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AI Solutions for E-Commerce

Pharos Production builds AI-powered e-commerce solutions that drive revenue growth through personalization at scale. From recommendation engines that increase average order value by 15-30% to dynamic pricing systems and demand forecasting models, we deliver AI that converts browsers into buyers and optimizes every step of the customer journey.

  • 90+ engineers
  • 13+ years in business
  • 70+ apps delivered

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SOC 2 Type II GDPR ISO 27001 NDA Protected

Aligned with these frameworks. Audit reports and certifications available on request.

Key facts: Pharos Production delivers custom ai solutions for e-commerce since 2013. Team of 90+ engineers from Las Vegas and Kyiv. 70+ applications delivered for 200+ clients. Rated 5/5 on Clutch (2026). aligned with ISO 27001. Last reviewed: June 2026. Editorial policy.

What is AI for e-commerce?

AI for e-commerce is the application of machine learning, natural language processing and computer vision to online retail - from product recommendation engines and dynamic pricing to visual search and demand forecasting. Unlike rule-based merchandising that relies on manual curation, AI-powered e-commerce systems learn from customer behavior in real time to personalize every touchpoint of the shopping experience. Common AI e-commerce project types include recommendation engines, dynamic pricing systems, demand forecasting models, visual and semantic product search, conversational shopping assistants, fraud detection and inventory optimization.
Dmytro Nasyrov - Founder and CTO of Pharos Production

Reviewed by Dmytro Nasyrov

Founder and CTO

23+ years in software development. PhD in AI. Led AI projects for e-commerce platforms, marketplaces and D2C brands. aligned with ISO 27001.

What is AI for e-commerce?
AI for e-commerce is the application of machine learning, natural language processing and computer vision to online retail - from product recommendation engines and dynamic pricing to visual search and demand forecasting. Unlike rule-based merchandising that relies on manual curation, AI-powered e-commerce systems learn from customer behavior in real time to personalize every touchpoint of the shopping experience. Common AI e-commerce project types include recommendation engines, dynamic pricing systems, demand forecasting models, visual and semantic product search, conversational shopping assistants, fraud detection and inventory optimization.

Custom AI for e-commerce vs SaaS recommendation platforms

Factor Custom AI (Pharos Production) SaaS Platforms (Algolia, Nosto, Dynamic Yield)
Personalization depth Models trained on your full customer journey data Limited to on-site behavior, no offline data
Catalog handling Custom models for any catalog size (10K to 10M+ SKUs) Performance degrades above platform limits
Revenue attribution Full A/B testing with revenue attribution per model Platform-reported metrics, limited transparency
Pricing optimization Custom dynamic pricing with business-specific guardrails Basic price testing, no real-time optimization
Search quality Semantic search with visual and natural language understanding Keyword-based with basic synonym matching
Integration Deep integration with your ERP, PIM, warehouse and CRM Pre-built connectors, limited custom workflows
Cost at scale One-time development + hosting, no per-request fees Per-request or per-session pricing, costs scale with traffic

Pharos Production recommends custom AI for e-commerce businesses with 10K+ SKUs, $10M+ annual revenue or complex personalization needs across multiple channels. SaaS platforms work well for smaller stores needing quick recommendation widgets.

How to choose an AI company for e-commerce

1 E-commerce domain expertise plus ML engineering. The team must understand product catalogs, customer journeys, conversion funnels and inventory systems - not just model training.
2 Proven revenue impact from AI. Ask for case studies showing measurable lift in conversion rate, average order value or customer lifetime value from deployed AI systems.
3 Real-time inference capability. Recommendation and pricing models must respond in under 100ms at peak traffic. The team needs experience with low-latency ML serving at scale.
4 A/B testing methodology for AI models. Every AI feature should be deployed behind feature flags with statistical significance testing and revenue attribution.
5 Cold start and data sparsity solutions. New users and new products have no interaction data. The team should demonstrate hybrid approaches that handle cold start gracefully.
6 Peak traffic engineering. E-commerce AI must handle Black Friday traffic spikes (10-50x normal) without degradation. Ask about auto-scaling, caching and graceful degradation strategies.

