Built for finance and operations teams

Your Data
Validated at Scale

Reconcile sources, enforce data quality, and clean files beyond Excel's limits — all in your browser. Nothing uploaded. Everything exportable.

Open Reconciler Run Data Quality

Reconciliation

Prove your sources agree

Match records across files with key mapping and tolerances. Isolate missing rows and mismatched values for review. Export reconciliation evidence ready for audit trails.

Defendable close numbers — every cycle.

Open Reconciler →
Reconciliation Result 2 files compared
Invoice Source A Source B Status
INV-1001 $4,200.00 $4,200.00 Matched
INV-1002 $1,850.00 $1,850.00 Matched
INV-1003 $3,100.00 $3,140.00 Mismatch
INV-1004 $920.00 — Missing
2 Matched 1 Mismatch 1 Missing

Data Quality

Expose hidden risk before it spreads

Flag blank-heavy columns and unexpected outliers. Detect rare values and format drift. Surface column health so teams can act before bad data enters dashboards or AI.

Fewer bad assumptions reaching your reports.

Run Data Quality →
Column Health Report 12 columns scanned
customer_id
98%
email
94%
contact_number
71%
region
43%
2 Healthy 1 Warning 1 At Risk

Power Query Alternative

Standardize large files without Excel breakpoints

Trim, split, parse, normalize IDs, and dedupe. Apply the same pipeline every cycle for consistency. Export clean data for BI, finance, or automation — no row limits, no VBA.

Reliable inputs without the Excel ceiling.

Clean a File →
Transformation Pipeline 3 steps applied
Raw Input
" ACME corp " "acme-CORP" "Acme Corp."
Step 1
"ACME corp" "acme-CORP" "Acme Corp."
Clean Output
"Acme Corp" "Acme Corp" "Acme Corp"
3 rows cleaned 2 duplicates resolved

Your final safeguard as AI takes over

As AI usage grows, garbage in scales faster than ever. Validation is the control point between raw data and decisions you can defend.

Truth

Reconciliation confirms whether sources truly agree before numbers are reused.

Trust

Data quality identifies hidden column defects that distort downstream models.

Ready

Clean, standardized outputs feed reporting and AI workflows with less rework.

Start validating

Pick any entry point. Reconcile sources, check data quality, or clean a file. Export evidence either way.

Open Reconciler Run Data Quality