Matflow vs. Citrine — an honest comparison
Citrine is an enterprise materials-informatics platform. We cannot verify Citrine's capabilities, pricing or roadmap from this repository, so this page does not claim them. It shows what Matflow verifiably ships — with the file behind each claim — and the questions to ask both platforms before you commit.
What this page does — and does not — claim about Citrine Informatics
Two commitments, both about trust.
Five dimensions you can check in the repository
These are the axes we would use to evaluate any research platform — and the ones we hold ourselves to.
Every scientific response carries one of six evidence classes — MEASURED, COMPUTED, PREDICTED, EXTRACTED, HYPOTHESIS, DEMO — with a level, plus an engine card naming what produced it. Surrogate paths are relabelled DEMO rather than printed as fact (backend/core/engines.py:114, 251-329).
A free tier and published plans anyone can reach without a sales call. The pricing page renders the same catalog the server enforces through GET /api/billing/plans (client/src/pages/StudioPricing.jsx, backend/core/pricing.py:1-48).
Cost is a first-class objective: TEA prices raw materials, equipment (six-tenths rule), CapEx/OpEx and end-of-life credit, and screening-grade LCA adds GWP, energy demand and E-factor — so candidates are ranked by net value, not performance alone (client/src/pages/docs/content.jsx, stages/catcost and lca/overview).
Data lives under a per-account directory with every served path validated (backend/core/paths.py:71-105); datasets export as CSV and RO-Crate v1.1 provenance ZIPs, and the repository ships a single-tenant Docker Compose overlay (deploy/production/docker-compose.single-tenant.yml).
All plans include the full pipeline — the differences are throughput, not features (client/src/pages/docs/content.jsx, account/billing). No module is held back behind an enterprise quote.
Matflow vs. Citrine Informatics: verifiable dimensions and open questions
The middle column is enforced in this repository. The right column states what we could not verify and what to ask — never what the other platform does or cannot do.
| Dimension | Matflow (verifiable) | Citrine Informatics: what we could not verify — ask |
|---|---|---|
| Trying it before sales | Free tier and self-serve signup; the full pipeline runs on a bundled demo dataset before you upload anything (client/src/pages/docs/content.jsx, getting_started/overview). | Demo-first sales is common in this segment. We could not verify a self-serve trial from public sources as of 2026-10. Ask: can I run a trial on my own file before procurement? |
| Published pricing | Monthly and annual plans with metered limits and credit packs, rendered live from the billing catalog the server enforces (backend/core/pricing.py:1-48). | Quote-gated for most enterprise platforms; not public. Ask for an itemized, metered price sheet and what resets when. |
| Evidence labelling | Six classes with levels and an engine card on every result; ML and surrogate outputs are PREDICTED/DEMO, never presented as measurements (backend/core/engines.py:114, 251-329). | Varies; not publicly documented at result level. Ask whether measured, computed and predicted outputs are distinguishable on the result itself. |
| Cost and sustainability as objectives | TEA (raw materials, six-tenths equipment sizing, CapEx/OpEx, end-of-life credit) and screening-grade LCA (GWP, energy demand, E-factor) can join the optimization objectives (client/src/pages/docs/content.jsx, stages/catcost; lca/overview). | Varies; costing often sits in a separate module or a consulting engagement. Ask whether cost can be an optimization objective alongside performance. |
| Data ownership and export | Account-scoped storage with path validation; datasets export as CSV and RO-Crate v1.1 provenance ZIPs, with training files SHA-256 hashed (backend/core/paths.py:71-105; backend/core/provenance.py). | Varies. Ask for a portable export specification — format, provenance and deletion path — before signing anything. |
| Deployment model | Browser-first web app; a single-tenant Docker Compose overlay ships in the repository, and the readiness endpoint reports tenancy, region gating and BYOK flags without exposing secrets (deploy/production/docker-compose.single-tenant.yml; backend/core/soc2.py:367-411). | Varies; on-prem and private-cloud options are usually an enterprise negotiation. Ask where the software runs and what single-tenant means in the contract. |
| Module access | Every plan includes the full pipeline: synthesis, evaluation, prediction, optimization, TEA, LCA, screening, DOE and the physics engines — limits are throughput, not features (client/src/pages/docs/content.jsx, account/billing). | Varies; capabilities are often tiered or licensed per module. Ask for the full module list and which tier unlocks each one. |
| Programmatic surface | OpenAPI 3.0 spec and interactive reference at /developers, a Python SDK under tools/sdk, hashed API keys, and HMAC-signed webhooks with retries (client/src/pages/docs/content.jsx, sdk/overview; backend/core/webhooks.py:1-14). | Varies; API access may be limited or enterprise-only. Ask for an OpenAPI spec, SDKs, key lifecycle and webhook events. |
| Reproducibility | Benchmark reports ship downloadable reproducibility bundles, and RO-Crate exports carry provenance and engine cards (client/src/pages/StudioBenchmarks.jsx; backend/routes/rocrate_routes.py). | Not public. Ask whether a reviewer can reproduce a result from the dataset version, configuration, seeds and metrics. |
Published pricing is the exception, not the rule
Price transparency in this category is rare — which is exactly why we publish ours.
Questions we expect from Citrine Informatics evaluators
Direct answers, including the limitations.
Citrine serves enterprise data programs. Is Matflow the same thing?
Can Matflow import data from Citrine?
Where does Matflow publish its prices?
What happens to my data if I stop using Matflow?
Does this page claim Matflow is better than the other platform?
How were the Matflow claims on this page verified?
Judge it on your own data
No demo gate and no sales qualification: sign up, load the bundled dataset or your own file, and inspect every result's evidence class before you decide. The comparison that matters is the one you run yourself.