AI & LLM Infrastructure
We design and operate the production substrate that makes large language models reliable, observable, and defensible. From multi-provider routers with deterministic fallback to retrieval-augmented assistants embedded in real operational workflows, we treat AI as critical infrastructure — with SLOs, governance, and unit economics rather than demos.
What you get.
- Multi-provider AI routers with cost guardrails and failover (Groq, OpenRouter, Claude, Mistral)
- Retrieval-augmented assistants for freight, automotive, real estate, and tax workflows
- Evaluation harnesses, prompt-version control, and human-in-the-loop tooling
- Domain-grounded chatbots with structured lead capture
- Inference cost dashboards and per-feature token economics
- AI content studio infrastructure for marketing teams
How it gets used.
- Embedded AI features for vertical SaaS
- Migration from single-vendor LLM dependence to provider-agnostic routing
- AI feature audit and remediation
- Domain assistants on top of existing platforms
The technologies we draw on.
We are unromantic about tooling. We pick what your team can run on a Tuesday.
Related work.
Engagements rarely live in a single practice. These are the ones most often paired with this work.
Systems that survive the second year.
Software Engineering
Full-stack engineering with serious architecture: typed end-to-end, observable, accessible, and built to be owned long after we leave.
Compute as a strategic asset.
Cloud Architecture
Vercel-grade edge runtimes, Supabase landing zones, observability, and the FinOps discipline that keeps the bill defensible.
Strategy that compiles.
Digital Transformation
Target architectures, operating models, and program leadership that survive contact with the org chart.
Engage the AI & LLM Infrastructure practice.
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