Pharos Production - Get your e-commerce AI estimate in 48h. Share your personalization, pricing or search requirements - our AI team will deliver a detailed estimate with expected revenue impact projections. Get a project estimate.

Reviews

Independent reviews from Clutch, GoodFirms and Google - verified client feedback on our software projects

Based on 10 verified client reviews

5 out of 5 stars
AI

Highly adaptable team with strong ownership and excellent communication delivering effective solutions.

Molly Lavie
5 out of 5 stars
AI

Strong full-cycle development execution.

Anonymous
5 out of 5 stars
AI

Highly responsive team with strong communication and professionalism.

Imad Jazzar
5 out of 5 stars
AI

Built scalable app aligned with hybrid workflows and user needs.

Tyler Servin
5 out of 5 stars
AI

Delivered reliable frontend solutions with strong performance and timely execution.

Robin Kim
5 out of 5 stars
AI

Stable platform delivery with minimal disruption.

Amber Caruso
5 out of 5 stars
AI

Our experience working with Pharos Production Inc. was very positive. From the beginning, their team demonstrated a clear understanding of our requirements and took the time to properly analyze our business processes before starting development. Communication remained smooth and transparent throughout the project.

Zoeb Khan
5 out of 5 stars
AI

Delivered ahead of schedule with efficiency gains.

Russell Searce
5 out of 5 stars
AI

Delivered Web3, NFT, and smart contract functionality successfully.

Alex Gurych
5 out of 5 stars
AI

Initial strong start but later issues with deadlines, communication, and transparency.

Kenneth Phough

Measurable results

70+ Applications delivered
200+ Clients worldwide
5/5 Clutch rating (2026)
13+ Years in production

AI for E-Commerce Benchmark 2026

Proprietary research based on AI-powered e-commerce projects delivered by Pharos Production. Dataset covers recommendation engines, dynamic pricing and demand forecasting systems. Methodology (Pharos Verified Delivery): aggregated delivery metrics with A/B test results. Full report available on request.

15-30% Average order value increase from recommendations
< 100ms Recommendation response time at peak traffic
8-12% Margin improvement from dynamic pricing
$40K-$350K+ Project cost range depending on complexity
10 weeks Average time to production-ready MVP
92% Demand forecast accuracy for top SKUs

AI Solutions for E-Commerce trends shaping 2026

Key technology shifts that impact how Pharos Production architects ai solutions for e-commerce software for clients.

Conversational Commerce with AI Agents

AI shopping assistants now handle product discovery, comparison, sizing advice and checkout in natural conversation. Conversion rates for AI-guided sessions are 3-5x higher than self-service browse. Pharos Production builds conversational commerce agents with RAG-powered product knowledge and real-time inventory awareness.

Visual Search and Image-Based Shopping

Customers photograph products they want and AI finds exact or similar items in your catalog. Visual search handles the "I want something like this" intent that text search cannot capture. Pharos Production builds visual search with CLIP-based embeddings that match across colors, styles and categories.

Hyper-Personalization with Real-Time Signals

AI personalizes every element - product recommendations, prices, content, email timing - using real-time behavioral signals. Moving beyond segments to individual-level personalization delivers 5-8x ROI over batch approaches. Pharos Production builds real-time personalization engines processing 100K+ events per second.

AI-Powered Demand Forecasting

ML models predict demand at SKU level by combining sales history, seasonality, promotions, weather and competitor pricing. Accurate forecasting reduces overstock by 20-30% and stockouts by 40-50%. Pharos Production builds multi-signal forecasting models with automated retraining.

Dynamic Pricing Optimization

Real-time pricing algorithms adjust prices based on demand elasticity, competitor prices, inventory levels and customer segments. AI pricing increases margin by 8-12% while maintaining competitive positioning. Pharos Production implements pricing AI with business guardrails and regulatory compliance.

Generative AI for Product Content

LLMs generate product descriptions, SEO content, email copy and ad creative from product attributes and images. This reduces content creation costs by 80% while maintaining brand voice. Pharos Production builds content generation pipelines with brand style enforcement and quality scoring.

