Claude & the Anthropic API
Claude Enterprise deployments, Anthropic API integration, and agents built on the models your license already pays for.
Explore →40 areas where we are subject-matter experts.
Every skill below is one our forward-deployed engineers have shipped to production — not a logo wall. Agentic AI on top, Kubernetes-grade foundations underneath. If it's on this page, we'll put it to work in your stack in weeks.
01 Browse the catalogue
Agentic AI
Agents that plan, reason, and act across your real systems — designed, shipped, and kept alive in production.
Model Context Protocol (MCP)
MCP servers and clients that give your agents governed, auditable access to real enterprise systems.
Explore →Multi-Agent Orchestration
Systems of specialized agents that hand off, verify each other, and escalate to humans — running reliably in production.
Explore →LangGraph
Stateful, durable agent graphs — checkpointing, human interrupts, and production deployment done properly.
Explore →LangChain
LangChain in production: lean chains, real retrieval, and the discipline the framework doesn't enforce for you.
Explore →Agent Evals & Testing
Eval suites that prove your agents work — before your users prove they don't.
Explore →Tool Use & Function Calling
Agents that safely act — schema design, permissioning, and execution layers for real side effects.
Explore →Human-in-the-Loop Systems
Approval gates, review queues, and escalation flows that let agents automate 95% and route the risky 5% to people.
Explore →Prompt Engineering
Prompts as engineered, versioned, eval-gated artifacts — not folklore in a shared doc.
Explore →AI Coding Agents
Claude Code and agentic development workflows that multiply engineering throughput — governed, measured, and real.
Explore →Agentic Workflow Automation
Whole business workflows — intake to resolution — handed to agents, with judgment steps automated, not just the clicks.
Explore →Data & Retrieval
Your fragmented, messy data — connected, cleaned, and wired into retrieval that makes agents actually know your business.
Retrieval-Augmented Generation (RAG)
RAG pipelines grounded in your real documents — with citations, evals, and answers your compliance team can live with.
Explore →Vector Databases
pgvector, Pinecone, Weaviate, Qdrant — chosen for your workload, tuned for recall and latency, run like real infrastructure.
Explore →Embeddings & Semantic Search
Search that understands meaning — embedding pipelines, hybrid retrieval, and reranking tuned on your queries.
Explore →Data Pipelines & ETL
The pipelines that feed your agents — ingestion, normalization, and freshness from systems that were never meant to talk.
Explore →PostgreSQL
The database under everything — schema design, performance, pgvector, and operations that hold at scale.
Explore →Kafka & Event Streaming
Event backbones for agentic systems — Kafka pipelines that feed agents fresh data and absorb their output safely.
Explore →Infrastructure
The Kubernetes-grade foundations under everything we ship — the reason our deployments survive contact with production.
Kubernetes
Production Kubernetes — cluster architecture, workload hardening, and the platform discipline that makes AI deployments survive.
Explore →Helm
Charts your team can actually maintain — packaging, templating discipline, and release automation for Kubernetes.
Explore →Terraform
Infrastructure as code that stays true — module architecture, state discipline, and drift-free cloud environments.
Explore →Amazon Web Services (AWS)
AWS architecture with adult supervision — landing zones, EKS, serverless, and bills that stop growing on autopilot.
Explore →Google Cloud Platform (GCP)
GKE-first cloud architecture — Google Cloud platforms built by people who know why GKE is the best-run Kubernetes money rents.
Explore →Microsoft Azure
AKS platforms and Azure OpenAI deployments inside the enterprise boundary your compliance team already governs.
Explore →Docker & Containerization
Images built right — small, secure, reproducible — and the container workflows that everything else stands on.
Explore →GitOps & ArgoCD
The cluster state lives in git, deploys are pull requests, and rollback is a revert — deployment as a controlled system.
Explore →CI/CD Pipelines
Pipelines that are fast, trusted, and boring — GitHub Actions and friends engineered like the production systems they are.
Explore →Observability
OpenTelemetry, Prometheus, Grafana — plus LLM-native tracing, so you debug systems instead of guessing at them.
Explore →Service Mesh
Istio and friends, deployed for reasons instead of résumés — mTLS, traffic control, and cross-service visibility.
Explore →AI Operations
The operational discipline that keeps models fast, governed, and affordable after launch day.
LLMOps
The operational layer for LLM systems — versioning, evals, cost control, and incident response for model-driven software.
Explore →MLOps
Classical ML operations done right — pipelines, registries, monitoring, and retraining for models that predict rather than chat.
Explore →Model Serving & Deployment
Inference infrastructure — vLLM, autoscaling, low-latency serving, and self-hosted models inside your boundary.
Explore →GPU Infrastructure
GPU fleets that earn their invoice — scheduling, utilization, and capacity strategy on Kubernetes and cloud.
Explore →Fine-Tuning & Model Customization
LoRA, distillation, and preference tuning — applied when evals prove the need, not when the hype does.
Explore →AI Security
Prompt injection defense, agent permissioning, and the security architecture that lets AI systems pass real review.
Explore →AI Governance & Compliance
Governance that ships — audit trails, human oversight, and EU AI Act readiness built into the system, not the binder.
Explore →Amazon Bedrock
Frontier models inside your AWS boundary — Bedrock agents, knowledge bases, and governance through the IAM you already audit.
Explore →Engineering
Senior software engineering — the languages and backend craft that everything above it depends on.
Python
Production Python — typed, tested, fast where it counts — for the AI systems and services the ecosystem runs on.
Explore →TypeScript & Node.js
Type-safe services and full-stack product engineering — the language of your frontend, backend, and half the agent ecosystem.
Explore →Go (Golang)
The language of cloud infrastructure — high-concurrency services, operators, and CLIs that deploy as one binary and just run.
Explore →API & Backend Engineering
The backend craft under every system we ship — API design, data modeling, auth, and services that hold under load.
Explore →02 How the skills become outcomes
Skills are the inventory. Services are the delivery.
A catalogue is only proof of breadth. Delivery happens through six focused services — forward deployed engineering, agentic systems, productionization, data & RAG, Kubernetes platforms, and AI governance — each staffed by engineers who hold the skills on this page.
See a skill you need in production?
Tell us the workflow and the stack. A forward-deployed engineer will show you what shipping it in weeks looks like.
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