Reconcile your production data with SAP. Without touching Excel.

Exactis reconciles your production exports (CSV or Excel files from a MES or the ERP) with your SAP or Sage data. Only exact matches are validated automatically; everything else goes to human review, and each remaining anomaly is flagged in the report. Zero silent errors: nothing approximate gets validated without you.

  • Working MVP, in development since September 2026
  • Pilot program open to 3 to 5 industrial sites, Morocco first
  • Project in formation

Designed first for manufacturers in Morocco and Africa running an ERP (SAP, Sage).

Formats supported today: SAP, Sage and MES exports as CSV, TSV, delimited TXT, XLSX or XLS. Direct connectors: on the roadmap.

SAP · CSVSage · CSVMES · CSVTSVTXTXLSXUTF-8ISO-8859-1SAP · CSVSage · CSVMES · CSVTSVTXTXLSXUTF-8ISO-8859-1
The problem

The invisible cost of manual reconciliation.

Every month, your teams manually cross-check production data against the ERP. Every mistake ends up in your KPIs.

01
4 812
1 240
0,98
L-02
3 377
1 240
0,97
L-O2
2 905
1 118
0,97
L-03

Data Entry Errors

Manually matched SAP exports that distort your KPIs.

02
J+1J+3J+5J+8
consolidation_usine_v7_FINAL(2).xlsx

Reporting Delays

Time lost at every close consolidating factory data.

03
SQDC · N/A

Blind Decisions

Impossible to steer SQDC (Safety, Quality, Delivery, Cost) performance on reliable figures.

How it works

A 3-step reconciliation pipeline.

Multi-source ingestion

Drop your SAP, Sage or MES exports as CSV, TSV, delimited TXT, XLSX or XLS, with your item master: the files are read in your browser.

Controlled matching

The Exactis engine normalizes formats, detects anomalies and matches references against your master data. Only exact matches are validated automatically; everything else goes to human review.

Structured Export

You download a CSV report that traces every check and every human decision, with its SHA-256 fingerprint.

01 · Raw sources
export_SAP.csv
export_Sage.csv
mouvements_MES.csv
referentiel.csv
export_ERP.txt
02 · Exactis engine
03 · Checked data
The differentiator

Why a code that is 98.3% similar is not the same code

A matching process based only on a similarity score accepts a reference as soon as it clears a threshold. In my tests, a reference with two digits swapped got a similarity score of 98.3%: it would have been validated without anyone noticing. Exactis does not validate it: it stays blocking and goes to human review. This case is part of the engine's regression tests.

Entered in the export

HT-10428-PET

ERP master data

HT-10482-PET

Similarity

98.3%

Blocked · human review
Reconciliation engine preview

Chaos in. Checked data out, before the ERP.

The engine checks every row against your ERP master data and proposes the closest match. While any anomaly remains, the report cannot be marked complete.

DEMOEXACTIS / MATCHING ENGINE

Ingest

Normalize

Match

Validate

Report

Raw inputs Validation core ERP ledger

Demo files (fictitious)

  • demo_fictif_export_production_casablanca_plant_02.csv40
  • demo_fictif_referentiel_articles.csv15

Analysis log

Analysis result

Rows checked

—

Validated (exact)

—

Anomalies

—

Blocking rows

—

Anomaly pending

L27

Suggestion, human review required

HT-10428-PETHT-10482-PET

Numeric segment changed: human check required

98.3%
Use Case: SQDC Performance & ERP Integration

Designed for industrial complexity.

Automate the matching between your production lines and the SAP item master. No more mistyped item codes slipping through unnoticed: your teams analyse instead of cross-checking files.

Production lines
OF-2026-6101 · HT-10482-PET
OF-2026-6102 · HO-20517-VRE
OF-2026-6103 · HT-10485-PET
OF-2026-6104 · PF-50128-28G
ERP item master
HT-10482-PET
HO-20517-VRE
HT-10485-PET
PF-50128-28G
Demo data4 / 4 exact matches ✓
Security

Security: what is in place today

In the Playground, your file is analysed locally: it never leaves your browser.

Encrypted connections (HTTPS).

For a pilot, columns containing personal data (operators, employee IDs) can be anonymised before any exchange.

Roadmap

SSO, dedicated hosting in Europe, or deployment in the customer's environment.

Adam Jalal, founder of Exactis

Adam Jalal

Founder · Data engineer

Paris
About the founder

Adam Jalal, founder.

I am a computer science student, specialising in data engineering and cloud architecture. I grew up between Italy and Morocco.

Exactis was born during my Data Engineer internship at a major food-industry group in Casablanca. There I saw how, across the industry, manually consolidating production data and SAP data for SQDC reporting takes time, and how a simple data-entry error, such as a transposed item code, can go unnoticed all the way to the dashboards.

I designed Exactis around one principle: a match is validated automatically only if it is exact. Everything else is decided by a human before the data goes out.

  • ETL pipelines
  • Data Engineer internship · Casablanca
  • Data engineering
  • Cloud architecture
30 days on your real exports
Pilot program

3 to 5 industrial sites, Morocco first.

For 30 days, Exactis is used on real exports from one of your data flows (for example your ERP and production exports), analysed locally.

What I ask of you:
anonymised exports and two follow-up meetings.
What you get:
free access during the pilot and a direct influence on the product.

After 30 days, we decide together what comes next.

Want to try Exactis on your own exports?

45 minutes with me to look at your files and see whether a pilot makes sense.