  • OpenDDE

    Predict protein, nucleic acid, and small-molecule complex structures with OpenDDE

  • OpenMM MD

    Prepare, solvate, and equilibrate proteins, small molecules, or membrane systems with OpenMM molecular dynamics

  • MD Trajectory Analyzer

    Compute RMSD, Rg, RMSF, ligand H-bond occupancy, and representative frames from OpenMM trajectories

  • RFAntibody

    Antibody and TCR design with RFdiffusion, ProteinMPNN, and RF2 (stages or full pipeline)

  • FreeBindCraft

    Design miniprotein and peptide binders against a target structure using open-source scoring

  • GNINA

    Protein–ligand docking and pose rescoring with convolutional neural network scoring functions

  • Interaction Profiler

    Enumerate hydrogen bonds, hydrophobics, salt bridges, and π-stacking in docked complexes

  • Protein Structure Ensemble Comparator

    Compare predicted or designed protein structures by TM-score and RMSD, cluster them, and pick one representative per fold

  • Structure QC Report

    Grade protein model geometry: Ramachandran and rotamer outliers, atomic clashes, cis-peptides, C-beta deviation and ligand bond geometry

  • MM-GBSA Rescoring

    End-point implicit-solvent MM-GBSA rescoring of docked poses or protein–ligand complexes

  • Relative Binding Free Energy

    Alchemical relative binding ΔΔG across ligand perturbation networks, absolute hydration ΔG, and REST2 replica-exchange sampling of protein–ligand complexes

  • SurfDock

    Surface-informed diffusion docking with a reference-ligand pocket and screen-model rescoring

  • SURFMAP

    2D projections of protein surface features from PDB structures or SURFMAP matrix files

  • Thompson Sampling

    Active-learning virtual screening of un-enumerated combinatorial libraries via Thompson Sampling

Browse all 100 tools

Developers

Run it from your own code.

Jobs, workflows, and their results are all on the REST API, so a run can start from a notebook, a pipeline, or an AI client.

  • Scoped API keys

    Each key has read or write scope, an optional expiry, and an optional spend ceiling.

  • Safe retries

    Retrying a submit or a new run with the same Idempotency-Key returns the original instead of starting a second one.

  • The same workflows

    List templates, validate and estimate a spec, start runs, and download results over REST or with the Python SDK.

  • MCP for AI clients

    Connect Claude Code, Cursor, or any MCP client to the hosted CogniChem MCP server with your key. You pay your own model costs; we bill only compute.

API reference
# pip install cognichem-client
from cognichem_client import CogniChem

client = CogniChem.from_env()  # reads COGNICHEM_API_KEY

for template in client.workflows.templates():
    print(f"{template.id}: {template.summary}")

# One template's full spec: validate it, estimate it, then start a run
# with client.workflows.runs.create(...).
spec = client.workflows.template("smiles-embed-dock").spec

Security

Careful with your account and your money.

Security and data handling

Encrypted in transit

All traffic is HTTPS, with HSTS, a Content-Security-Policy, and related headers site-wide.

Scoped access

Sign-in through Supabase Auth; API keys carry their own scope, expiry, and spend ceiling.

Payments through Stripe

Card data stays with Stripe. Our servers receive only tokens and verified webhook events.

Enterprise terms

Data processing agreements, security questionnaires, and custom deployments on the Enterprise plan.

Start with a workflow, or just describe the problem.

The Basic plan is free: you pay only for what you run.