Frequently Asked Questions

All IP created during an engagement belongs to the client.

This is codified in our Master Service Agreement (MSA) and reinforced by individual NDAs signed by every team member.

We don’t retain, reuse, or reference client code or proprietary information.

We map regulatory requirements into a control checklist at the start of every engagement - covering ISO 27001, GDPR, PCI DSS (if payment data is involved), and any relevant local sector rules (e.g., Hong Kong financial regulations, German industrial standards). Controls are built into the architecture and delivery process: RBAC with least-privilege access, MFA, environment separation, and layered access approvals.

Data handling follows minimization principles with defined retention/deletion policies and managed subprocessor agreements for cross-border data transfers. DevSecOps is applied to every release with security checks, vulnerability/dependency scanning, and penetration test support when required. We maintain a full audit trail and run regular compliance reviews with the client.

We follow the principle of least privilege - team members only access data required for their specific tasks.

We use client-approved environments and toolchains, support VPN-based access to client infrastructure, and do not store client data on local machines or personal devices.

Yes. We routinely integrate into client-mandated security frameworks, including SOC 2 environments, HIPAA-adjacent requirements for healthcare-adjacent projects, and PCI DSS for fintech engagements.

We adapt to your security policies rather than asking you to adapt to ours.

Yes. We’ve executed large-scale cloud migrations, including migrating an entire fintech ecosystem from on-premise to Azure with zero downtime, involving a team of 100+ man-months.

Our cloud practice covers lift-and-shift, re-platforming, and cloud-native re-architecture on both Azure and AWS.

AI isn’t a separate offering - it’s embedded in how every team works.

Our engineers use AI for code review, test generation, documentation, architecture analysis, and regression detection as part of their standard workflow. This means a 10-person EGS team operates at the velocity of a traditional 15–20 person team.

We also build AI-powered features into client products - from ML pipelines to agentic automation - when the project calls for it.

The key distinction: we use AI to make our engineers more effective, not to replace engineering judgment.

We take an incremental approach - we don’t recommend big-bang rewrites.

Typically: technical and compliance analysis of the current system, design a modular target architecture, then roll out prioritized modules using agile delivery.

Our Motorway Traffic Prediction platform for Germany's Autobahn is a good example: incrementally processing sensor data streams into a modern analytics platform while maintaining continuous operational uptime.

We follow DevSecOps best practices: automated CI/CD pipelines, infrastructure as code, containerized deployments, automated testing at unit/integration/e2e levels, and security scanning integrated into the pipeline.

We adapt to client toolchains (GitHub Actions, Azure DevOps, Jenkins, GitLab CI, etc.) rather than imposing our own.

AI writes code. Engineers solve problems.

Our teams use AI every day - automated code review, test generation, documentation, boilerplate scaffolding - and it makes them significantly faster.

But AI agents can’t sit in your architecture review and challenge a design decision. They can’t interpret ITS protocol edge cases, navigate payment compliance across three jurisdictions, or debug a race condition in a SCADA integration.

The value of our engineers isn’t typing code. It’s understanding your domain deeply enough to know what to build, what not to build, and why.

AI is the accelerator. Domain expertise is the moat.

We follow an async-first model - write-first, read-anytime - so collaboration isn’t blocked by timezone differences. Delivery cadence follows quarterly planning with 2-week sprints and early feedback loops. Every sprint includes the full Agile ceremony set: daily standups, backlog refinements, sprint planning, retrospectives, and sprint demos.

For mission-critical projects, we run a hybrid model with synchronized meeting windows within client business hours. We integrate into your tools - Slack, Teams, Jira, Confluence - rather than creating a separate communication layer.

Agile/Scrum is our default, with 2-week sprints, but we adapt to your methodology.

We’ve worked in Scrum, Kanban, SAFe, and hybrid environments. What matters is alignment with your team’s rhythm, not imposing ours.

We scale by skill mix, not just headcount - and clients can join final interviews for key roles. Typical onboarding timelines: under 5 people in 2–4 weeks, 10+ people in 4–6 weeks. For peak demand spikes, we extend from our Vietnam network of trusted partners and vetted specialists for short ramp-ups.

For urgent timelines, we don’t follow the “throw more people at it” approach - adding people late often slows delivery. Instead, we plan a small capacity buffer upfront and deploy a focused “S.W.A.T team” to handle urgent work in parallel without disrupting the core team’s velocity.

Documentation is a deliverable, not an afterthought.

We maintain architecture decision records (ADRs), runbooks, API documentation, and onboarding guides as part of every engagement.

If the engagement ends, you receive complete documentation and a structured knowledge transfer period - we never hold knowledge hostage.

Our leadership team combines Vietnamese engineering talent with German and US enterprise experience.

CEO Ha Bui leads the company alongside Board members Dr. Paul Mathias and Christian Dowideit (both bringing German enterprise and advisory experience), and CDO Tuan Nguyen.

This dual-culture leadership ensures we combine Vietnamese engineering efficiency with German-standard precision and reliability in every engagement.

We maintain long-term strategic partnerships with Fortune Global 500 companies including Siemens, Yunex Traffic, and Autobahn.

These are not one-off projects - they are multi-year embedded engineering relationships that require the highest standards of quality and security.

93%. Most of our clients have been with us for 3+ years. We believe this reflects that our teams operate as genuine engineering partners rather than interchangeable resources.

Our deepest expertise is in transportation and smart mobility (ITS, airport systems, traffic infrastructure).

We also serve:
- Fintech/BFSI - payment orchestration, compliance systems
- Enterprise ERP - SAP-adjacent modernization
- Retail - inventory management, e-commerce platforms
- AI/automation - across sectors

Large IT services firms (Accenture, EPAM, Wipro, TCS) built their model on labor arbitrage - large teams, billable hours, time-and-materials pricing. That model is under structural pressure as AI compresses delivery timelines.

Eastgate was built differently. We run senior-heavy teams of 5–15 engineers with AI embedded in every workflow.

You get a dedicated Technical Lead, direct access to our CTO, and domain-specific engineers - not a rotating bench managed through an account layer.

Our 93% client retention rate reflects the difference. We’re not the cheapest option, and we’re not trying to be. We compete on domain depth, delivery speed, and engineering quality.

Our engineering center is in Vietnam (Hanoi), with local sales and account management presence in Germany and Japan.

Our leadership team includes solution architects and senior leaders from Germany and the US.

Our 200+ engineers are in-house, not subcontracted.

For urgent timelines, we may temporarily engage vetted specialists to start immediately, then transition to permanent in-house team members.

Our team includes solution architects with 10–15+ years of enterprise experience from Germany and the US, senior tech leads, full-stack developers, QA engineers, DevOps specialists, and AI/ML engineers.

The IT services industry is going through a structural repricing. Firms built on labor arbitrage and billable hours are under pressure as AI compresses delivery timelines and commoditizes routine engineering work.

We see this as validation of how we’ve always operated. Eastgate runs small, senior-heavy teams with AI built into every workflow - what the industry is now calling the “diamond model” versus the traditional consulting pyramid.

We don’t have 50,000 engineers to restructure. We have 200 engineers who already work with AI daily, deep domain expertise in industries where software failure has real consequences, and an engagement model tied to outcomes.

The firms that thrive in this era won’t be the biggest. They’ll be the ones with the deepest expertise and the courage to stop selling hours.