Services The practice

Production AI fails
at the seams.

Modeling, infrastructure, and security are one system. We work across all three disciplines so nothing falls through.

A warm timber-and-glass gallery filled with daylight Fig. 01 · Architecture as Place
01

AI/ML Engineering

Production-grade language model systems, from architecture review through deployment, evaluation, and continuous improvement.

Specializations
RAG & retrieval systems LLM evaluation, guardrails & red-teaming Inference cost & latency optimization MLOps & LLMOps pipelines
Representative deliverables
  • RAG pipeline design and implementation (Bedrock, Azure OpenAI, Vertex AI, pgvector)
  • Model selection, fine-tuning, and distillation strategy
  • Automated evaluation harnesses and regression testing
  • Cost and latency optimization for high-volume inference
02

Cloud Architecture

Reference architectures, IaC modules, and platform engineering for AI and data-intensive workloads across AWS, Azure, and Google Cloud.

Specializations
Landing zones & multi-account governance Cross-cloud workload migration Identity & access (IAM, Entra ID) Data & AI platforms (BigQuery, Vertex AI, Bedrock)
Representative deliverables
  • Multi-account landing zones and org-level governance (AWS, Azure, GCP)
  • Kubernetes (EKS, AKS, GKE) and serverless patterns for inference at scale
  • VPC, networking, and data-residency design
  • Terraform and IaC modules with documentation and runbooks
  • Cross-cloud portability for multi-cloud estates and migrations
03

Security & Compliance

Audit-ready posture for AI systems handling sensitive data. We work alongside your security team, not around it.

Specializations
AI & LLM threat modeling SOC 2 readiness for LLM apps HIPAA-readiness architecture CSPM & IAM hardening
Representative deliverables
  • IAM and least-privilege design for human and machine identities
  • Encryption strategy: cloud key management (KMS, Key Vault, Cloud KMS), envelope encryption, model-weight protection
  • SOC 2, HIPAA, and ISO 27001 readiness assessments
  • Threat modeling for LLM-specific risks (prompt injection, data leakage)
Engagement models

Structured around the
shape of the problem.

Not a fixed playbook. We scope work to the system in front of us.

2 weeks

Architecture Sprint

Focused review and reference architecture for a defined system or migration.

4–12 weeks

Embedded Build

Principal engineers work alongside your team to design, build, and harden production systems.

Quarterly retainer

Standing Advisory

Ongoing architecture review, security-posture monitoring, and on-call principal access.

Start here

Bring us the system
that worries you.

Book a 30-minute technical review with a principal. No sales engineers.

Book a technical review