Machine Learning Consulting

From feature engineering to MLOps, we build reliable ML systems with clear business linkage and lifecycle control.

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iconTechnology Stack
  • scikit-learn
  • XGBoost
  • LightGBM
  • PyTorch
  • TensorFlow
  • MLflow
  • W&B
  • Feast
  • Arize
  • WhyLabs
  • Airflow
  • Kubeflow
  • Docker
  • Kubernetes

End-to-End ML, Done Right

Problem Framing & KPI Design

Tooling rail: decision rubrics • KPI maps • lift curves

Edge: ReinΩlytix™ binds model metrics to P&L impact.

Data Prep & Feature Engineering

Tooling rail: Feast • drift checks • leakage tests

Edge: Reproducible features with lineage and tests.

Modeling & Validation

Tooling rail: sklearn/XGBoost/LightGBM • PyTorch/TensorFlow

Edge: Robust CV, fairness, and stability checks.

MLOps & CI/CD

Tooling rail: MLflow • registries • pipelines • canary

Edge: Promotion gates with rollback and audit trails.

Monitoring & Drift Management

Tooling rail: Arize/WhyLabs • PSI/KS • alerts

Edge: Playbooks for drift, outliers, and incident response.

Cost & Performance Optimization

Tooling rail: quantization • batching • autoscaling

Edge: FinOps guidance for sustained ROI.

Our Clients

Clients that trusted Us

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Methodology

Frame & Baseline KPIs

Business-linked metrics locked.

Build & Prove QA

Validation + fairness + stability.

Ship & Run MLOps

Registry, canary, monitoring.

ML with lifecycle discipline

Reliable models, governed promotions, measurable value.

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  • KPI-first framing and evaluation
  • Tested features and reproducibility
  • Registry-based promotions with rollback
  • Drift detection and response playbooks
  • FinOps-aware inference optimization

Assurance Strip

Foundational safeguards ensuring compliance, accountability, and operational integrity.

FinOps-aware Inference Optimization Techniques and best practices to optimize AI inference workloads while controlling cloud and operational costs

Boardroom Kit

Executive tools to govern, track, and fund AI initiatives responsibly.

MLOps Blueprint Comprehensive framework outlining processes, tools, and standards for managing ML lifecycle efficiently
Promotion Gate Policy Guidelines and checkpoints for promoting models from development to production while ensuring quality and compliance
Drift Response Playbook Standardized procedures to detect, analyze, and mitigate model performance drift in production environments
ROI Tracker Template Tool to measure, monitor, and report the return on investment for AI and ML initiatives

Get Started – AI Efficiency with
Proven Performance

Accelerate AI workloads with rigorously tested Quantum-Inspired Neuromorphic AI.

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United States

Strategemist Corporation
16192 Coastal Highway Lewes, Delaware 19958

United Kingdom

Strategemist Limited
71-75 Shelton Street,Covent Garden, London, WC2H 9JQ

India

Strategemist Global Private Limited
Cyber Towers 1st Floor, Q3-A2, Hitech City Rd, Madhapur, Telangana 500081, India

KSA

Strategemist - EIITC
Building No. 44, Ibn Katheer St, King Abdul Aziz, Unit A11, Riyadh 13334, Saudi Arabia