Strategy and architecture
Define where private models create value, how they connect to existing systems, and where cloud services still make sense.
Model Context ProtocolAI gateway architectureDesktop-to-cloud roadmaps
Expertise
Two practices. One engineering standard.
Covalent Forge works where operational control, technical depth, and credible evidence matter more than a generic AI rollout.
Practice 01
For organizations
Sovereign AI
Put useful models close to your data and operations while preserving a deliberate path to larger infrastructure and cloud services.
Pilots and proofs of concept
Turn a bounded operational problem into a working application using models deployed within your environment.
Use-case and risk definitionMeasured model evaluationOperator feedback loops
Local model operations
Tune, serve, and observe open models with an inference stack sized to your workload and hardware.
vLLM, llama.cpp, and SGLangQuantization and throughput tuningMonitoring and handoff
Practice 02
For labs and institutions
Research engineering
Extend a research team with focused software and ML engineering while keeping scientific questions, assumptions, and results visible.
Reproducible research pipelines
Create clear paths from data and configuration to comparable experiments, artifacts, and results.
MLflow and experiment trackingBenchmark reproductionEvaluation design
Custom model engineering
Work below the standard training interface when a research question requires specialized model behavior or performance.
PyTorch cross-attention modulesCustom objectives and lossesCUDA kernel development
Institutional compute
Move research workloads from individual workstations to shared accelerators without losing reproducibility.
H200, GH200, and Blackwell systemsSLURM jobs and debuggingPerformance and resource analysis
Engagement models
Choose the smallest useful commitment.
Technical discovery
A short assessment that produces a decision, architecture, risk register, or experimental plan.
Focused pilot
A bounded implementation designed to prove utility or technical feasibility before broader investment.
Research collaboration
An embedded engagement organized around experiments, artifacts, and regular written review.
A useful first conversation