Enterprise data & AI engineering
ByteLoom Consulting helps enterprises modernize data platforms, engineer scalable cloud architectures, and operationalize AI.
What we do
Every engagement is scoped around an outcome, such as a governed lakehouse, a completed migration or an AI workload in production, and delivered by an architect who also writes the code.
Lakehouse platforms designed and built to be governed, fast and cost-aware from day one, not retrofitted later.
Legacy ETL estates migrated to modern pipelines with reconciliation evidence that the business can sign off on.
AWS foundations and data platform architecture expressed as code: secure, reproducible and sized to the workload.
Retrieval-augmented and LLM applications taken to production with tracing, evaluation and cost controls built in.
Why ByteLoom
ByteLoom is deliberately small and senior. The architect who designs your platform also builds it, reviews the code, and stays accountable for how it runs in production.
Work happens at the level of Spark plans, Delta table design and pipeline code. Recommendations arrive with a working implementation, not a slide.
Designs account for the realities of large organizations: governance models, environment strategy, access control, and many teams sharing one platform.
Reusable patterns, automation and Infrastructure as Code let a platform grow without rework, and leave your engineers able to run it with confidence.
The simplest architecture that meets the requirement, proven with evidence: reconciliation results, cost baselines and measured performance.
Technical insights
Architecture patterns, implementation detail and the trade-offs behind them, written for the engineers and architects doing the work.
Triage a Talend, Informatica or SSIS estate, design the lakehouse target, translate ETL semantics, and prove the result with a reconciliation framework.
A reference framework for observing LLM and RAG applications: signals, a Delta telemetry model, cost attribution, evaluation and governance on Databricks.
Designing Unity Catalog for an enterprise: catalogs, workspace binding, group-based grants, ABAC, lineage, grants as code and Hive metastore migration.
A structured assessment of a Databricks environment, covering configuration, compute efficiency, governance and reliability, with prioritized recommendations. It is being developed as ByteLoom's first reusable engineering accelerator.
Start a conversation
Tell us about the platform you are modernizing, the migration you are planning, or the AI workload you need in production. You will hear back from an engineer, not a sales team.