Key takeaways
  • AI for e-commerce drives measurable revenue through personalized recommendations (15-30% AOV lift), dynamic pricing (8-12% margin gain) and demand forecasting (92% accuracy).
  • The global AI in retail market is projected to reach $85.07 billion by 2032 at 31.8% CAGR. 79% of top-performing retailers already use AI personalization.
  • Custom AI eliminates per-request SaaS fees and enables deep personalization across your full customer journey - online, offline and cross-channel.
  • A recommendation engine MVP starts from $40,000-$80,000 and takes 10 weeks. Full AI-powered commerce platforms range from $150,000 to $350,000+.
  • Every Pharos Verified Delivery e-commerce AI sprint includes A/B testing, revenue attribution and peak traffic load testing.
Limitations and considerations
  • Recommendation engines require minimum 10,000 user interactions before collaborative filtering produces meaningful results. New stores with thin behavioral data must start with content-based approaches.
  • Dynamic pricing algorithms need 8-12 weeks of price elasticity data collection before optimization converges. Premature deployment may cause margin erosion or customer trust damage.
  • AI personalization accuracy depends on product catalog data quality. Missing attributes, inconsistent categories and sparse product descriptions reduce recommendation relevance by 20-30%.
  • Peak traffic scaling (Black Friday, flash sales) requires load testing and pre-provisioned infrastructure. AI inference latency under 10x normal traffic must be validated before seasonal events.

Pharos Production - Ready to build your product? From architecture to production - share your requirements and our engineering team will deliver a detailed estimate within 48 hours. Start Your Project.

Choose your cooperation model

Pilot
AI discovery and PoC

Feasibility study, prototype on your data and integration roadmap in four to eight weeks.

$16,000 - $35,000
Popular choice
Production
Production AI system

Full model development, API layer, cloud deployment and MLOps with monitoring.

$30,000 - $70,000
Enterprise
Enterprise AI platform

Multi-model architecture, custom data infrastructure, compliance and hybrid or on-prem delivery.

$75,000 - $170,000

Prices vary based on project scope, complexity, timeline and requirements. Contact us for a personalized estimate.

Or select the appropriate interaction model

Request staff augmentation

Need extra hands on your software project? Our developers can jump in at any stage – from architecture to auditing – and integrate seamlessly with your team to fill any technical gaps.

Outsource your project

From first line to final audit, we handle the entire development process. We will deliver secure, production-ready software, while you can focus on your business.

Comparison of engagement models at Pharos Production
Model Best for Team setup Budget range
Staff Augmentation Existing teams needing extra engineers at any project stage 1-2 weeks From $5,000/month
Project Outsourcing Full-cycle development from idea to production launch 1-2 weeks $10,000-$80,000+

An approach to the development cycle

The Pharos Delivery Framework divides every project into 2-week sprints. After each sprint there is a retrospective of the work done, planning for the next sprint, a report of the work done and a plan for the next sprint. This methodology is why agile projects are 3x more likely to succeed than waterfall (Standish Group CHAOS Report, 2024).
  1. Team Assembly

    Our company starts and assembles an entire project specialists with the perfect blend of skills and experience to start the work.

  2. MVP

    We’ll design, build, and launch your MVP, ensuring it meets the core requirements of your software solution.

  3. Production

    We’ll create a complete software solution that is custom-made to meet your exact specifications.

  4. Ongoing

    Continuous Support

    Our company will be right there with you, keeping your software solution running smoothly, fixing issues, and rolling out updates.

187+ technologies

Technologies, tools and frameworks we use

Our engineers work with 187+ technologies across blockchain, backend, frontend, mobile and DevOps - chosen for production reliability and performance.

Frameworks

Backend Frameworks 8

Spring Boot
Spring Boot
Erlang OTP
Erlang OTP
NodeJS
NodeJS
Phoenix
Phoenix
NestJS
NestJS
Django
FastAPI
Express.js

Front End Frameworks 8

React
React
Next.JS
Next.JS
Svelte
Svelte
Angular
Angular
Vue.js
Remix
Astro
Nuxt.js

AI and Machine Learning

LLM Providers 8

OpenAI GPT
Anthropic Claude
Google Gemini
Meta Llama
Mistral AI
Cohere
Ollama
xAI Grok

