Where Matflow is headed
The platform ships in research cycles, not marketing cycles. This page is the honest version of that: what you can use today, what is being built next, and what is on the horizon.
In the platform today
Pipeline
End-to-end chaining of Data Synthesis → Evaluation → Prediction → Optimization with synthetic-data nodes and TEA in the loop.
Cost-aware optimization
TEA with five costing modules and six-tenths scale-up rules feeding a single net-value objective.
Explainable prediction
Five-model ensemble with global/local impact, conformal intervals and extrapolation flags on every prediction.
Screening, DoE & active learning
Structural-similarity virtual screening, five design families, and a Bayesian active-learning loop.
AI Copilot + Data Enrichment
Page-aware AI Copilot grounded in the docs with inline citations, plus tabular extraction from literature PDFs.
Evaluation suite
Quality, ML-efficacy, dimensionality-reduction, Privacy Shield and anomaly-detection reports on every generated batch.
Building next
Model registry & governance
Every trained model versioned, comparable, and promotable — no more retraining on every optimization run. Dataset versioning and lineage from raw upload to final candidate.
Model Hub expansion
New generative modes for Data Synthesis; new ensemble variants, Gaussian-process and stacking models for prediction; new multi-objective and Bayesian optimization strategies for search.
Formal privacy suite
DCR/NNDR metrics, membership-inference scores, and TSTR/TRTS efficacy — the standard set reviewers ask for — plus optional differential privacy for shareable synthetic data.
Deeper explainability
PDP/ICE plots, permutation importance, H-statistics, and quantile regression for asymmetric uncertainty.
Run templates & scheduling
Save any configuration as a reusable template, sweep parameters across batch runs, and re-optimize on a schedule as new lab data arrives.
Reproducibility bundles
Every run exports data, config, seed, environment and results as a single bundle a reviewer can reproduce.
On the horizon
Unit-aware columns
Declare units per column; the platform converts, validates dimensional consistency, and labels every axis correctly.
Chemical intelligence
Parse chemical formulas, look up elemental properties, and warn on impossible formulations before you generate.
Notifications
In-app, email and webhook events for run completion, quota levels, project invites and security events — with quiet hours.
Multilingual platform
English shipped with an Arabic locale scaffolded and full RTL support.
Public status history
90-day uptime bars, incident timelines and scheduled-maintenance notices on the status page — built on real recorded history, not estimates.
Organizations
Shared projects, role-based collaboration and comments — bringing multi-researcher groups into one workspace.
Help shape what comes next
Feedback from researchers working on real data decides the roadmap — not speculation. Tell us what the platform is missing.