One Senior Engineer. Zero Hand-off Latency.
Pick the discipline that matches the immediate challenge in front of you — most production engagements naturally touch all three layers (server, application, and AI features).
DISCIPLINE 01
Web Development & Platform Rebuilds
End-to-end web development — from greenfield builds to rescuing platforms that have been compromised or have stalled under an underperforming codebase. This covers full-stack application builds, e-commerce, and CMS work, with the same standard applied throughout: a platform that's fast, secure, and maintainable, not just shipped.
Core Engineering Deliverables
- Full-stack application builds (Next.js, React, Node.js)
- Rescue and rebuild of malware-compromised or underperforming platforms
- E-commerce builds and CMS work (WordPress, headless CMS)
- SEO recovery and technical SEO foundations
Engagement Lifecycle
Typically a fixed-scope engagement of 2–8 weeks, scoped against a clear before/after (traffic, security posture, load time) rather than an open-ended retainer.
Verified Proof: wmedtour.com
INSPECT DOSSIERwmedtour.com — Full Rebuild & SEO Recovery
Outcome: 4.04K clicks (+998%) and 724K impressions (+985%) in 28 days, per Google Search Console
Read Case StudyDISCIPLINE 02
Infrastructure, DevOps & SRE
Infrastructure work at the layer where most subtle production issues actually live — reverse proxy and CDN configuration, multi-region and multi-CDN routing, container orchestration, and the debugging work needed when a platform is technically 'up' but intermittently unreliable.
Core Engineering Deliverables
- Nginx / reverse proxy architecture and hardening
- Multi-region and multi-CDN routing setups
- Docker and Docker Compose orchestration
- Performance and reliability engineering (CDN/WAF/load-balancer debugging)
Engagement Lifecycle
Ranges from a focused infrastructure audit (1–2 weeks) to an ongoing operational role for platforms that need a dedicated infra owner.
Verified Proof: Enterprise Multi-Jurisdiction Brokerage
INSPECT DOSSIERRegulated FX & Multi-Jurisdiction Trading Platform
Outcome: 38+ production trading widgets and real-time SignalR price streaming across 4 regulatory jurisdictions
Read Case StudyDISCIPLINE 03
AI Engineering & Automation
AI engineering focused on production-shaped outcomes: multi-agent systems that coordinate real workflows, retrieval-augmented generation grounded in your own data, LLM integration into existing products, and automation pipelines (including n8n) that remove manual work rather than adding a chatbot on top of it.
Core Engineering Deliverables
- Agentic AI systems and multi-agent orchestration
- Retrieval-augmented generation (RAG) over your own data
- LLM integration into existing products and workflows
- Workflow automation (n8n) and AI-assisted SEO/content pipelines
Engagement Lifecycle
Usually starts as a scoped prototype (2–4 weeks) to prove the workflow, then a production hardening phase once the approach is validated.
Verified Proof: Xplora Kodo
INSPECT DOSSIERXplora Kodo — Agentic AI for Workforce Migration
Outcome: 17+ specialist agents coordinated across visa compliance, language training, and job placement
Read Case StudyEngagement & Technical FAQs
Direct answers to how we architect, scope, and deliver high-stakes engineering projects.
What infrastructure and DevOps consulting services do you provide?+
We provide end-to-end DevOps, SRE, and cloud infrastructure consulting including production Kubernetes cluster architecture, bare-metal and cloud Linux administration, Nginx reverse proxy hardening, multi-CDN routing, and automated CI/CD pipelines.
How are consulting engagements typically structured?+
Engagements typically start as fixed-scope sprints of 2–8 weeks scoped against clear technical deliverables (e.g. latency targets, zero-downtime migrations, or security compliance) or ongoing infrastructure ownership retainers.
Do you support regulated European environments like DORA and financial tech?+
Yes. We have direct experience engineering platforms for regulated financial institutions and trading entities in Europe, adhering to DORA compliance, strict network segmentation, and sovereign data residency requirements.
How do you build production Agentic AI and AIOps systems?+
We develop production-grade multi-agent swarms, grounded retrieval-augmented generation (RAG) pipelines, and intelligent operational triage systems that automate manual engineering tasks rather than simple prototype chatbots.
Not sure which lane fits?
Most complex technical problems don't respect neat single-lane boundaries. Describe the situation and I'll outline the exact technical architecture needed to resolve it.