AI Frameworks 15

LangChain
LangGraph
CrewAI
AutoGen
Hugging Face
PyTorch
TensorFlow
scikit-learn
LlamaIndex
Keras
XGBoost
LightGBM
OpenCV
spaCy
ONNX Runtime

Vector Databases 7

Pinecone
Weaviate
Qdrant
Chroma
pgvector
Milvus
FAISS

MLOps and Infrastructure 11

MLflow
Weights & Biases
DVC
Kubeflow
AWS SageMaker
Azure ML
Google Vertex AI
NVIDIA Triton
Airflow
Ray Serve
vLLM

AI Agent Tools 4

OpenAI Agents SDK
Claude MCP
Semantic Kernel
Haystack

Blockchains

Private and Public Blockchains 33

Ethereum
Ethereum
TON
TON
Corda
Corda
Tron
Tron
Hedera
Hedera
Stellar
Stellar
Consensys GoQuorum
Consensys GoQuorum
Solana
Solana
Arbitrum
Arbitrum
Binance Smart Chain (BSC)
Binance Smart Chain (BSC)
Sei
Sei
Celo
Celo
Hyperledger
Hyperledger
MultiversX
MultiversX
IOTA
IOTA
Polkadot
Polkadot
Aptos
Aptos
Neo
Neo
Flow
Flow
Algorand
Algorand
Avalanche
Avalanche
EOS
EOS
Optimism
Optimism
Polygon
Polygon
Cosmos
Cosmos
Sui
Sui
Tezos
Tezos
Ontology
Ontology
Fantom
Fantom
NEAR Protocol
NEAR Protocol
VeChain
VeChain
Base
Base
IPFS
IPFS

Cloud Blockchain Solutions 4

Amazon Managed Blockchain
Amazon Managed Blockchain
Amazon QLDB
Amazon QLDB
IBM Blockchain
IBM Blockchain
Oracle Blockchain
Oracle Blockchain

DevOps

DevOps Tools 15

Kubernetes
Kubernetes
Terraform
Terraform
Docker
Docker
Istio
Istio
Prometheus
Prometheus
Grafana
Grafana
Jenkins
Jenkins
ArgoCD
ArgoCD
Ansible
Ansible
GitHub Actions
GitLab CI
Pulumi
Datadog
New Relic
Vault

Clouds

Clouds 6

Amazon Web Services
Amazon Web Services
Azure
Azure
Google Cloud
Google Cloud
Cloudflare
Vercel
DigitalOcean

Databases

Databases 15

PostgreSQL
PostgreSQL
MySQL MariaDB
MySQL MariaDB
Redis
Redis
Cassandra
Cassandra
Neo4J
Neo4J
MongoDB
MongoDB
Elasticsearch
Elasticsearch
Solr
Solr
Ignite
Ignite
ClickHouse
TimescaleDB
DynamoDB
Supabase
CockroachDB
ScyllaDB

Brokers

Event and Message Brokers 7

Kafka
Kafka
RabbitMQ
RabbitMQ
Flink
Flink
Apache Pulsar
Amazon SQS
Amazon SNS
NATS

Tests

Test Automation Tools 6

Postman
Postman
Appium
Appium
Cucumber
Cucumber
Selenium
Selenium
JMeter
JMeter
Cypress
Cypress

Programming

UI/UX

UI/UX Design Tools 12

Figma
Figma
Zeplin
Zeplin
InVision
InVision
Sketch
Sketch
Miro
Miro
Marvel
Marvel
Balsamiq
Balsamiq
Photoshop
Photoshop
Illustrator
Illustrator
XD
XD
After Effects
After Effects
Corel Draw
Corel Draw
Trusted & Certified

Partnerships & Awards

Recognized on Clutch, GoodFirms and The Manifest for software engineering excellence

  • Partner1
  • Partner2
  • Partner3
  • Partner4
  • Partner5
20+ industry awards

FAQ

Last updated: Reviewed by: Dmytro Nasyrov (Founder and CTO)

Quick answers to common questions about custom software development, pricing, process and technology.

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    Pharos Production has been in business since 2013, with over 13 years of experience in custom software development. During this time, we have delivered over 70 applications for 200+ clients across 18 industries, including FinTech, healthcare, crypto and e-commerce. We are rated 5/5 on Clutch based on 73 verified reviews (2026).

