Simreka AI-Powered Formulation Generator
Formulate smarter. Launch faster. Waste less.
Give your R&D teams an always-on co-pilot that proposes ready-to-test formulations in minutes—balanced for performance, cost, safety, and sustainability. Powered by Simreka’s materials AI and the industry’s richest 150M+ record Databank, our generator turns requirements into optimized recipes, complete with predicted properties, compliance checks, and supplier-ready outputs.
Why teams choose Simreka
70% faster concept-to-candidate (case studies) with virtual experiments replacing trial-and-error
Multi-objective optimization: hit targets for performance, cost, toxicity & CO₂—all at once
Regulatory-smart by design: REACH, GHS, EPA, allergens & label claims checked as you generate
Enterprise-ready: secure cloud, on-prem, or hybrid deployment; SSO, audit trails, versioning
Data in, insight out: tap Simreka’s Databank + your internal data for richer, better suggestions
What it does (at a glance)
Generate optimal formulations from goals & constraints (e.g., viscosity 2–3 Pa·s, VOC < 50 g/L, cost <$2/kg)
Reverse engineer alternatives when an ingredient is restricted, out-of-stock, or too costly
Predict properties before you mix (rheology, adhesion, stability, barrier, sensory, etc.)
Score sustainability (CO₂, recyclability, green chemistry metrics) alongside performance
Auto-check compliance for regions & markets; export documentation and labels
Explain the “why” with interpretable drivers and sensitivity sliders
How it works
Ingest & align data
Connect lab data (LIMS/ELN), SDS/COAs, supplier sheets, and literature. DataDive structures unstructured docs; DocTalk summarizes technical papers; ImageXP extracts data from lab images and plots.Set goals & constraints
Define targets, ranges, forbidden lists, allergens, budget caps, and sustainability goals.Generate & simulate
MatIQ proposes candidate recipes; forward & reverse simulations predict properties and risks.Compare & choose
Side-by-side scoring (performance, cost, risk, CO₂). One click to swap ingredients or tighten constraints.Validate & export
Export BOMs, label claims, and test plans; push to PLM/ERP; track results for continuous learning.
Built on Simreka’s AI stack
Core AI engine: multi-objective optimization & property prediction
Databank (150M+ records): materials, additives, interactions, regulations
ChemQuest (LLM search): natural-language querying across chem data & patents
DocTalk: instant patent & paper summaries with citations back to source
ImageXP: auto-read microscopy/curve images into structured data
DataDive: extract entities, units, ranges from PDFs, SDS, COAs, reports
Use cases (ready today)
Coatings & Paints: gloss/DOI, hiding power, VOC, corrosion resistance
Adhesives & Sealants: tack, peel, shear, cure profile, open time
Personal Care & Cosmetics: clean-label, allergen-free, sensory targets, stability
Food & Beverage (R&D): additive optimization, clean label alternatives
Batteries & Energy: binder/solvent systems, electrode mix, viscosity windows
Packaging & Polymers: barrier, clarity, recyclability, bio-content
Ceramics/Metals: sintering aids, densifiers, strength/toughness trade-offs
Compliance & sustainability—built in
REACH / GHS / EPA rules & lists checked live during generation
Claim & allergen controls (e.g., “fragrance-free”, “paraben-free”, food allergens)
Sustainability scoring: CO₂, recyclability, renewable content, solvent metrics
Audit trails & versioning for regulatory and IP documentation
Integrations & deployment
Connectors: LIMS/ELN, PLM/ERP (SAP, Oracle), MDM, data lakes, SSO (Okta/AD)
APIs: REST/GraphQL for programmatic runs & pipeline automation
Deployment: Cloud, On-Prem, or Hybrid with data locality controls
Proof & outcomes
Fewer wet experiments: prioritize only the highest-likelihood candidates
Lower material costs: find equivalent or better substitutes instantly
Faster compliance: fewer reformulation cycles late in the process
Measurable sustainability gains: optimize for CO₂ without losing performance
FAQs
How accurate are predictions?
We benchmark against historical lab results; typical targets are within lab-reproducibility ranges. Your data + Databank improve accuracy over time.
Do we keep ownership of our data?
Yes. Your data remains yours. Access is governed by your tenancy and RBAC; private deployments available.
How quickly can we go live?
Pilot projects typically stand up in 2–4 weeks with 1–2 product lines, then scale.
Can we ban or whitelist ingredients?
Absolutely—set forbidden lists, supplier preferences, and regional constraints per project.
What about LinkedIn/website claims?
The generator includes approved phrasing libraries and compliance checks to avoid unapproved claims.
