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AI Solutions for Food Industry

  • 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 food industry 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 the food industry?

AI for the food industry is the application of machine learning, computer vision and optimization algorithms to food production, distribution and service operations - from demand forecasting and dynamic menu pricing to kitchen automation and delivery route optimization. Unlike traditional restaurant and food systems that rely on manual inventory counts and static pricing, AI-powered FoodTech platforms learn from sales patterns, external signals (weather, events, holidays) and real-time operational data to optimize every step from procurement to plate. Common AI food industry project types include demand forecasting for perishable inventory, dynamic pricing engines, computer vision for food safety inspection, delivery optimization, kitchen workflow automation and customer personalization.
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 restaurant chains, food delivery platforms and CPG companies. aligned with ISO 27001.

What is AI for the food industry?
AI for the food industry is the application of machine learning, computer vision and optimization algorithms to food production, distribution and service operations - from demand forecasting and dynamic menu pricing to kitchen automation and delivery route optimization. Unlike traditional restaurant and food systems that rely on manual inventory counts and static pricing, AI-powered FoodTech platforms learn from sales patterns, external signals (weather, events, holidays) and real-time operational data to optimize every step from procurement to plate. Common AI food industry project types include demand forecasting for perishable inventory, dynamic pricing engines, computer vision for food safety inspection, delivery optimization, kitchen workflow automation and customer personalization.

Custom AI for food industry vs vendor AI platforms

Factor Custom AI (Pharos Production) Vendor Platforms (Afresh, BlueCart, etc.)
Demand forecasting Models trained on your menu, location mix, customer base and local events Generic restaurant forecasting across aggregated data
Pricing optimization Custom elasticity models per item category and customer segment Standard dynamic pricing with limited menu-level control
Inventory integration Deep integration with your POS, inventory, supplier and kitchen systems Pre-built connectors for supported POS platforms only
Delivery optimization Custom routing for your delivery zones, driver fleet and service promises Generic last-mile optimization, limited constraint modeling
Food safety AI Computer vision trained on your kitchen environments and compliance requirements Standard food safety checklists, limited visual inspection
Cost structure One-time development + self-hosted optimization engine Per-location or per-order pricing that scales with volume
Data ownership All sales, inventory and customer data stays in your infrastructure Data processed on vendor servers, aggregated across clients

Pharos Production recommends custom food industry AI for chains with 20+ locations, delivery platforms processing 10K+ daily orders or CPG companies managing perishable supply chains. Vendor platforms work for single-location restaurants needing basic inventory management.

How to choose an AI development company for the food industry

1 Food industry domain expertise alongside ML engineering. The team must understand perishable inventory dynamics, food safety regulations (FDA, FSMA), restaurant operations and delivery logistics - not just model training.
2 Demand forecasting experience for perishable goods. Ask for case studies showing waste reduction and stockout rate improvements on perishable inventory with daily retraining cycles.
3 POS and kitchen system integration track record. The team should have production experience with Toast, Square, Oracle MICROS or equivalent restaurant technology stacks.
4 Real-time delivery optimization capability. Food delivery has a 30-minute freshness window. The team needs experience with real-time routing that balances speed, driver utilization and food quality.
5 Computer vision for food safety and quality. Automated inspection of food prep, storage temperatures and packaging requires specialized vision models trained on food industry environments.
6 A/B testing infrastructure for pricing and menu optimization. Dynamic pricing and menu recommendation changes require controlled experimentation. The team should build statistical testing frameworks that measure impact on both revenue and customer satisfaction.

Pharos Production - Get your FoodTech AI estimate in 48h. Share your demand forecasting, dynamic pricing or kitchen automation requirements - our AI team will deliver a detailed estimate with architecture recommendations. Get a project estimate.

Reviews

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

Based on 8 verified client reviews

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
5 out of 5 stars
AI

Highly responsive team with strong communication and professionalism.

Imad Jazzar
5 out of 5 stars
AI

Innovative AI solutions that supported scaling.

Ryan Florin
5 out of 5 stars
AI

Strong domain expertise and agile delivery.

Joshua Hernandez
5 out of 5 stars
AI

Aligned with manufacturing constraints and workflows.

Brian Hess
5 out of 5 stars
AI

Built scalable app aligned with hybrid workflows and user needs.

Tyler Servin
5 out of 5 stars
AI

Fast delivery with strong collaboration.

