Independent freelance support
Make your data easier to trust and use.
I organize approved business records, review duplicates, and flag missing or unclear information. Your handover can include a cleaned file, the rules used, and a list of items that still need your decision.
Discuss your projectTry a small example
A tidy table can still contain a wrong value. See how source checks and unresolved fields affect a handover.
Start with your task
Examples of work we can scope together. The source material and intended result determine the approach.
Manual typing, copy/paste, form entry and structured records from authorized files, images, business cards or directories.
At handover A reviewed Excel, CSV or Google Sheets table with source references and missing-field notes.
Prepare editable tables or Word/PowerPoint content from suitable source material. Agree whether layout recreation is needed.
At handover An editable working file, a checked sample and a list of ambiguous text or layout exceptions.
Standardize formats, categorize records and review duplicates using agreed matching rules. Unknown values remain unknown.
At handover A clean working copy, duplicate decisions, field definitions and a change log.
Transcribe client-owned invoices or bank statements, and organize visible product codes. This is data preparation, not accounting or document authentication.
At handover Structured entries linked to source pages, with reconciliation checks and unresolved values.
Extract agreed information or transcribe authorized material after reviewing language, audibility and scope.
At handover A reviewed transcript or table with timestamps and uncertain passages marked for follow-up.
A useful fit
For teams working with inconsistent spreadsheets, repeated records, missing fields, or authorized information that needs extraction and careful review.
Cleaning is not the same as verifying every fact. AI can assist with agreed extraction and organization, with manual checks. Unresolved information is retained for follow-up, not invented. Private material requires an agreed handling process.
Self-initiated demonstrations with synthetic data, created to make the process and deliverables inspectable.
Data cleanup
Clean 40 synthetic source rows, inspect exact-match duplicates, and review the information a careful process leaves unresolved.
Self-initiated demonstration · Synthetic dataExplore the workA clear starting point
Start with a description. Please don’t send passwords, tokens, private contact lists, or full client datasets through the enquiry form.
From brief to handover
Useful to know
Work is scoped around an original source and a separate working copy. The handover distinguishes the source from the reviewed changes.
Matching rules are agreed using available fields, such as company and email. Ambiguous matches are flagged rather than silently merged.
AI can support an agreed task using authorized inputs. The schema, sample, review checks, and known limitations are defined before the output is used.
Prepare your project
Read the guide and adapt its editable template to your task.
Hand over usable records with field definitions, a change log and unresolved issues. Includes a reusable cleaning agreement and reconciliation checklist.
Turn suitable PDFs, scanned tables and images into structured spreadsheets. Define the columns, preserve source references and review uncertain text before delivery.
Your next step
Share the task, your current tools, and any constraints. I’ll review the brief and let you know how I can help.
Discuss your project