Unify and connect your scientific data to power explainable decision making

Connect chemical and biological data into a semantic graph—enabling traceable, AI-powered decisions across your R&D lifecycle.

Unify and connect your scientific data to power explainable decision making

Connect chemical and biological data into a semantic graph—enabling traceable, AI-powered decisions across your R&D lifecycle.

Unify and connect your scientific data to power explainable decision making

Connect chemical and biological data into a semantic graph—enabling traceable, AI-powered decisions across your R&D lifecycle.

Partners

Trusted by leading organizations in scientific research and innovation.

Partners

Trusted by leading organizations in scientific research and innovation.

Partners

Trusted by leading organizations in scientific research and innovation.

Why Semantic Chemistry?

Traditional systems store scientific data in tables and documents, then try to reconstruct relationships later.

Chemantics places scientific entities—such as compounds, biologics, materials, formulations, batches and samples—at the center of a connected scientific knowledge graph. Rather than storing scientific knowledge in disconnected records and systems, here scientific entities are registered as first-class graph objects from which relationships, context, and lineage are automatically derived.

This creates a persistent foundation of scientific knowledge that supports traceable, explainable, and AI-ready decision making.

Register compounds, biologics, formulations, and materials as first-class graph entities.

Automatically derive and preserve scientific relationships, context, and lineage as entities are registered.

Ground LLMs in scientific knowledge to improve chemistry accuracy while enabling traceable, explainable AI.

Scientific knowledge emerges from connected entities, relationships, and context.

Why Semantic Chemistry?

Traditional systems store scientific data in tables and documents, then try to reconstruct relationships later.

Chemantics places scientific entities—such as compounds, biologics, materials, formulations, batches and samples—at the center of a connected scientific knowledge graph. Rather than storing scientific knowledge in disconnected records and systems, here scientific entities are registered as first-class graph objects from which relationships, context, and lineage are automatically derived.

This creates a persistent foundation of scientific knowledge that supports traceable, explainable, and AI-ready decision making.

Register compounds, biologics, formulations, and materials as first-class graph entities.

Automatically derive and preserve scientific relationships, context, and lineage as entities are registered.

Ground LLMs in scientific knowledge to improve chemistry accuracy while enabling traceable, explainable AI.

Scientific knowledge emerges from connected entities, relationships, and context.

Why Semantic Chemistry?

Traditional systems store scientific data in tables and documents, then try to reconstruct relationships later.

Chemantics places scientific entities—such as compounds, biologics, materials, formulations, batches and samples—at the center of a connected scientific knowledge graph. Rather than storing scientific knowledge in disconnected records and systems, here scientific entities are registered as first-class graph objects from which relationships, context, and lineage are automatically derived.

This creates a persistent foundation of scientific knowledge that supports traceable, explainable, and AI-ready decision making.

Register compounds, biologics, formulations, and materials as first-class graph entities.

Automatically derive and preserve scientific relationships, context, and lineage as entities are registered.

Ground LLMs in scientific knowledge to improve chemistry accuracy while enabling traceable, explainable AI.

Scientific knowledge emerges from connected entities, relationships, and context.

Transform Scientific Data into Traceable Intelligence

Connected scientific knowledge enables a structured workflow that transforms fragmented data into traceable intelligence.

Unify

Integrate diverse data from internal systems and external sources into a single foundation for connected scientific knowledge.

Connect

Connect scientific entities, relationships, and context into a domain-aware scientific knowledge graph.

Reason

Apply scientific knowledge and AI to derive transparent, explainable insights from connected data.

Predict

Anticipate outcomes, identify risks, and evaluate alternatives before decisions are made.

Decide

Support evidence-based decisions with complete scientific context and traceability.

Semantic Research Dossier

A Semantic Data Platform for Scientific Entities

SRD is a semantic platform for scientific data integration — built around the entities that drive research, development, quality, and compliance.

It connects compounds, materials, formulations, batches, samples, experiments, and processes into a knowledge graph, preserving the relationships and lineage teams need for traceable decisions and trustworthy AI.

emantic

Connect data through meaning, relationships, and context.

Entities
Relationships
Context
esearch

Model scientific entities as first-class data objects.

Compounds
Batches
Samples
Experiments
ossier

Organize evidence into a traceable decision foundation.

Evidence
Lineage
Decisions

See how it works

Semantic Research Dossier

A Semantic Data Platform for Scientific Entities

SRD is a semantic platform for scientific data integration — built around the entities that drive research, development, quality, and compliance.

It connects compounds, materials, formulations, batches, samples, experiments, and processes into a knowledge graph, preserving the relationships and lineage teams need for traceable decisions and trustworthy AI.

emantic

Connect data through meaning, relationships, and context.

Entities
Relationships
Context
esearch

Model scientific entities as first-class data objects.

Compounds
Batches
Samples
Experiments
ossier

Organize evidence into a traceable decision foundation.

Evidence
Lineage
Decisions

See how it works

Semantic Research Dossier

A Semantic Data Platform for Scientific Entities

SRD is a semantic platform for scientific data integration — built around the entities that drive research, development, quality, and compliance.

It connects compounds, materials, formulations, batches, samples, experiments, and processes into a knowledge graph, preserving the relationships and lineage teams need for traceable decisions and trustworthy AI.

emantic

Connect data through meaning, relationships, and context.

Entities
Relationships
Context
esearch

Model scientific entities as first-class data objects.

Compounds
Batches
Samples
Experiments
ossier

Organize evidence into a traceable decision foundation.

Evidence
Lineage
Decisions

See how it works

Scientific Knowledge in Practice

Trace every relationship back to evidence, source data, and scientific context.

Register compounds, biologics, formulations, materials, and samples as graph-native entities. Automatically derive relationships, context, and lineage to create connected scientific knowledge.

Register

Register compounds, biologics, ingredients, materials, formulations, and samples as graph-native entities.

Connect

Automatically derive scientific relationships from structures, compositions, formulations, reactions, and experiments.

Trace

Trace origins, transformations, and dependencies across compounds, materials, formulations, experiments, and decisions.

Example: Register a small protein using a HELM Editor.

Where SRD Creates Value

See how connected scientific data accelerates decisions across regulated and innovation-driven industries.

Healthcare and Consumer Products

Fragmented scientific and regulatory data slows decisions across the product lifecycle.

SRD connects and contextualizes data to accelerate decisions, reduce compliance risk, and improve product quality.

Pharmaceuticals
Pharmaceuticals
Pharmaceuticals
Cosmetics
Cosmetics
Cosmetics
Nutraceuticals
Nutraceuticals
Nutraceuticals
Chemicals & Materials Innovation

Siloed structure, formulation, and process data makes performance hard to predict and optimize.

Connect experimental, simulation, and production data to accelerate development and improve product performance.

Chemicals
Chemicals
Chemicals
Advanced Materials
Advanced Materials
Advanced Materials

Explore how SRD connects scientific data across regulated, formulation-driven, and materials-focused workflows.

See how SRD works

Science is complex.

Your decisions don't have to be.


See how Chemantics helps your team turn scientific data into decisions—in days, not months.