Enterprise AI & LLM Integration
LLM integration, AI agents, and production-ready AI pipelines at enterprise scale. From strategy to scalable rollout — with real impact instead of proof-of-concept theater.
Some consultants deliver slide decks. I deliver commits. Cloud architecture, AI engineering, and platform transformation — for teams who know that production is the only test that counts.
From the first whiteboard session to production deploy. No vendor lock-in, no one-size-fits-all playbook — I start with an honest look at what actually is, not what I want to sell.
LLM integration, AI agents, and production-ready AI pipelines at enterprise scale. From strategy to scalable rollout — with real impact instead of proof-of-concept theater.
Analyze complex business processes and transform them into robust, maintainable automations. Reduce manual steps at every level of the organization — AI-assisted where it makes sense.
Multi-cloud architectures on AWS, GCP, and Azure. Highly available, scalable infrastructure — Well-Architected compliant and ready for real load, Day-2 operations included.
Structured migration of on-premise and legacy systems to the cloud. Lift & shift to cloud-native transformation — with clear migration paths, minimal downtime, and maximum carry-over.
High-traffic systems and distributed architectures that work under real load. Bottleneck analysis, load profiling, capacity planning.
Observability architectures, incident response processes, SLO/SLI definitions, and error budget management for enterprise-grade operations.
From mono-repos to distributed services — build systems, test automation, and release pipelines that make teams more productive instead of slowing them down.
Terraform for reproducible, versionable infrastructure. Enterprise-wide unified modules, policies, and compliance-as-code. GitOps workflows with Flux CD.
Internal developer platforms (IDPs), self-service infrastructure, and golden-path templates. Reducing cognitive load for development teams.
Zero-trust architectures, identity & access management, secret management, and security-by-design in CI/CD pipelines. Compliance without productivity loss.
Systematic analysis and optimization of cloud spending. Commitment strategies, rightsizing, tagging policies, and continuous cost monitoring.
Scrum coaching, dev team orchestration, and process analysis through to automation. Structured methodologies for distributed teams — from backlog to deployment cadence.
I'm not a consultant who delivers PowerPoints and disappears. I'm the person still in the terminal at 3am because the system needs to be highly available by morning — and who makes sure that situation never happens again.
For more than 15 years I have built and operated systems that must work under real load — not just in the demo. My clients are companies that want to scale, need to modernize legacy infrastructure, or want to understand how to meaningfully integrate AI into their processes.
My approach: I start with an honest technical picture of reality. No cargo-cult architectures, no over-engineering traps. What I recommend, I have run in production myself and know its weaknesses firsthand.
Incremental migration of a grown PHP monolith into a containerized, highly available, and scalable microservices architecture on AWS ECS Fargate. Zero downtime through blue-green deployments and feature flags. Terraform for the entire infrastructure, Bitbucket Pipelines for fully automated CI/CD workflows.
Design and implementation of an AI automation platform using n8n as orchestration layer and Anthropic Claude as the cognitive core. Automation of document processing, email routing, and internal approval workflows. Integration with existing systems via REST APIs and RabbitMQ. Running on AWS, fully as Infrastructure as Code.
Design and implementation of a company-wide Terraform framework on AWS with reusable modules for 14 development teams. Multi-staging system with separate environments for Dev, Staging, and Production. Dedicated CI/CD pipelines for Terraform runs with automatic plan validation and controlled apply process.
Built an enterprise-wide observability platform based on OpenSearch and Elasticsearch for centralized log management and search. AWS CloudWatch as native monitoring layer for infrastructure metrics and alerts. OpsGenie as alerting and on-call platform with rule-based routing. AI-powered incident management for automatic alarm correlation, root cause analysis, and runbook generation — MTTR significantly reduced.
You talk directly with me — not a sales team. No template, no standard proposal. Just an honest conversation about your project.
Thank you for your inquiry. I will get back to you as soon as possible.