Support for data systems under pressure: memory limits, long runtimes, unstable types, and cost growth. Reviews also cover automation, LLM systems, and twin builds when they sit inside a data workflow. Output is a short plan plus specific actions, based on evidence from logs and runs.
Support focused on pipelines under pressure: memory limits, long runtimes, unstable types, and cost growth. Output is a short plan plus specific actions, based on evidence from logs and runs.
Fast review of an existing pipeline to locate failure points and slow steps.
Reduce total run time and spend, without changing the meaning of outputs.
Lightweight checks to confirm outputs can be trusted after changes.
Review a retrieval or assistant setup (RAG or tool use) with checks for quality, safety, and cost.
Design or review automation that runs safely: guardrails, fallbacks, monitoring, and audit traces.
Review a digital or geomatic twin build: data feeds, state updates, spatial joins, and validation rules.
Move the slider to estimate the shape of work. This is not pricing; it is a quick way to set expectations.
Tip: if the pipeline touches 100GB+ and runs for hours, start with “Medium”.
A short report: failure points, measured bottlenecks, and a ranked change list. When relevant, include a template checklist for future runs.
Work can be based on logs, schema summaries, and small redacted samples. No raw data is required by default.
Runtime reduction, peak memory reduction, fewer retries, and stable outputs (row counts, null rates, and key distributions).
Yes. Focus stays on pipeline behaviour: file formats, joins, sampling, memory, and correctness checks.
Ready to start? Use the contact form to send a short problem statement. Replies are usually sent within 2 business days.