AI
AI Agent Development with Guardrails
We build AI agents that actually do things: call your tools, work across systems, and complete multi-step tasks, with the guardrails and oversight to run them safely.
An AI agent is a system that reasons about a goal and takes actions, calling tools and APIs, to reach it. That autonomy is powerful and risky in equal measure, because an agent that can act can also act wrongly at scale. We build agents with tight tool boundaries, human oversight where it matters, and the observability to see exactly what an agent did and why.
Automated tasks
multi-step work completed across your tools and systems
Full traceability
every agent decision and action logged and auditable
Bounded risk
least-privilege access and approval gates on consequential actions
Tools, orchestration and reliable execution
An agent is only as good as the tools it can call and how reliably it strings them together. We give agents well-defined tools with strict schemas, and design the orchestration so multi-step tasks recover from failure rather than looping or stalling. For complex workflows we favour clear, inspectable control flow over letting a model improvise every step.
- Well-scoped tools with strict input and output schemas
- Orchestration that handles retries, failures and dead ends
- Deterministic control flow where reliability matters most
- Integration with your APIs, data and internal systems
Guardrails and human oversight
Autonomy needs boundaries. We constrain what an agent can touch, require confirmation before consequential or irreversible actions, and enforce permissions so an agent never exceeds the authority of the user it acts for. Guardrails against prompt injection matter especially when an agent reads untrusted content and can act on it.
- Least-privilege tool access scoped to each task
- Human approval gates before high-impact actions
- Permission enforcement tied to the acting user's authority
- Defences against prompt injection from untrusted inputs
Observability and evaluation
You cannot operate what you cannot see. We instrument agents so every decision, tool call and output is traced and auditable, which is essential for debugging and for trust. We evaluate agents against realistic task suites before release and monitor success rates, cost and latency once they are live.
- Full tracing of reasoning steps, tool calls and outcomes
- Task-based evaluation before and after release
- Monitoring of success rate, cost and latency
- Audit trails for accountability and compliance
Starting sensibly
Not every problem needs a fully autonomous agent, and the failure modes grow with autonomy. We often start with a narrowly scoped, semi-autonomous assistant that keeps a human in the loop, then widen its remit as it earns trust in production. That is usually faster to value and far safer than a big-bang autonomous system.
Frequently asked questions
- How is an AI agent different from a chatbot?
- A chatbot answers questions; an agent takes actions to achieve a goal, calling tools and APIs and chaining steps together. That means an agent can update records, trigger workflows or query systems on your behalf, which makes it far more useful and also far more important to constrain and monitor carefully.
- How do you keep an autonomous agent from doing something harmful?
- We limit agents to a defined set of tools with least-privilege access, require human approval before consequential or irreversible actions, and enforce that an agent cannot exceed the permissions of the user it acts for. We also trace every action for audit and defend against prompt injection when agents read untrusted content.
- Do we need a full agent, or would a simpler approach do?
- Often a simpler approach is better. A fixed workflow with an LLM at a few decision points is more predictable and cheaper than a fully autonomous agent, and it fails less surprisingly. We recommend the least autonomy that solves your problem, and only add more when it clearly earns its keep.
Related services
- AI DevelopmentWe build custom AI features that make it to production and stay reliable there. From LLM applications and RAG to model integration, evaluation and MLOps.
- Enterprise AIWe help large organisations turn AI from scattered experiments into governed, secure capability that delivers measurable value. Strategy, platform, governance and adoption.
- API DevelopmentAPIs designed as durable contracts, well-documented, versioned and secure, so consumers can build on them with confidence.
Industries we serve
- LogisticsSoftware built for the depot, the cab and the loading dock, not just the office. We build tracking, dispatch and field apps that keep working across Australia's patchy regional connectivity.
- StartupsShip an MVP fast without building a mess you have to unpick at Series A. We help Australian startups and scale-ups get to market and then scale the architecture as traction demands.
- GovernmentSecure, accessible digital services that meet the standards Australian government actually holds you to. We build for IRAP assessment, the Essential Eight and data sovereignty from day one.
From the blog
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