Why build on the cloud with Nexterse?
Our team builds and migrates cloud platforms for companies across industries and regions. We choose the cloud model and services based on business logic, scale, compliance constraints, and long-term run cost.
We use our ADLC alongside a well-architected cloud process. We define the workload, prepare the data and infrastructure, set evaluation and cost criteria, and add monitoring. This reduces rework and makes it easier to move AI features from PoC to production.
30% less time to market
with cloud-native development
40% lower infrastructure cost
through cloud optimization & FinOps
99.9% uptime and availability
with resilient cloud architecture
Cloud development services
Cloud consulting & assessment
Our cloud architects assess your current infrastructure, applications, and goals before any migration or build starts. We define the target cloud strategy, estimate total cost of ownership, and identify the workloads that benefit most from the cloud. If AI is part of the plan, we map where managed AI services and data pipelines fit into the architecture from day one.
- Assess current infrastructure, workloads, and dependencies
- Choose the right cloud model โ public, private, hybrid, or multi-cloud
- Estimate migration effort, TCO, and expected savings
- Define the target architecture and cloud landing zone
- Map AI and data services into the cloud roadmap
- Reduce avoidable rework and lock-in risk

Cloud architecture & migration
We design well-architected cloud environments and migrate your applications and data with minimal disruption. We follow proven patterns for reliability, security, performance, and cost, and choose the right migration approach for each workload โ rehost, replatform, or refactor. For AI features, we account for data residency, managed model endpoints, and controlled access.
- Design landing zones, networking, and account structure
- Plan rehost, replatform, refactor, or re-architect per workload
- Migrate applications, databases, and storage with validation
- Design for high availability, disaster recovery, and multi-region
- Set up identity, access, and secure network boundaries
- Preserve business continuity throughout the migration

Cloud-native development
Our engineers build cloud-native applications using containers, microservices, and serverless where they fit. We focus on scalable architecture, automated infrastructure, and maintainable code. When AI is required, we add model-facing services, retrieval flows, and monitoring through managed cloud AI platforms.
- Build with containers (Docker, Kubernetes) and serverless functions
- Design microservices, event-driven, and API-first architectures
- Automate infrastructure as code (Terraform, CloudFormation)
- Process, store, and expose large volumes of data at scale
- Integrate managed databases, queues, caches, and AI services
- Keep systems elastic, resilient, and cost-aware under load

Cloud DevOps, security & QA
Our DevOps and QA teams join the project from day one. We build CI/CD pipelines, automated testing, and observability so releases stay fast and safe. We cover functional quality, performance, security, and cost. For AI-enabled features, we also test output quality, grounding, fallback behavior, and monitoring rules.
- Build CI/CD pipelines and automated deployments
- Add monitoring, logging, tracing, and alerting (observability)
- Run performance, load, security, and resilience testing
- Embed security scanning and compliance into pipelines (DevSecOps)
- Apply FinOps practices to keep cloud spend under control
- Shorten release cycles through earlier defect detection

Cloud solutions we build
We build cloud solutions tailored to specific business needs. We consider workloads, data structure, access rights, compliance, and integrations. If a project requires AI, we build it into the architecture from the start: we define scenarios, restrict data access, and establish quality, cost, and control rules.
Cloud migration & modernization
We migrate on-premise and legacy applications to AWS, Azure, or Google Cloud with a workload-by-workload strategy. We rehost, replatform, or refactor based on business value and risk, modernize data stores, and re-architect toward managed services. The result is lower infrastructure cost, better scalability, and a foundation ready for automation and AI.
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Cloud AI & ML services
We integrate managed cloud AI โ language models, retrieval, classifiers, and automation flows โ into products where they support a defined business task.
AI integration on the cloudZero-leakage security (RBAC)
We enforce role-based access control and strict data boundaries so users, services, and AI features only access what they are allowed to use.
Cloud-native microservices
We structure services so components โ including AI โ can be added, scaled, or updated independently without disrupting the core platform.
Cloud development process
We run SDLC and ADLC as one process, so the cloud platform and its AI layer are scoped, designed, built, migrated, tested, and released together.
Assessment
- Review current infrastructure, workloads, and dependencies
- Define goals, constraints, compliance needs, and cloud scope
Architecture & planning
- Set target architecture, landing zone, and migration approach
- Outline networking, security, data flows, and release logic
Design
- Design services, data stores, and integration boundaries
- Define scaling, resilience, and disaster-recovery patterns
Build & migrate
- Build cloud-native services, APIs, and infrastructure as code
- Migrate applications and data with validation and rollback paths
Testing & security
- Test performance, resilience, security, and permissions
- Run load, failover, and compliance checks before release
Deployment
- Automate CI/CD, blue-green or canary releases, and monitoring
- Cut over workloads and track system health and cost
Optimization & FinOps
- Right-size resources and tune autoscaling and storage tiers
- Track spend, set budgets, and continuously reduce cloud cost
A well-structured development process is the foundation of successful software projects. By combining clear planning, an agile approach, and continuous early feedback from the Client, we ensure that every product we build perfectly aligns with business goals. Our approach minimizes risks, optimizes resources, and delivers high-quality applications on time and within budget.
Irina BaryshnayaUnit Coordinator / Head of PMOur recent works