Charlotte Preston

Measurable results

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

AI for Food Industry Benchmark 2026

Proprietary research based on AI-powered food industry projects delivered by Pharos Production. Dataset covers demand forecasting, dynamic pricing and delivery optimization deployments. Methodology (Pharos Verified Delivery): aggregated delivery metrics with production monitoring data. Full report available on request.

20-35% Reduction in food waste through AI forecasting
8-15% Revenue increase from dynamic pricing
< 2% Stockout rate for perishable inventory
$40K-$350K+ Project cost range depending on complexity
25% Improvement in delivery route efficiency
10 weeks Average time to production-ready MVP

AI Solutions for Food Industry trends shaping 2026

Key technology shifts that impact how Pharos Production architects ai solutions for food industry software for clients.

Agentic AI for Restaurant Operations

Autonomous AI agents manage end-to-end restaurant workflows - from automated supplier ordering based on demand forecasts to kitchen prep scheduling, staff allocation and customer communication. Pharos Production builds restaurant operation agents with human-in-the-loop controls for procurement above threshold amounts.

Computer Vision for Food Quality Control

AI-powered camera systems inspect food preparation, plating consistency and storage compliance in real time. Models detect contamination risks, temperature violations and portioning errors before food reaches customers. Pharos Production deploys kitchen vision systems integrated with HACCP compliance workflows.

Personalized Menu Recommendations

ML models analyze order history, dietary preferences, time-of-day patterns and basket composition to suggest menu items that maximize both customer satisfaction and average order value. Pharos Production builds recommendation engines integrated with POS and mobile ordering platforms.

AI-Powered Ghost Kitchen Optimization

Multi-brand ghost kitchens use AI to optimize menu overlap, ingredient sharing and kitchen station allocation across virtual brands. Demand forecasting per brand reduces waste while maximizing kitchen throughput. Pharos Production builds ghost kitchen management AI with real-time order routing and prep scheduling.

Predictive Maintenance for Kitchen Equipment

IoT sensors and ML models predict commercial kitchen equipment failures (ovens, refrigeration, HVAC) 2-4 weeks before breakdown. Proactive maintenance prevents costly service disruptions during peak hours. Pharos Production builds equipment monitoring systems integrated with service provider dispatch.

AI-Driven Sustainability and Waste Tracking

ML models track food waste by source (overproduction, spoilage, customer returns), identify waste reduction opportunities and generate sustainability reports for ESG compliance. Pharos Production builds waste analytics platforms with automated donation routing for surplus food.

Key takeaways
  • AI for the food industry requires ML engineering combined with deep understanding of perishable supply chains, food safety regulations and restaurant operations.
  • The global AI in food and beverage market is projected to reach $43.4 billion by 2029 at 45.2% CAGR. 55% of restaurant chains are investing in AI for demand forecasting and waste reduction.
  • Custom AI enables demand models trained on your menu and locations, pricing optimization per customer segment and delivery routing for your specific zones and constraints.
  • A demand forecasting MVP starts from $40,000-$100,000 and takes 10 weeks. Full FoodTech AI platforms with pricing and delivery optimization range from $150,000 to $350,000+.
  • Every Pharos Verified Delivery food industry AI sprint includes waste reduction benchmarking, POS integration testing and A/B testing framework setup for pricing experiments.
Limitations and considerations
  • Demand forecasting for perishable inventory needs 6-12 months of POS data to capture seasonal patterns, holiday effects and local event impacts. New locations start with chain-level averages until sufficient local history accumulates.
  • Dynamic pricing sensitivity varies by market and customer segment. Price-conscious markets reject visible menu price changes. A/B testing is mandatory before full rollout to measure elasticity without damaging brand perception.
  • Computer vision food safety inspection requires controlled lighting and camera placement in kitchen environments. Retrofit installations in existing kitchens add hardware costs and may require kitchen workflow adjustments.
  • Delivery route optimization depends on real-time driver location and traffic data. Markets with poor GPS coverage or limited traffic data reduce optimization accuracy by 10-15% compared to well-mapped urban areas.

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.

$17,000 - $40,000
Popular choice
Production
Production AI system

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

$40,000 - $90,000
Enterprise
Enterprise AI platform

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

$80,000 - $180,000

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
19+ industry awards

FAQ

Last updated:

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.

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    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.

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

    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.

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

    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