AI Agent Development Services We Offer in Adelaide
Adelaide AI agent demand splits into defence and space agents that must run inside cleared environments, and commercial agents serving wine, agribusiness, education, and SA Government back-office workflows. Our agent services cover document intelligence agents that read tender packs, supplier capability briefs, and Defence Industry Security Programme (DISP) compliance documents, multi-tool research agents that pull from controlled document libraries and structured data warehouses through Model Context Protocol (MCP) servers, satellite imagery and Earth observation triage agents that operate against Sentinel, Landsat, Planet, Maxar, and Australian smallsat feeds, V2X traffic operations agents for the Department for Infrastructure and Transport smart corridor pilots, and customer service agents for SA Health, SA Power Networks, and the South Australian Tourism Commission. We default to LangGraph, AutoGen, and Microsoft Semantic Kernel for orchestration, evaluate with Ragas, DeepEval, and LangSmith, and harden against prompt injection, tool poisoning, and data exfiltration using NeMo Guardrails, Lakera, and Microsoft Prompt Shields. Every engagement ships with a model card, an AI Ethics Framework alignment review, an AUKUS export control screen, and an ISM control map when defence or government data is in scope.
Our AI Agent Development Development Process
We run discovery, design, build, and operate phases on ACDT hours so Adelaide programme directors, DISP security officers, and SA Government delivery managers get synchronous reviews rather than overnight handoffs. Discovery opens with an Australian Privacy Principles assessment, an AUKUS and Defence Trade Controls Act screen for any defence or dual-use work, an ISM and DSPF review when the agent touches OFFICIAL: Sensitive or classified data, and an Australian AI Ethics Principles mapping that covers human-centred values, fairness, privacy, reliability, transparency, contestability, and accountability. For space clients we add an Australian Space Agency licensing review where the agent touches launch, return, or overseas payload activity. Build sprints are two weeks, run inside the cleared environment when AUKUS or DSPF restrictions apply, and reviewed against an agent evaluation harness (Ragas for retrieval, DeepEval for task completion, and a custom red-team suite for prompt injection and tool poisoning). Operate phase covers continuous evaluation, drift detection on the agent's tool catalogue and document corpus, human-in-the-loop review gates calibrated to the AI Ethics Principles, and SOCI Act incident response runbooks that exercise the 12-hour and 72-hour reporting windows where the agent supports a critical infrastructure asset.
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
Adelaide agent workloads sit on a narrow set of regions and a deliberate set of tools. We default to Azure Australia Central 1 and 2 in Canberra Data Centres (PROTECTED-rated) for any Commonwealth or Defence agent, AWS ap-southeast-2 in Sydney for OFFICIAL and OFFICIAL: Sensitive workloads, and Azure Australia East in Sydney for commercial agents. For the LLM layer we use Anthropic Claude through Azure or AWS Bedrock in Australian regions, GPT-4o through Azure OpenAI Service in Australian regions, and self-hosted Llama 3.3 70B, Mistral Large, or Qwen 2.5 on GPU clusters when AUKUS export controls or DSPF obligations rule out closed APIs. Orchestration runs LangGraph, AutoGen, or Microsoft Semantic Kernel, with tool exposure through Model Context Protocol (MCP) servers and OpenAPI specs. Vector storage runs Azure AI Search, AWS OpenSearch, pgvector on Azure Database for PostgreSQL, or Qdrant on AKS. Evaluation runs Ragas, DeepEval, LangSmith, Phoenix Arize, and a custom red-team suite. Guardrails run NeMo Guardrails, Lakera, Microsoft Prompt Shields, and Pangea AI Guard. Observability runs LangSmith, Datadog LLM Observability, Grafana Tempo, and OpenTelemetry. Pricing defaults to AUD with GST handled at invoice.
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