Notebook → Module
AI-assisted refactoring turns exploratory notebooks into typed, tested Python modules — preserving the scientist's intent while removing the cruft.
Spotlight — Crosswalk
From notebook to production — in days, not quarters.
Crosswalk is our cross-platform MLOps suite that uses AI to convert data scientists' experimentation and iteration code into production-grade, auditable codebases — without losing the modeling intent that made the experiment work.
87%
of ML models never reach production. Crosswalk is built to change that ratio.
6×
average reduction in time from validated experiment to deployed service.
0
compromises on reproducibility, lineage, or regulator-readable documentation.
What it does
A complete bridge — not a checklist of plugins.
Crosswalk is opinionated about the parts that matter and pluggable everywhere else.
Pipeline synthesis
Detects training, feature, and inference boundaries and generates orchestrator-ready DAGs for Airflow, Kubeflow, Dagster, or Vertex.
Cross-platform targets
One source-of-truth experiment compiles to AWS SageMaker, Azure ML, Databricks, or on-prem Kubernetes with identical lineage.
Governance baked in
Every emitted artifact carries a model card, data contract, and validation harness mapped to SR 26-2, the EU AI Act, NIST AI RMF, and ISO/IEC 42001.
Reproducible by design
Deterministic environment manifests, pinned dependencies, and DVC-style data hashes — re-run any experiment six quarters later.
Drift & cost telemetry
Production monitors are emitted alongside the model, wired to your observability stack from day one.
How it works
Four steps. One source of truth.
01
Ingest the mess
Point Crosswalk at a folder of notebooks, scripts, and pickled models. It maps your unwritten data contracts and identifies the live decision logic.
02
Translate with AI
Large language models, constrained by static analysis and your house style guide, rewrite the code into modular, typed, and tested production form.
03
Compile to your platform
Choose your target — SageMaker, Databricks, Kubeflow — and Crosswalk emits the pipeline, IaC, and CI/CD configuration.
04
Govern continuously
Validation reports, model cards, and monitoring hooks regenerate on every change. Audit trails are a side-effect, not a project.
Curious whether Crosswalk fits your stack?
We run scoped pilots on a single model lineage so you see the value before committing to a platform rollout.