Zentavor is a technology company specializing in artificial intelligence, machine learning and large-scale data platforms for enterprises. We help organizations accelerate digital transformation through applied AI integrated into real business processes — and deliver measurable business impact

What you get with Zentavor

60+ experts across AI, ML & Data Engineering

5+ years of enterprise delivery

Zentavor

A senior delivery partner that can take you from discovery and PoC to production rollout and long-term support. We combine AI/ML engineering with modern data infrastructure to build solutions that work in real enterprise workflows

Dozens of projects for major international companies

faster time‑to‑production

45%

lower operational workload

30%

business outcomes

measurable

predictable delivery & governance

37%

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Typical advantages our clients value:

Tell us your goals — we’ll propose the right delivery model and a realistic roadmap

About

Applied AI integrated into real business processes

Enterprise delivery: from PoC to production rollout

AI Agents & LLM systems: RAG, semantic search, automation

ML & Recommenders: personalization, forecasting, optimization

Data Platforms: DWH, ETL/ELT, BI, real‑time analytics

Zentavor builds solutions step by step — from diagnostics and architecture to implementation and production-scale development.

This approach enables fast MVP launches, reduces risks, controls total cost of ownership, and gradually expands functionality without compromising stability.

Our goal is not just to implement technology, but to create a sustainable data and AI platform that helps businesses grow, make decisions faster, and scale confidently in a rapidly evolving digital environment.

Our focus

We turn AI from experiments into stable, production-ready solutions integrated into existing workflows and governance

Lack of applied expertise in production AI

Access senior ML/LLM and Data Engineering expertise without lengthy hiring cycles — and scale up/down when needed

Hiring and scaling senior AI/Data teams takes months

Proven delivery methodology, ready components and clear milestones help keep timelines predictable and measurable

Tight delivery timelines and uncertain scope

We build the data foundation (DWH/ETL/quality) required for AI to deliver consistent, explainable results

Fragmented data, technical debt and data quality issues

We combine AI, ML and modern data infrastructure to deliver business-critical systems — not just prototypes

AI Agents for enterprise automation

Autonomous agents that analyze context, make decisions and execute workflows across support, sales and internal operations

Machine Learning
& applied AI

Recommendation engines, forecasting, support automation, personalization and decision optimization at scale

Semantic
search & RAG

Enterprise search and knowledge retrieval that provides accurate answers with sources and reduces expert workload

Data platforms
& analytics

DWH, ETL/ELT pipelines, data marts and BI dashboards for a single source of truth and KPI monitoring

MLOps & production readiness

Monitoring, evaluation, governance and continuous improvement to keep models reliable in production

End‑to‑end
engineering

Discovery, architecture, development, integration, deployment and long‑term support with SLA-backed deliverables

Two engagement models to accelerate AI adoption and achieve predictable business results

Why clients choose us

International expertise and best engineering practices

Transparent pricing and governance

Ability to assemble a complete cross‑functional team

Focus on business outcomes and SLA-backed deliverables

Full-cycle delivery: analysis → architecture → development → rollout → support

Turnkey solution within tight deadlines

Outsourcing (end‑to‑end delivery)

Flexible terms aligned with your roadmap

Scale quickly without long hiring cycles

Senior ML/LLM/Data engineers join your team

Staff augmentation

A predictable, end-to-end process — from diagnostics to production operation

Align on business goals, assess data readiness and existing architecture, select the optimal AI approach

Diagnostics & analysis

Define target architecture (AI agents / ML / DWH), decompose tasks, build roadmap and success metrics

Solution design

Develop models and services, prepare datasets, build APIs and integration modules

Development & training

QA, load testing and integration with CRM/ERP/DWH and internal services

Testing & integration

Monitor quality, optimize and continuously improve; provide technical support and long-term evolution

Launch & maintenance

Design dashboards for speed and clarity: the right granularity, consistent visuals, and decision‑ready layouts

UX and interface design

Monitor pipelines and BI performance, handle updates, and continuously improve data quality and adoption

Technical support

Build and validate dashboards, set refresh schedules, create automated distributions, and implement alerts for anomalies

Dashboards, reports, and alerts

Banking & Fintech

Automation & analytics

–20–40% in operational risks and manual operations

Using customer data, analytics, and AI models helps improve personalization, increase conversion, and optimize assortments without increasing operating costs.

Retail & E-commerce

Personalization & growth

+5–15% revenue growth through data and AI approaches

Using customer data, analytics, and AI models helps improve personalization, increase conversion, and optimize assortments without increasing operating costs.

Logistics & Operations

Operational optimization

–10–25% in operating costs

Process and data quality analytics help identify bottlenecks, reduce losses, improve planning, and enhance control over logistics and operational chains.

Enterprise use cases across industries where scale, reliability and compliance matter

Note: Estimates depend on the number of data sources, domains, update requirements, the security model, and the maturity level of existing data

A single, reliable center of truth for business health and KPI dynamics — in real time, not “last quarter”

Independent control tool for leadership

Visualize millions of rows and drill down in seconds. Clear design helps teams make decisions confidently

Interactive dashboards anyone can use

Reduce costs and time spent building reports, eliminate manual steps, and lower the influence of human error

Operational efficiency

Spot patterns in data and validate hypotheses quickly — so teams can iterate and improve performance continuously

Faster hypothesis testing

Share your reporting pain points, data sources, and the key decisions you want BI to support. We’ll propose the target architecture, pilot scope, and delivery plan

Email: info@zentavor.ai

Share your goals, data landscape and constraints — we’ll propose the most effective combination of AI agents, ML and data platforms and a realistic delivery plan

What to share to get started

Which domains matter most (sales, finance, marketing, operations)

Current sources (CRM/ERP, web analytics, ad platforms, finance systems)

Top KPI conflicts and reporting bottlenecks

Refresh needs (daily / hourly) and data latency expectations

Security and access model (roles, departments, compliance)