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    Pharos Production provides six core service categories: Software Development (mobile apps, web platforms, database design, UI/UX), Blockchain Development (smart contracts, DeFi, tokenization on Ethereum, Solana, TON and other chains), Software Security (code audits, penetration testing, smart contract audits), Software Consulting (architecture design, MVP validation, startup consulting) and Software Testing and QA (manual, automation, performance and regression testing).

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    Pharos Production is headquartered in Las Vegas, Nevada, USA (5348 Vegas Dr, Las Vegas, NV 89108), with an engineering office in Kyiv, Ukraine (44-B Eugene Konovalets Str. Suite 201, Kyiv 01133). We work with clients worldwide and provide remote collaboration across all time zones. Visit our contact page for directions and scheduling options.

  • Copy link Copies a direct link to this answer to your clipboard.

    Pharos Production has a team of 90+ engineers, including software developers, blockchain specialists, QA engineers, DevOps experts, UI/UX designers, project managers and solution architects. Our founder, Dr. Dmytro Nasyrov, holds a PhD in Artificial Intelligence and leads the technical direction of all projects.

  • Copy link Copies a direct link to this answer to your clipboard.

    We serve a wide range of clients, from startups and product companies to mid-sized enterprises and large institutions. Our clients include crypto exchanges, FinTech providers (like Pleenk), healthcare organizations, sportsbook operators (like Pro Gambling), e-commerce platforms and SaaS companies. Pharos Production has worked with 200+ clients across 18 industries since 2013, adapting engagement models to match each client’s stage, whether it is MVP validation for a startup or enterprise-scale development for an established business.

  • Copy link Copies a direct link to this answer to your clipboard.

    A custom software development company is a firm that designs, builds and maintains software tailored to a specific business’s needs, as opposed to off-the-shelf products. Custom software addresses unique workflows, integrations and scalability requirements that generic tools cannot. According to Grand View Research (2024), the global custom software development market is valued at over $35 billion and is projected to grow at a 22.3% CAGR through 2030. Pharos Production is a custom software development company founded in 2013, with a team of 90+ engineers delivering solutions across blockchain, FinTech, healthcare and 15 other industries.

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    Custom software development costs vary based on project scope and complexity. At Pharos Production, typical project ranges are: MVP development ($10,000-$25,000), suitable for startups validating a product idea; full-fledged production ($25,000-$50,000), for established businesses scaling a proven concept; and full-cycle development ($50,000-$80,000+), for complex enterprise-grade systems. These ranges include architecture design, development, QA testing and deployment. Final pricing depends on technology stack, number of integrations and engagement model (staff augmentation, dedicated team or project outsourcing).

  • Copy link Copies a direct link to this answer to your clipboard.

    Development timelines depend on scope and complexity. At Pharos Production, a typical MVP takes 2-4 months, a production-ready application takes 4-8 months and a complex enterprise system can take 8-12+ months. We use an agile methodology with 2-week sprints, delivering working increments after each sprint. Every sprint includes a retrospective, progress report and planning session for the next iteration. This approach ensures transparency and allows businesses to launch faster by prioritizing high-impact features first. Get a timeline estimate for your project.

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    Pharos Production serves 18 industries: Crypto, Web3 and Blockchain (Kimlic, GridTradeX, NextCheck), Sports and Sportsbooks, Casino and Gambling (Gambit Stream, Lucky Bets), FinTech, Healthcare, E-Commerce, Insurance, Energy and Utilities, Education, Telecom, Media and Entertainment, Logistics and Transportation (Taxi Aggregator), Marketing, Banking, Construction and Real Estate, Agriculture and Travel. Our deepest expertise is in FinTech, blockchain and healthcare, where we have delivered compliance-ready platforms (HIPAA, PCI DSS, GDPR) and high-load systems handling thousands of concurrent users. For the latest industry insights, read our guides on FinTech trends in 2026 and the Web3 technology stack.

  • Copy link Copies a direct link to this answer to your clipboard.

    Hiring a software development company offers faster time-to-market, lower upfront costs and access to specialized expertise without long-term employment commitments. According to Deloitte’s 2024 Global Outsourcing Survey, 57% of companies outsource software development to access skills they cannot hire internally.

