Data Clean

Any Source. Any Target. Alpica Builds the Bridge.

Alpica Data Clean is an AI-powered transformation engine that takes your data — in whatever messy format it exists today — and converts it into clean, validated, standardised output that matches exactly the schema you need. No manual field mapping. No brittle ETL scripts. Just define the target, point it at your source, and let the AI build the bridge.

Problem

Your data is everywhere. Your target format is exact. The gap between them is expensive.

01

The challenge

Enterprise data lives in ERPs, supplier spreadsheets, legacy databases, CSV exports, and JSON feeds — each with its own naming conventions, units, formats, and quirks. Whenever a new regulation, standard, integration partner, or internal system demands data in a specific structure, someone has to manually figure out how every source field maps to every target field, write transformation logic, handle edge cases, and validate the output.

02

The solution

That manual work is slow, error-prone, and has to be repeated every time the source or target changes. Alpica Data Clean replaces it with an AI pipeline that understands both sides and builds the transformation automatically.

Why Alpica

Why enterprises choose Alpica Data Clean

01
Intelligent field understanding

Semantic Mapping, Not Templates

Forget rigid field-matching templates that break when column names change. Our AI reads field names, descriptions, and actual values to build intelligent mappings — even across systems that use completely different conventions for the same data.

Step 01 of 03
02
Review → Approve → Deploy

Human-in-the-Loop at Every Step

Every AI-generated artifact goes through a review → approve → deploy lifecycle. Confidence scores tell you where the AI is certain and where it needs your judgment. Full audit trails with cryptographic hashing document every decision.

Step 02 of 03
03
Zero data egress

On-Premise, Your Data Stays Yours

Deployed on-premise within your infrastructure. No data leaves your systems. Model-agnostic architecture lets you plug in the LLMs that meet your compliance and performance requirements.

Step 03 of 03
Use cases

One platform. Many transformation problems solved.

DPP
01/05

Digital Product Passports (EU DPP)

Transform product data into regulation-compliant Digital Product Passports — now a dedicated Alpica product, built on Data Clean.

EU ESPR
Explore Alpica DPP
MIG
02/05

Data Migration & System Integration

Moving data between systems with incompatible schemas — ERP consolidation, CRM migration, partner data onboarding. Define the target format, upload the source, and let the AI generate the mapping instead of writing custom ETL code.

ERPCRMETL
REG
03/05

Regulatory & Standards Compliance

When industry standards or regulations define a strict data format (product safety declarations, material safety data sheets, supply chain reporting), use Alpica Data Clean to transform your internal data into the exact required structure with built-in validation.

MSDSSafetyCompliance
SUP
04/05

Supplier Data Harmonisation

Dozens of suppliers sending product data in dozens of different formats? Define one canonical schema, then create a mapping for each supplier format. The AI handles the variation; you get consistent, validated output.

SchemaMappingValidation
DQE
05/05

Data Quality & Enrichment

Run your existing datasets through the Fix stage to detect and repair missing values using machine learning. Use the validation engine to score completeness, accuracy, and consistency — then export clean, enriched data back to your systems.

MLScoringEnrichment
AI repair

AI that doesn't just transform — it repairs

FIX
Machine learning repair

Predict & repair missing data

Real-world data has gaps. Fields are missing, values are malformed, units are inconsistent. Alpica Data Clean doesn't just flag these problems — it fixes them. The Fix stage uses TabPFN machine learning to analyse patterns across your entire dataset and predict the most likely values for missing fields. Every prediction carries a confidence score and is clearly marked in the audit trail so you always know which values are measured and which are inferred.

TabPFNConfidence scoresAudit trail
IMP
Domain-specific enrichment

Enrich with domain-specific logic

Beyond repair, the Impute stage runs specialised calculations tailored to your domain — derived fields, scoring, and regulatory metrics — appending the results directly to your output records. Enrichment modules are configurable for your industry's requirements.

ConfigurableExtensibleDomain logic
Trust & compliance

Swiss-engineered. Audit-trailed. On-premise.

Every action in Alpica Data Clean is recorded: who did what, when, and why. Cryptographic hashes before and after every change let you prove data integrity at any point in the pipeline. The review-approve-deploy lifecycle ensures no AI output reaches production without human verification. And because the platform deploys entirely on-premise, your data governance policies are never compromised.

Free proof of concept

Your source. Your target. A free PoC on real data.

Send us a sample of your messy data and the schema you need. Our engineering team will build a working transformation pipeline on your own data — no obligation, no sales funnel, just proof that it works.

Your source format
Your target schema
Working pipeline
Contact

Stop mapping data manually

See how Alpica Data Clean transforms your own data. Our engineering team delivers a free proof of concept tailored to your source formats and target schemas.

  • Talk to real engineers

    Every message is answered by someone who builds the product — not a sales funnel.

  • Fast, honest replies

    Expect a thoughtful response within one business day, with clear next steps.

  • Built around your context

    We adapt scope, security, and delivery to fit your team and your data.

GDPR-alignedAccepting pilots

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