Roadmap

Where Matflow is headed

The platform ships in research cycles, not marketing cycles. This page has three honest states — shipped, in progress and exploring — and deliberately no dates: priorities move with research feedback.

How to read this

Three states, one rule: evidence

Every shipped item names the route or module behind it. Everything else is explicitly unfinished.

ShippedIn the platform today and usable — each card links to the real route or names the backend module that implements it.
In progressPartially available or actively being extended. Something may already work; treat the rest as a commitment of direction.
ExploringCandidate work. It may change, merge or disappear based on feedback and evidence — no dates, no promises.
Shipped

In the platform today

Usable now. Each card opens the feature or the documentation behind the claim.

10 areas
Pipeline
End-to-end pipeline & reusable templates

Chain Data Synthesis → Evaluation → Prediction → Optimization with synthetic-data nodes and TEA in the loop on a visual node graph, and save a configuration as a reusable pipeline template (backend/routes/pipeline_routes.py; /pipeline).

Open in the app →
Economics
Cost-aware optimization

TEA runs inside the optimization loop with scale-up costing rules feeding a net-value objective, so candidates are ranked on economics as well as performance (Studio TEA; /studio/tea).

Open in the app →
Explainability
Explainable prediction with honest uncertainty

A cross-validated ensemble returning global/local impact, permutation importance, PDP/ICE curves, conformal intervals from the same folds, and an extrapolation flag on every prediction (backend/models/prediction/generalized_predictor.py; /studio/prediction).

Open in the app →
Design
Screening, DoE & active learning

Structural-similarity virtual screening, six design families, and an active-learning loop with uncertainty sampling, query-by-committee and Bayesian acquisition (Studio Screening, DoE, Active Learning).

Open in the app →
Assistant
Matflow Pilot + Data Enrichment

The page-aware assistant grounded in the docs, with approvals on writes and compute, plus tabular extraction from literature and instrument data (backend/routes/assistant_routes.py; /copilot).

Open in the app →
Quality
Evaluation suite with privacy checks

Quality, ML-efficacy, dimensionality-reduction and anomaly reports on every generated batch — including distance-to-closest-record baseline protection and overfitting checks (backend/evaluators/main_evaluator.py).

Open in the app →
Governance
Governed model registry

Every registered model records task, intended use, limitations, metrics by split, calibration, baselines, artifact hash and a rollback path; a model without traceable metrics cannot be marked validated (backend/routes/model_registry_routes.py; Model Hub registers governed rows).

Open in the app →
Reproducibility
Dataset versions, provenance & export bundles

Datasets version with SHA-256 file hashes, benchmark runs ship downloadable reproducibility bundles, and saved datasets export as RO-Crate v1.1 ZIPs with provenance and engine cards (backend/core/provenance.py; backend/routes/rocrate_routes.py).

Open in the app →
Collaboration
Organizations, roles & public org pages

Organizations own projects and campaigns, members carry roles across a read/write/admin permission matrix, and verified orgs can publish a public profile that feeds the benchmark leaderboards (backend/routes/organization_routes.py; backend/core/rbac.py; /orgs/:slug).

Open in the app →
Operations
Notifications & signed webhooks

An in-app notification center for run completion and project invites, opt-in email on run success/failure, and HMAC-signed webhooks with retries for external systems (backend/routes/notifications_routes.py; backend/core/webhooks.py).

Open in the app →
In progress

Being built now

Actively worked areas; parts may already be live in the product.

6 areas
Models
Model Hub expansion

More generative modes for Data Synthesis, additional ensemble variants and stacking candidates for prediction, and new multi-objective and Bayesian strategies for search.

Privacy
Formal privacy suite

DCR baseline-protection and overfitting checks already ship with evaluation. Membership-inference scores, TSTR/TRTS efficacy and optional differential privacy for shareable synthetic data are the next additions.

Explainability
Deeper explainability

PDP/ICE and permutation importance are in the platform today; H-statistics for interaction strength and quantile regression for asymmetric uncertainty are being built.

Automation
Run scheduling & sweeps

Pipeline templates can be saved and reused now. Parameter sweeps across batch runs and scheduled re-optimization as new lab data arrives are in progress.

Operations
Broader notification coverage

Run completion and invite events are live in-app, by opt-in email and via webhooks. Quota-level and security-event alerts, plus quiet hours, are planned.

Chemistry
Chemical intelligence before generation

Formula parsing, elemental properties and composition descriptors ship today (backend/core/cheminformatics.py). Pre-generation validation that warns on implausible formulations is being extended.

Exploring

On the horizon

Directions we are considering — priorities shift with research feedback, so nothing here is scheduled.

4 areas
Data
Unit-aware columns

Declare units per column; the platform would convert values, validate dimensional consistency and label every axis correctly. Today, unit-aware mapping exists only inside specific instrument and enrichment paths — not general columns.

Reach
Additional locales and RTL

English is the only shipped locale; the design system already uses logical layout properties so right-to-left layouts are supported structurally. Full locales are exploring, not scheduled.

Status
Public status history

Server-recorded 90-day uptime bars, incident timelines and maintenance notices. The /status page today probes live and keeps history in your browser only — there is no server-side historical record to publish yet.

Strategy
The next validated module

The planning docs commit to earning new modules through customer evidence rather than shipping everything at once (planning/2026-09-replan). What gets built next is decided by observed use, not by this list.

Maintenance

How this page stays honest

Two rules keep the roadmap from becoming a wish list.

Shipped means shipped.When an item moves to Shipped, it links to the working route or the backend module — the same standard the changelog uses. We do not mark something shipped because a demo exists.
No dates.Delivery depends on research outcomes and infrastructure, so we do not publish release dates. If a direction matters to your lab, tell us — feedback is the input this page is built from.

Help shape what comes next

Feedback from researchers working on real data decides the roadmap — not speculation. Tell us what the platform is missing.