Generative AI Consulting

Generative AI consulting focuses on large language models, vector retrieval, agentic systems, and the orchestration layer that wraps them in production. Los Angeles clients usually need to move past pilots into governed deployments: guardrails, evaluation harnesses, and integration with existing data systems. Generic AI consulting stops at strategy decks. We ship working systems.

Not currently. We deliver to Los Angeles on a remote-first basis from our nearest offices in Sydney, Melbourne, and Auckland, with time-zone overlap and synchronous delivery cadence. On-site visits are arranged on request.

The first phase runs 2-4 weeks and starts in the low five figures. Building it, from proof of concept through to production, runs 8-16 weeks. Cost depends on data volume, how much it has to connect to, and whether you need self-hosted models. After a 30-minute call we tell you a clear price.

A focused PoC for a single use case takes 4-6 weeks from kickoff to a working demo. Examples: document intelligence over a defined corpus, or an internal copilot for a specific workflow. The bottleneck is rarely the model. It is data access, evaluation criteria, and stakeholder alignment.

We are model-agnostic. In production we deploy Anthropic Claude (Opus, Sonnet, Haiku), OpenAI GPT, Google Gemini, and self-hosted open-weights models (Llama, Mistral, Qwen, DeepSeek) when data residency or cost requires them. The task drives selection. Coding agents, structured extraction, long-context analysis, and creative generation each favour different models.

US client data residency is configured per state requirements (CCPA, NYDFS, HIPAA where applicable), with cloud regions chosen to match: typically US-East, US-West, or US-Gov. Sectoral controls (HIPAA, SOX, FedRAMP) are wired in at architecture time.