Services
Five practice areas, one team
Engage one or all five. Every practice area is staffed by the same group of senior engineers and operators, so the people writing the architecture are the same people who will operate it once it is live.
Practice areas
Where the work is concentrated.
AI & Automation
LLM integration, RAG architectures, agent workflows, eval harnesses, and safety reviews for customer-facing AI. Production observability and incident response for non-deterministic systems.
Cloud & Infrastructure
Multi-cloud architecture, Kubernetes cost discipline, infrastructure-as-code platform decisions, security posture management, and exit strategy when repatriation makes sense.
Custom Software
Greenfield products, MVP-to-production engineering, event-driven architectures, and platform builds. Built for production, not for demonstration.
Integration & APIs
API governance at scale, event-driven backbones, contract testing, and integration platforms across heterogeneous enterprise stacks. OpenAPI as the single source of truth.
Enterprise Strategy
Build-vs-buy frameworks, TCO modeling, operating-model design, and engineering-org milestones from MVP through scale. Architecture audits with written recommendations.
Toolchain we ship with
The stack we know in depth.
These are the tools we use day-to-day; we will work in whatever your existing stack already uses. Every vendor decision is documented with its tradeoffs.
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AI infrastructure
OpenAI, Anthropic, Pinecone, Weaviate, LangChain, and the vector database your data already wants to live in.
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Cloud
AWS, GCP, Azure, and Cloudflare. Multi-cloud where the data residency story demands it, single-cloud where it does not.
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Languages & frameworks
Flutter, React, Node.js, .NET, Python, and Go. The choice is downstream of latency, team skill, and the libraries that already work for your problem.
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Orchestration
Kubernetes, Docker, Helm, and Argo. When serverless is the cheaper or simpler answer, we will say so rather than default to a cluster.
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Data
Postgres, ClickHouse, Kafka, and Redis. Operational store, analytical store, event log, and cache — chosen by the query pattern, not the trend cycle.
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Observability
Prometheus, Grafana, OpenTelemetry, and Sentry. Metrics, traces, logs, and errors wired before launch, not after the first outage.
Engagement scope
What’s included in every engagement.
Discovery
Stakeholder interviews, codebase walkthroughs, and infrastructure inventory. We document the current state in writing before proposing any change, including the failure modes nobody has named out loud yet.
Architecture
A written design with diagrams, decision records, and explicit tradeoffs. Each option is costed against the next 24 months of load, headcount, and vendor risk — not just the launch.
Implementation
Code, infrastructure-as-code, CI pipelines, and observability shipped against time-boxed milestones. Every artifact lives in your repos and your accounts — no proprietary glue, no hidden dependencies on us.
Handoff
Runbooks, on-call playbooks, and a written exit plan. Your team can operate the system without us on day one of the next quarter, and the option to keep us on an advisory cadence is yours, not ours.
Getting started
How engagements start.
Architecture audit
The default entry point. Two to four weeks, written deliverable, no implementation commitment required afterward. Most engagements that go further begin here.
Focused proof-of-concept
A narrowly scoped build — one workflow, one integration, one model in production — to retire technical risk before the larger commitment. Three to six weeks, with the path to scale documented.
Standing advisory
For teams whose leverage is in a handful of high-stakes calls per quarter: architecture review, hiring loops, vendor selection, postmortems. Monthly cadence, exit on notice.
Start with a written proposal.
Tell us the constraint, the deadline, and what you have already tried. We will return a written outline of how we would approach it within one business day.
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