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Claude-Native Solutions

Our Services

Purpose-built enterprise AI solutions powered exclusively by Anthropic’s Claude. From development acceleration to autonomous agents, we deliver production-ready results.

Claude Code & AI Development

The Challenge

Enterprise development teams are drowning in boilerplate, repetitive testing, and documentation debt. Traditional coding assistants offer superficial autocomplete that barely scratches the surface. Meanwhile, backlogs grow, velocity stalls, and your best engineers spend more time on maintenance than innovation.

Our Solution

Claude Code (v2.1.76) transforms your entire software development lifecycle — an agentic coding partner that understands your full codebase, executes multi-step tasks autonomously, and maintains context across complex refactoring sessions.

  • Custom Skills & Plugins — tailored to your workflows, drawing from an ecosystem of hundreds of plugins and thousands of skills
  • CI/CD Integration via Hooks — event-driven automation integrated with your deployment pipelines and custom system prompts
  • Claude Code Security — AI-powered vulnerability scanning that identifies complex flaws traditional static analysis misses
  • Agent Teams — multiple Claude instances working in parallel on cross-layer changes spanning frontend, backend, and tests

20-60% productivity improvement

Based on Anthropic enterprise deployment benchmarks

Claude CodeClaude Opus 4.6Claude Sonnet 4.6Agentic DevelopmentSkills & PluginsHooksClaude Code SecurityAgent Teams

MCP System Integration

The Challenge

Enterprises operate dozens of disconnected systems — CRMs, ERPs, document stores, databases, APIs — each requiring custom integration work. Every new AI capability means another bespoke connector, another maintenance burden, another point of failure. The result is fragile, expensive data pipelines that can't keep pace with business needs.

Our Solution

The Model Context Protocol (MCP) is the de facto industry standard for connecting AI models to external systems — now under Linux Foundation governance with 97M+ monthly SDK downloads and MCP v2 beta.3 bringing multi-agent communication.

  • Custom MCP Servers — secure, structured access to your entire technology ecosystem including CRMs, ERPs, and internal knowledge bases
  • Authentication & Audit Logging — enterprise-grade security with rate limiting built in from day one
  • Cross-Platform Orchestration — eliminate the integration tax by connecting Salesforce, databases, and APIs through a single protocol

80% reduction in integration time

Compared to traditional point-to-point integration approaches

Model Context ProtocolMCP ServersEnterprise ConnectorsAPI OrchestrationData Integration

Autonomous Agent Development

The Challenge

Critical business processes still require constant human monitoring and intervention. Customer enquiries queue overnight, compliance checks run on schedules instead of in real-time, and incident response depends on whoever happens to be on call. Single-purpose bots can't handle the nuance and decision-making these workflows demand.

Our Solution

Using Anthropic’s Agent SDK, we build autonomous AI agents that handle complex, multi-step workflows with human-level judgement — from single specialised agents to coordinated Agent Teams.

  • Agent Teams — multiple Claude instances coordinate in parallel, with one as team lead and others as specialists sharing context
  • Adaptive Thinking — dynamically adjusts reasoning depth based on task complexity for optimal quality-latency trade-offs
  • Computer Use — automates desktop workflows across applications, handling UI interactions autonomously
  • Constitutional AI Guardrails — every agent operates within defined boundaries with human-in-the-loop checkpoints for high-stakes decisions

90% faster response times

For automated workflow processing versus manual handling

Agent SDKAgent TeamsAdaptive ThinkingComputer UseConstitutional AIHuman-in-the-Loop

AI Governance & Compliance

The Challenge

Deploying AI in regulated industries without proper governance is a liability timebomb. Most AI vendors leave compliance as an afterthought, forcing enterprises to either slow-roll adoption or accept unquantified risk. Australian organisations face unique requirements around data sovereignty, privacy, and workplace regulations that generic AI governance frameworks simply don't address.

Our Solution

We build comprehensive AI governance frameworks purpose-designed for Australian regulatory requirements, covering the full lifecycle from alignment to ongoing monitoring.

  • Constitutional AI Alignment — embeds your organisation’s values directly into model behaviour and decision-making
  • Data Sovereignty Architecture — all processing stays within AWS Sydney region, with IRAP assessment readiness from the ground up
  • Claude Code Security — AI-powered vulnerability scanning that traces data flows and identifies business logic flaws
  • Compliance Automation — Privacy Act-compliant data handling, risk assessments, bias testing protocols, and clear escalation procedures

Privacy Act & IRAP compliant

Meeting Australian Privacy Act and IRAP standards

Constitutional AIIRAP AssessmentPrivacy Act ComplianceData SovereigntyClaude Code SecurityFedRAMP High

Custom Agent Training & Fine-Tuning

The Challenge

Generic AI models lack domain expertise. They hallucinate on specialised workflows and can't learn from your organisation's specific patterns.

Our Solution

We train custom models using open-source foundations and proprietary data — Claude serves as the orchestration and evaluation layer, not the model being fine-tuned.

  • Custom Small Language Models (SLMs) — purpose-built from open-source foundations for specific enterprise workflows, delivering faster and more accurate results than general-purpose models
  • Reinforcement Learning & RLHF — training pipelines that align custom models with your organisation’s domain expertise
  • Custom Tooling Agents — agents that learn from your team’s workflows and continuously improve over time
  • Evaluation Frameworks — A/B testing infrastructure and continuous improvement pipelines for every custom agent

Custom-trained for your workflows

Purpose-built for your domain-specific workflows

Reinforcement LearningRLHFFine-TuningCustom SLMsAgent Evaluation

Enterprise AI Observability

The Challenge

Agentic systems operate autonomously, making it critical to understand what they're doing, why, and whether they're performing as expected. Without observability, autonomous AI is a black box — unacceptable for regulated enterprises.

Our Solution

We implement comprehensive observability stacks that give you end-to-end visibility into every decision your agentic AI systems make.

  • Distributed Tracing — OpenTelemetry-based tracing of agent decision chains with structured logging of every tool call and reasoning step
  • Real-Time Dashboards — Grafana dashboards showing agent performance, cost, and accuracy metrics at a glance
  • Compliance Audit Trails — full audit logging for regulated environments with session replay for debugging
  • Anomaly Detection — automated alerting for behaviour drift, cost spikes, and performance degradation

Complete pipeline visibility

End-to-end visibility across your agentic AI systems

OpenTelemetryGrafanaDistributed TracingAudit TrailsCost Analytics

Ready to move from AI pilots to production?

Let’s discuss how Claude can transform your enterprise.

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