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Platform

The AI-native R&D operating layer.

Three pillars, one closed loop — data infrastructure, agentic decisions, and execution feedback, working as one system.

Launch Platform

How it fits together

Three pillars, one closed loop.

Each pillar mirrors a layer of the live platform — data, decisions, execution — and the loop closes when wet-lab evidence flows back into the next design round.

R&D Data Infrastructure01 / 03

Gold-standard data, ready for AI.

We curate antibody–antigen complexes, pre-calculated structural properties (affinity, binding free energy, developability liabilities) and AI-driven cryo-EM structures into a single training-grade dataset. Manufacturability and developability metadata are first-class fields, not afterthoughts.

TRAINING-GRADE DATASET COREManufacturabilityMETADATAFIRST-CLASS FIELDDevelopabilityMETADATAFIRST-CLASS FIELDAntibody–Antigen ComplexesIMMUNE · NON-IMMUNEPre-calculated PropertiesAFFINITY · K_DPre-calculated PropertiesBINDING ΔG · kcal/molDevelopability LiabilitiesPRE-CALCULATED FLAGSAI-Driven Cryo-EM StructuresCOST −70% VS CONVENTIONAL
  • Curated complexesAntibody–antigen complexes covering immune and non-immune proteins.
  • AI-driven cryo-EMStructure determination with cost reduced by > 70% vs conventional pipelines.
  • Pre-calculated propertiesAffinity, ΔG and developability flags, ready for downstream scoring.
Agentic Decision Layer02 / 03

The model proposes — you decide.

Axiom™ pairs deep-learning generative design with physics-guided optimisation — but the human stays in the loop. Every run gates at the decisions that matter: approve the budget, review each round's humanness, steer the back-mutations. Watch a live antibody-humanization loop below, or click through it yourself.

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Antibody humanization design loop
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Design-loop details appear here.
  • Human-in-the-loop gatesApprove cost, review each round, choose the back-mutations — nothing reaches the lab unseen.
  • Generative + physics scoringDeep-learning design with physics-guided optimisation across a multi-stage cascade.
  • Developability gateManufacturability and developability filters built into every round.
Execution-Feedback Loop03 / 03

Every round closes on a cryo-EM structureexperimental ground-truth, not a prediction.

Axiom's candidates run straight into Ark's automated wet-lab, then cryo-EM resolves each one to near-atomic detail. That measured structure flows back into the model — so the next generative round is grounded in real 3D evidence, not estimates.

EXECUTIONstructure-grounded feedback → AxiomCryo-EMSINGLE-PARTICLE ANALYSISraw particles2.9 Ånear-atomicAxiom designscandidates inArk™ auto-labexpress · purify · vitrify
  • Ark™ automated wet-labStandardised digital protocols and high-throughput auto-lab turn each design into testable material — the groundwork the loop runs on.
  • Cryo-EM in the loopExperimental near-atomic structures — native state, no crystallisation — feed the model as ground-truth, where others rely on predictions.
  • Self-improving cycleEvery resolved structure sharpens the next generative round, compounding gains campaign over campaign.

Talk to us about embedding abYcloud in your pipeline.

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