Outback Yak
Let’s talk
Explore

01 / AI & Agents

AI & Agents

We build AI systems that are generative and agentic, and useful. We use generative AI to create, summarise, reason, and respond to information, and agentic AI to take actions such as managing workflows and handling repetitive tasks (in your businesses, or your products). This allows businesses to offer more value to their customers and employees.

We are prolific users of agentic techniques to build better software and products. We also employ the same agentic techniques to help build value for your businesses and products.

A question connects to source documents and a referenced answer
An engineering view / From our delivery work
01

What it makes possible

  • Automates repetitive, time-consuming tasks without extra headcount.
  • Faster responses and insights by pairing foundation models and agentic techniques.
  • Consistent execution that scales without adding complexity.
  • Evals and metrics to measure the success of your AI systems.
02

What to watch for

  • Using AI without a clear, measurable use case.
  • Confusing generative AI with autonomous agents and overpromising.
  • Expecting AI to repair broken processes instead of fixing foundations.
  • Not measuring how your AI systems are actually performing.
03

How we approach it

  • We use foundation models and agentic techniques to build value for your businesses and products.
  • We embed AI into real workflows with human oversight by design.
  • We measure outcomes so AI remains useful, accurate, and accountable.
  • We also tell you when AI is not the best solution for your problem.

Frequently Asked Questions About AI and Agents

Where should we start with AI and Agents in our business?

We start by understanding your business goals and pain points. We then identify the specific tasks that can be automated with AI. We then build a proof of concept to demonstrate the value of the AI system. We then scale the system to your business needs.

Do we need custom models or can we use off-the-shelf?

From our experience, we find that using off-the-shelf models and agent frameworks is the best way to get started. We then customise the model to your business needs.

How do you keep AI and Agent outputs accurate?

We use evals and metrics to measure the accuracy of the AI system. We also use human oversight to ensure the accuracy of the AI system.

Can you integrate AI and Agents with our existing systems?

Yes. We connect AI agents to your current apps and data, respecting permissions and logging activity for auditability. We also build new apps and data to support the AI system.

How do you handle security and privacy?

We apply principle-of-least-privilege for connectors, redact sensitive data where required, and choose hosting that meets your compliance needs.

How do we measure success?

We define metrics tied to cycle time, cost per task, and quality benchmarks, then monitor them in dashboards to keep value visible. We also use evals and metrics to measure the success of the AI system.

Recent work

Where we've done this

Hai Helper retrieval workflow: a participant's question, official NDIS documents, and an answer with source references

Empowering NDIS Participants with Multi-Agent Retrieval AI

Large Language Models (LLMs) are impressive at generating human-like text, but in real-world applications, fluency isn’t enough.

Read the case studyMEKSI text, audio and video learning, shown as a diagram

Transforming Medical Education with AI: MEKSI's Journey to a State-of-the-Art Chatbot

Building AI-supported medical learning with MEKSI, a Sydney-based startup

Read the case study

Ready to put AI and Agents to work in your business?

Let's build a proof of concept to demonstrate the value of the AI system. We then scale the system to your business needs.

Talk to us