Data Science
Ensemble models, deep learning, NLP, and agentic AI architectures that move the metrics your business actually reports on.
Read moreData Science · MLOps · Model Risk
Built to hand off.
Built to maintain.
Built to matter.
Senior practitioners who build ML systems, meet regulatory standards, and transfer full ownership to your team.
Engagement Snapshot
Q3 retail credit portfolio
57.3%
lift in default-prediction precision after model rebuild & revalidation.
12wk
delivery100%
SR 26-23x
inferenceCapabilities
Three disciplines, one engagement model.
We assemble small senior teams that pair with yours — diagnosing fast, building responsibly and leaving documentation a regulator can read.
MLOps
Production ML platforms — pipelines, feature stores, monitoring and rollback — engineered for scale and auditability.
Read moreModel Risk Management
Independent validation, governance frameworks and documentation aligned with SR 26-2, OCC 2026-13, EU AI Act, PRA SS1/23, NIST AI RMF and ISO/IEC 42001.
Read moreOur Approach
Senior practitioners. No layers.
01
Diagnose with rigor
Two-week assessments map data, models and risk posture against business objectives — surfacing what to fix and what to leave alone.
02
Build for production
Every artifact we deliver — notebook, pipeline, validation report — is written to be re-run, audited and extended by your team.
03
Hand over completely
We embed knowledge transfer into the engagement so the platform thrives long after we leave. No lock-in, no black boxes.
Data Science · MLOps · Model Risk
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