AI agents for chemistry R&D

Investigate chemical systems with auditable AI agents.

Investigate reactions, impurities, degradation pathways, spectra, properties, and literature evidence in one governed workflow — with traceable answers instead of black-box guesses.

Discuss a use case See example workflow →

Now onboarding pilot teams in pharma, agrochemicals, and polymers.

Language model

Governed calls

chemistry.tools runtime

Reaction prediction Impurity analysis Quantum chemistry Spectra Properties Literature Databases Audit trail

Example workflow

From a chemistry question to a defensible report.

The agent does not just chat. It plans a scientific investigation, calls approved tools, and gives chemists something they can review.

Question

“What degradation products should we expect for this API under acidic storage conditions?”

Agent does

Searches known degradation and impurity literature
Proposes plausible transformation pathways
Runs computational checks and spectra predictions where useful
Ranks candidates by plausibility, risk, and evidence strength
Produces a reviewable report with citations and calculation traces

Output

Ranked impurity candidates, predicted spectra, risk rationale, evidence table, and recommended experiments.

The problem

Chemistry decisions are high-stakes. The tools are fragmented.

Impurity investigations, degradation studies, property checks, spectra interpretation, and literature review often happen across disconnected tools, scripts, databases, notebooks, and expert memory. chemistry.tools brings those steps into one governed workflow so teams can move faster without losing scientific traceability.

Use cases

Focused chemistry. Reviewable outcomes.

Start with one workflow where missing a plausible pathway, impurity, or property risk would be expensive.

Pharmaceuticals

Generate impurity hypotheses, degradation pathways, spectra predictions, and literature-backed risk reports for APIs and intermediates.

Agrochemicals

Screen degradation products, persistence risks, and toxic byproducts before costly field studies.

Polymers

Investigate degradation mechanisms, additive interactions, stability, and end-of-life chemistry under realistic conditions.

Platform

Computational chemistry, data, and literature in one governed interface.

The agent can select and run appropriate tools, then return traceable results with citations, settings, and intermediate steps.

Quantum chemistry

Geometry optimization, transition-state search, thermochemistry, and pathway energetics with reproducible settings.

Property prediction

Estimate logP, pKa, solubility, melting point, stability, and related molecular properties using appropriate computational methods.

Spectra prediction

Predict NMR, IR, and mass spectra to support impurity identification and experimental confirmation.

Literature & databases

Search scientific literature, public databases, and customer-provided references with source-backed answers.

Workflow orchestration

Let the agent plan multi-step investigations, select tools, track intermediate results, and produce reviewable outputs.

Audit trail

Every answer can be traced back to prompts, tool calls, calculations, datasets, and citations.

Trust & governance

Built for proprietary chemistry, not public demos.

Chemistry teams need more than impressive answers. They need controlled access, reviewable evidence, and clear boundaries around proprietary molecules and data.

Data isolation

Customer molecules, documents, and proprietary datasets stay scoped to the deployment.

Controlled tool access

Define which models, databases, and computational tools agents are allowed to call.

Human review

Designed for chemist-in-the-loop validation, not unsupervised black-box decisions.

Auditable outputs

Preserve calculation settings, intermediate steps, citations, and generated reports for review.

Pilot

A pilot in 4–6 weeks.

Bring one hard chemistry workflow. We define success criteria, run real investigations, and validate the output with your chemists.

01 Select one workflow

Choose a high-value investigation: impurity, degradation, spectra, route risk, or property screening.

02 Connect the context

Bring molecules, internal references, data sources, policies, and validation examples.

03 Run investigations

The agent plans the work, calls approved tools, and produces traceable reports.

04 Validate with chemists

Compare outputs against known cases, expert expectations, and pilot success criteria.

Team

Chemistry depth. Software speed.

Built by chemists and engineers working at the intersection of molecular modeling, agent systems, and production infrastructure.

**Jan Meissner** Computational chemistry, DFT workflows, reaction mechanisms

**Philipp Kuboth** Software engineering, infrastructure, agent systems

Pilot partners

Bring us one hard chemistry problem. We’ll show what the agent can do.

Send a chemistry problem

Now onboarding pilot teams in pharma, agrochemicals, and polymers.