AI Agent Development Services We Offer in Auckland
Auckland AI agent buyers are pragmatic — New Zealand corporates run leaner engineering teams than Australian peers and look for partners who deliver rather than write proposals. Our services match that disposition. We build customer-service agents for Spark New Zealand, ANZ NZ, ASB, BNZ, and Westpac NZ pattern banks under the Financial Markets Conduct Act 2013 and the RBNZ outsourcing policy (BS11), claims-handling agents for IAG New Zealand (AMI, State, NZI brands), Suncorp New Zealand (Vero, Asteron Life), Tower Insurance, and ACC-adjacent insurers under the Insurance (Prudential Supervision) Act 2010 administered by the RBNZ, dairy-supply-chain copilots for Fonterra-pattern cooperative agribusiness flows from farmgate through processing to export, aviation operations agents for Air New Zealand and Auckland International Airport ground-handling workflows, primary-sector decision-support agents for the wider dairy, beef, sheep, kiwifruit, and wine sectors served by Fonterra, Synlait Milk, Open Country Dairy, Silver Fern Farms, Zespri, and Villa Maria, public-sector copilots for Auckland Council, Watercare, Auckland Transport, and Te Whatu Ora Health New Zealand under the Algorithm Charter for Aotearoa, and research-intensive agents for University of Auckland, AUT, and Massey University Auckland campus spinouts. Every agent ships with explicit human-in-the-loop boundaries, full observability through LangSmith or Langfuse, deterministic guardrails, an OPC-aligned Privacy Impact Assessment, and a documented Te Tiriti o Waitangi review where the agent affects Māori communities or data.
Our AI Agent Development Development Process
Discovery opens with a use-case workshop defining the agent boundary: which decisions are autonomous, which require human approval, which stay fully human. For RBNZ-regulated banks and insurers we run an outsourcing policy (BS11 for banks, IPS-Outsourcing for insurers) review, an RBNZ prudential supervision assessment, and an FMA conduct risk classification under the Conduct of Financial Institutions Act 2022 (CoFI) which commenced 31 March 2025. For public-sector clients we run an Algorithm Charter for Aotearoa New Zealand alignment review (the 28 government agencies signed up commit to transparency, partnership with Māori, focus on people, and ongoing accountability), a Government Chief Digital Officer Cloud Risk Assessment, and a Privacy Impact Assessment under the New Zealand Privacy Act 2020 with the Office of the Privacy Commissioner notification model in mind. For Te Whatu Ora Health New Zealand work we run a Health Information Privacy Code 2020 review and engage with the National Ethics Advisory Committee (NEAC) ethical standards where research-adjacent work is in scope. Build sprints are two weeks. Every agent ships with versioned prompts, a tool catalogue (what external systems the agent can call), an evaluation harness running golden test cases on every pull request, and a documented escalation path to a named human owner. Deployment runs through Codazz-managed observability, with drift detection, prompt-injection defences, and a rollback that RBNZ, FMA, and OPC reviewers can sign off without bringing in a second vendor.
Process Discovery
1-2 WeeksWe sit with the people doing the work in {city} and record the real process — including the exceptions they handle by instinct, which are exactly what kill naive automations.
Tool Surface Design
1-2 WeeksEvery system the agent touches gets a typed, permission-scoped tool with its own rate limit and rollback path. The agent gets a narrow set of verbs, never raw admin access.
Build & Evaluate
3-6 WeeksThe agent is built alongside its evaluation suite from day one, using real tasks from your business with verified outcomes. Every change is scored before it ships.
Shadow Mode
2-3 WeeksThe agent runs against live traffic but commits nothing. We compare its proposed actions to what your team actually did and tune until agreement is high enough to trust.
Staged Autonomy & Run
OngoingAutonomy is released by risk band — reversible actions first, irreversible ones keeping a permanent human gate. Then we monitor completion rate, escalations, latency and spend.
Technologies We Use for AI Agent Development
Auckland agent workloads benefit from a new option in 2024 — AWS announced the New Zealand Region (ap-southeast-6, Auckland) launch with confirmed availability from 2024, joining the existing Azure presence in Australia (Sydney, Melbourne, Canberra) and the Auckland-hosted edge locations from Cloudflare and Fastly. Where New Zealand data residency is a strict requirement, we default to AWS ap-southeast-6 (Auckland) as it becomes generally available for the production services in scope, with AWS ap-southeast-2 (Sydney) as the established fallback for services not yet in Auckland. For Microsoft-anchored stacks we use Azure Australia East (Sydney) until Azure announces a New Zealand region. For GCP-anchored stacks we use australia-southeast1 (Sydney) and australia-southeast2 (Melbourne). Frontier model APIs are Amazon Bedrock with Anthropic Claude and Meta Llama on Sydney inference endpoints, Azure OpenAI on Australia East, and Anthropic on AWS Bedrock. Self-hosted Llama 3, Mistral, and Qwen run on Australian or Auckland GPU instances when CoFI conduct obligations or Te Tiriti partnership commitments require strict data sovereignty. Agent frameworks are LangGraph and CrewAI for stateful orchestration, with LangSmith and Langfuse for observability and Pydantic AI for type-safe tool calls. Evaluation runs through Promptfoo and DeepEval. Vector storage sits in pgvector on Aurora ap-southeast-2 or Pinecone Sydney.
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