Raw data in.
Analytics-ready data out.
Cynch takes the spreadsheets, exports, and feeds your team has been wrestling with and hands back clean, structured, trustworthy datasets — ready for reporting, modeling, or migration.
Numbers we hold ourselves to
Every step between messy and meaningful
Take one piece or the whole chain — from the first awkward export to a feed your dashboards can rely on.
Ingestion & pipelines
Pull data from files, APIs, and databases into one dependable, repeatable flow.
Cleaning & validation
Deduplicate, standardize, and enforce rules so the numbers actually add up.
Transformation
Reshape and normalize records into the schema your tools expect.
Enrichment & labeling
Add reference data and consistent labels for analytics and ML.
Delivery & integration
Land finished data in your warehouse, BI tool, or as a clean API feed.
Quality & monitoring
Ongoing checks and lineage so quality holds as the source keeps changing.
Four steps, no mystery
Scope the sources
We look at a real sample, the formats, and exactly what “done” means for you.
Build the pipeline
A repeatable flow that ingests, reshapes, and routes the data — documented as we go.
Clean & validate
Rules catch gaps, duplicates, and outliers before anything reaches your reports.
Deliver & watch
Output lands where you need it, with checks that flag drift on the next refresh.
Built around the result you actually need
- Analytics-ready datasetsTidy, joined tables your BI tool reads on the first try.
- ML training dataLabeled, balanced, and documented sets for modeling.
- Migration & consolidationMerge legacy systems into one clean source of truth.
- Compliance-ready recordsConsistent, auditable data with clear lineage.
Most teams don’t have a data problem. They have a data preparation problem — and that’s the part we love.
Cynch is a small, focused practice in Austin built around one stubborn belief: that the unglamorous work of cleaning and shaping data is where good decisions actually begin.
Before you send the first file
What formats can you take in?
CSV, Excel, JSON, Parquet, database exports, and most API responses. If you can export it, we can almost always ingest it — messy headers and all.
Is my data kept private?
Yes. Work happens in access-controlled environments, samples are handled under agreement, and we delete working copies once a project wraps unless you ask otherwise.
Do you set up something repeatable or a one-off?
Both. Some clients need a single cleanup; others want a standing pipeline that refreshes on a schedule. We scope to whichever fits.
How fast can we see results?
A first usable pass on a representative sample is usually back within about 48 hours, so you can judge the output before committing to the full set.
Have a dataset that’s fighting you?
Send a sample or just describe the mess. We’ll tell you, plainly, what it would take to get it clean.