Cloud migration and enhancement of a property platform
A 5-year enhancement and cloud migration of a franchise property platform that brought ~30% more property enquiries through a redesign and CoreLogic data integration โ without rebuilding the platform from the ground up.
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Cloud control interface for robot operation
A cloud-connected control platform that freed Dexai Robotics' restaurant staff from engineer dependency โ cutting robot setup time per shift by ~65% and reducing interaction errors by ~50% through real-time state monitoring and offline-capable edge sync.
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Cloud ERP/CRM platform for Toyota dealers
A cloud-hosted ERP/CRM for Business Car Group โ Russia's largest Toyota and Lexus dealer network โ that replaced decade-old disjointed tools with a unified, scalable platform, cutting sales cycles by 30% across 20 dealer centers.
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Cloud-native AI knowledge base for a global nonprofit
A Middle Eastern nonprofit working in cultural preservation needed a single searchable repository for fragmented research. We built a multilingual, cloud-native AI platform that now indexes 12,000+ artifacts across 18 countries with elastic scaling.
View MoreQuick playbook: selecting a cloud development partner [pdf]
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Comprehensive multi-layer cloud security measures
Client security
- Signing NDA and SLA from the start
- Clear policies that secure your intellectual property
- Secure authentication and access control for cloud accounts
Data security
- Adherence to GDPR, HIPAA, SOC 2, ISO 27001
- AES-256 encryption at rest and TLS 1.2+ in transit
- Zero trust security model
- Automated backups, snapshots, and disaster recovery
Application security
- Automated continuous scanning for vulnerabilities
- Real-time DDoS & bot protection (WAF)
- Compliance with OWASP's Top 10 guidelines
- Regular security patches and automated updates
Cloud network security
- VPCs, security groups, firewalls, and intrusion detection
- Network segmentation and private subnets for isolation
- Encrypted tunnels and VPN for secure remote access
- OAuth 2.0, JWT tokens, and API gateways
DevSecOps
- Automated security checks in CI/CD pipelines
- Infrastructure-as-code scanning and policy as code
- Safeguarding containerized workloads against misconfigurations
- Centralized logging & real-time security monitoring
Core tech stack we use
Cloud development engagement models
Depending on your business needs, project scope, and team structure, we offer three flexible cooperation models for our cloud development services.
Outsourcing
This is a classic approach in which we take complete responsibility for the entire cloud development and migration process. Our project management team organizes the work for our cloud architects, engineers, DevOps, and QA specialists. You act as a stakeholder who focuses on strategic goals, communicating with our business analysts on requirements and with our project managers on status.
Industry-specific cloud development
We specialize in developing multi-integrated, easily customizable, and fully controllable cloud solutions. Where the use case supports it, we add AI for search, classification, and forecasting on top of scalable cloud data.
E-learning
We build scalable cloud platforms for e-learning portals, LMS systems, and content delivery. The cloud handles traffic spikes during peak enrollment, while AI can support learner assistance, content search, and Q&A over internal materials.
Edtech cloud developmentE-commerce & Retail
We develop elastic cloud commerce platforms, catalog systems, and order management that scale for seasonal peaks. AI can support product discovery, pricing analysis, support workflows, and demand forecasting on top of cloud data pipelines.
E-commerce developmentTransport & Logistics
We build cloud platforms for freight booking, warehouse operations, fleet management, and delivery control. The cloud handles high-volume telemetry and events, while AI can help with route planning, exception handling, and demand prediction.
Logistics cloud developmentMarketing Automation
We develop cloud marketing platforms for campaign management, audience segmentation, reporting, and analytics. Elastic infrastructure processes large event streams, and AI can support content classification, lead routing, and customer insights.
MarTech cloud developmentHealthcare & Lifestyle
We build secure, compliant cloud applications for patient services, records management, and internal workflows. Where policy allows, AI can support document intake, search, triage, and staff knowledge access within HIPAA-aligned cloud environments.
Healthcare cloud developmentFintech
We build secure cloud applications for payments, compliance, risk control, and operational workflows. Compliance-ready cloud services and strong isolation support regulated workloads, while AI can support investigations, document review, and transaction analysis.
Fintech cloud developmentOur cloud development approach
We run cloud development and migration through a structured process that covers scope, team setup, cost control, and post-launch operations. When AI is part of the product, we extend SDLC with ADLC, so use case design, data preparation, evaluation, and rollout are handled inside the same process.
Project scoping
We define cloud goals, business requirements, migration scope, and delivery boundaries before development starts.
- Run stakeholder interviews and architecture workshops
- Document workloads, dependencies, integration points, and success metrics
- Define the target cloud model and where AI and data services fit
- Prepare a roadmap with milestones, migration waves, dependencies, and priorities
Awards& Recognitions
Frequently asked questions
It depends on your existing stack, team skills, compliance needs, and the managed services you rely on. AWS offers the broadest service catalog, Azure integrates tightly with Microsoft environments, and Google Cloud is strong for data and AI workloads. We assess your requirements and recommend a single-cloud, hybrid, or multi-cloud approach โ and design so you are not unnecessarily locked in.
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