THE OPERATING SYSTEM FOR PLANT PROTEINS

Formulate
with certainty.

ProtAIn combines protein biochemistry with predictive modelling to optimise processing parameters, improve functionality, and compress R&D from months to weeks.

The Problem

Plant proteins behave unpredictably under processing — and trial-and-error R&D can't keep up.

01

The Translation Gap

Published protein data doesn’t predict behaviour under your processing conditions — shear, pH, thermal history all change the outcome.

REPLICATION_GAP: 73%
02

Batch-to-Batch Variability

Different protein sources, suppliers, and extraction methods create unpredictable functionality — gelation, texture, and solubility shift between batches.

VARIABILITY_COST: 18.4%
03

Knowledge Loss

Processing insights from past formulations are locked in spreadsheets, bench notes, and the heads of senior scientists who leave.

DATA_LEAK: 60TB+
04

Trial-and-Error Trap

Millions of processing parameter permutations can’t be tested physically. Without predictive models, R&D teams are trapped in costly experimental loops.

TRIAL_WASTE: $1.2M/yr

Not charts. Scientific instruments.

ProtAIn generates interactive analysis widgets — extraction simulators, root cause tracers, material profilers — directly inside your conversation. The move from trial-and-error to predictive protein optimisation, grounded in your data and the published literature.

Generative UIExtraction SimulationRoot Cause AnalysisMaterial ProfilingParameter Optimisation

Extraction Simulator

pH Range7.2
Temp (Celsius)45°

Predicting 84.2% yield with low denaturation risk.

400nm500nm600nm700nm

Why the batch failed. What the protein is made of.

Root cause + composition.

When something goes wrong in a batch, ProtAIn doesn't just flag the failure — it traces the causal chain back to the source variable. Pair that with real-time compositional profiling to understand why your protein behaves the way it does.

Root Cause Tracer

Trace batch failures back to source variables.

Raw Material
Extraction
Thermal
LIKELY CULPRIT
?Gelation

AI Diagnosis: Temperature exceeded threshold by 22°C

Raw Insight

Real-time material profiling.

Globulins65%
Albumins20%
Glutelins10%
Prolamins5%
GelationSTRONG
FoamingMODERATE
SolubilityHIGH
EmulsificationSTRONG

From structure to process to function. One platform.

Three layers, one workflow.

Connectivity

The Knowledge Base

Stop searching and start discovering, with provenance.

  • Query the knowledge base using natural language.
  • Team-isolated workspace — your data, your confidentiality.
  • Every insight anchored to its source, whether a trial or a study.
Reasoning

The Co-Scientist

Your research partner in causal discovery.

  • Traces causality to understand the why.
  • Parameter-level recommendations for processing variables.
  • A library of specialized skills for recurring workflows.
Execution

The Virtual Lab

High-fidelity workbench where your team actually works.

  • Interactive simulations for processing variables — pH, temperature, dwell time and more.
  • Skill modules for batch analysis, EDA, structural modeling and growing.
  • Prediction models to test solubility and gelation before physical trials.
  • Save only the most relevant exchanges and simulations.
Four steps. Real answers.

The platform behind every insight.

1
Knowledgebase/New hypothesis

Start from what's known — or propose a new hypothesis

Query the pre-loaded plant-protein knowledgebase, or sketch a new hypothesis to explore.

2

Upload your data

Drop in batch records, trial results, or proprietary documents. ProtAIn structures them into your private graph.

3

Analyse

Query the combined graph for cross-batch correlations, parameter recommendations, and failure-mode tracing.

4

Recommended next steps

Get specific processing parameters and follow-up experiments — with reasoning and citations.

Reimagine R&D

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