Ozon Data Services
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Solutions

Where AI actually earns its place.

We do not chase hype. These are the problems where a well-built LLM system pays for itself quickly, and where we have shipped before.

By function

Built for the work you already do.

Every one of these starts from your data and your process, not a demo.

Customer support

Grounded assistants that draft replies from your own docs and tickets, cutting handling time while keeping a human in control.

Analytics & reporting

Natural-language access to your data, plus predictive models that turn history into a forecast your team trusts.

Document processing

Read, classify and extract from contracts, invoices and forms, with confidence scores and a full audit trail.

Risk & compliance

Screening, monitoring and explainable checks that flag what matters and record exactly why.

Operations

Agents that connect your internal tools and take repetitive, rules-based work off your team's plate.

Data & architecture

Cloud data pipelines and the reporting layer under them, designed to be queried by people and agents alike.

Proof

Results from systems in production.

−63%support handling time
Ozon built a retrieval assistant on top of our five years of support tickets and product docs. It drafts every reply our agents send now, grounded in our own content, and the evaluation harness they set up means we can change prompts without holding our breath. Handling time dropped by nearly two-thirds in the first quarter and our CSAT actually went up.
Martina Kovacs
Head of Support, Northwind SaaS
4.2×faster document processing
We drowned in scanned contracts. The Ozon team shipped an extraction pipeline with human review that reads, classifies and structures every document into our system, with a confidence score and a full audit trail. What took a team two days now runs in hours, and legal trusts it because they can see exactly why every field was filled the way it was.
Daniel Petrov
COO, Meridian Capital
+31%forecast accuracy
Ozon rebuilt our reporting stack and put a natural-language layer on top of it. Our commercial team now asks questions in plain English and gets answers grounded in the actual numbers, and the demand model they trained lifted our forecast accuracy by nearly a third. What used to be a Monday-morning spreadsheet ritual is now a live dashboard nobody argues with.
Elena Ruseva
VP Data, Kestrel Retail
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