    Factor In-house team Software development company
    Time to assemble 3-6 months (recruiting + onboarding) 1-2 weeks
    Upfront cost High (salaries, benefits, equipment) Lower (project-based pricing)
    Specialized expertise Limited to who you can hire locally Access to 90+ engineers across blockchain, AI, FinTech
    Scalability Slow (each new hire takes months) Fast (scale up or down per sprint)
    Long-term commitment Full-time employment contracts Flexible engagement models
    Risk High if key engineers leave Company ensures continuity and knowledge transfer

    For businesses that need blockchain, AI or high-load architecture expertise, outsourcing to a specialized firm like Pharos Production reduces risk and accelerates delivery.

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    Pharos Production focuses on mid-to-large custom software projects with budgets starting at $10,000. We do not take on template-based websites, WordPress theme customization, or short-term contracts under one month. We also do not provide non-technical staffing (marketing, sales or design-only roles). Our strongest fit is blockchain, FinTech and healthcare projects where security, compliance and high-load architecture are critical. For smaller projects or MVPs under $10,000, we recommend exploring freelance platforms or no-code tools as a more cost-effective starting point.

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    We use agile with 2-week sprints because it reduces the risk of building features that miss the mark. Each sprint ends with a working demo, a retrospective and a plan for the next iteration.

    This means clients see progress every 14 days and can adjust priorities based on real results, not assumptions. According to the Standish Group CHAOS Report (2024), agile projects are 3x more likely to succeed than waterfall projects. We chose this approach after years of experience showing that rigid, fixed-scope contracts lead to scope creep, missed deadlines and products that do not match market needs by launch day.

  • Copy link Copies a direct link to this answer to your clipboard.

    Custom development is not the right choice in every situation. You should not hire a custom software company if: your problem is fully solved by an existing SaaS product (e.g. Shopify for e-commerce, Salesforce for CRM); your budget is under $10,000 and timeline is under 4 weeks; you need a simple landing page or marketing website (WordPress or Webflow is faster and cheaper); or you are still validating the idea and have not spoken to potential users yet.

    In these cases, off-the-shelf tools or no-code platforms offer better ROI. Custom development makes sense when you need unique workflows, regulatory compliance, high-load architecture or competitive differentiation that packaged software cannot provide.

  • Copy link Copies a direct link to this answer to your clipboard.

    Here are three anonymized examples from our recent delivery history:

    FinTech startup - payment platform (MVP)
    Scope: mobile app + backend API with bank-grade encryption. Team: 4 engineers, 1 QA. Timeline: 10 weeks. Budget: $38,000. Result: launched on schedule, processed $2M+ in transactions within the first quarter.

    Healthcare provider - patient portal (Full product)
    Scope: HIPAA-aligned web platform with EHR integration, appointment scheduling and telemedicine. Team: 6 engineers, 1 DevOps, 2 QA. Timeline: 6 months. Budget: $120,000. Result: 15,000+ active patients, zero compliance violations in two annual audits.

    Crypto exchange - trading engine (Complex)
    Scope: high-load matching engine handling 50,000+ orders per second, multi-chain wallet infrastructure on Ethereum and Solana. Team: 8 engineers, 2 QA, 1 security auditor. Timeline: 11 months. Budget: $340,000. Result: 99.97% uptime, passed three independent security audits.

    See more projects: NoMoreBets, Pulse, Sagas, Gambit Stream and Pleenk. For the full portfolio, visit our case studies. Learn more about the technology behind these projects in our guide to stablecoins and crypto infrastructure.

Dmytro Nasyrov, Founder and CTO at Pharos Production
Dmytro Nasyrov Founder & CTO Let’s work together!

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Our offices

Headquarters in Las Vegas, Nevada. Engineering office in Kyiv, Ukraine.

Las Vegas, United States

Headquarters PST (UTC-8)
5348 Vegas Dr, Las Vegas, Nevada 89108, United States

Kyiv, Ukraine

Engineering office EET (UTC+2)
44-B Eugene Konovalets Str. Suite 201, Kyiv 01133, Ukraine