Reliable AI answers
On clean, semantically prepared data, accuracy improves dramatically — user trust is preserved.
Smartegy
Data Cleaning & AI Preparation
AI is exactly as good as the data it works from
We turn company databases and document stores AI-ready: data cleaning, unification and semantic preparation — so your AI rollout starts with a system that gives reliable answers, not with the "garbage in, garbage out" trap.
Data audit with a clear reportAI-assisted cleaning with human validationData quality maintained for the long termEU GDPR — your data stays yours
Why critical?
The most common cause of failed AI rollouts is poor data quality
Duplicate records, product names written five different ways, missing attributes — AI cannot fix these either. This service removes exactly that risk from the project.
Pays off on its own
Fewer duplicate records: more accurate reports, fewer billing errors — even without AI.
Lasting effect
The import pipelines we build keep data quality high for the long term.
The process
From audit to lasting data quality
First we see what is there: the audit report shows what is usable right away, what needs cleaning and what is missing — then the work begins.
01
Data audit
Duplicates, incomplete records, inconsistent naming, outdated data — with a clear report
02
Cleaning and unification
Merging duplicates, normalizing names and units, filling missing attributes with AI support and human validation
03
Semantic preparation
Documenting the data model, defining business terms, building searchable indexes
04
Continuous data quality
Import pipelines, data-quality metrics and alerts — so the data stays clean
What you get
From raw data to an AI-ready data asset
Data audit
Databases reviewed, with a clear report: what is usable, what needs fixing, what is missing.
Duplicate handling
Detecting and merging duplicates of customers, products and partners.
Normalization
Unifying names, categories and units — the same product should not exist under five names.
Semantic indexes
Meaning-based, searchable indexes for product data and documents.
Document processing
Contracts, policies and technical descriptions turned into a queryable knowledge base.
Import pipelines
Loading and update processes so data quality is maintained.
Delivered project
A 160,000+ item product catalog, prepared for AI
We prepared a technical distributor’s entire product catalog for AI: normalized names, unified technical parameters and indexes ready for semantic search. AI-based quoting runs on this data asset today.
- Normalized product names and parameters
- Indexes ready for semantic search
- Documented data model and business terms
- Import pipelines for lasting data quality
160,000+
items
product catalog prepared for AI — a delivered project
Measurable business impact
A precondition of AI success — and a benefit on its own
Clean data does not only remove the risk from your AI rollout: more accurate reports and fewer faulty processes bring money even without AI.
01
Project risk
The most common cause of failure — poor data quality — is removed from the project
02
Accuracy
Reliable AI answers from day one
03
Direct benefit
More accurate reports, fewer billing errors — even without AI
04
Future projects
An organized, documented data asset makes every development faster and cheaper
Human validation
AI-assisted completions and merges are finalized with human approval.
Production systems protected
The audit and the cleaning run in a controlled process, without disturbing operations.
Documented data model
The finished data model and glossary are the company’s documented, reusable knowledge.
EU GDPR and your own AI context
Full EU GDPR compliance. The company builds its own AI context: your data never trains external large language models and is never passed to third parties — your business secrets remain yours for the long term.
FAQ
Worth clarifying
What data do you work with?+
Product catalogs, customer and partner registries, document stores — both databases and file-based sources.
How long does it take?+
The audit answers that: after the status report we give a precise estimate for the schedule of cleaning and preparation.
Does it require downtime?+
No. The work runs in a controlled process, without disturbing your production systems.
What guarantees the data stays clean?+
The import pipelines, data-quality metrics and alerts we build — cleaning is not a one-off action but a maintained state.
Is our data used to train external AI models?+
No. The system operates with full EU GDPR compliance, and the company builds its own, isolated AI context. Your data never flows into the training of external large language models and is never handed to third parties — the company knowledge you build remains exclusively yours.
Start with a data audit
After the audit you get a clear report: what is usable right away, what needs cleaning, and what AI preparation would bring on your data asset.