Arryze is a Brisbane‑based consulting and technology advisory firm. Its AI‑enabled bid support tools help advisory teams reuse existing knowledge and reduce time spent on repetitive proposal work.
Using AI to strengthen tenders and win work
How Arryze helps consultants reuse proposal knowledge, reduce effort and improve bid quality
The challenge
Preparing bids and proposals is time‑consuming and repetitive.
Many advisory firms rely on fragmented libraries of CVs and case studies. Consultants are often asked to rewrite the same content to meet tender requirements. This takes time, increases cost, creates inconsistencies and reduces the chances of winning work.
In some firms, up to half of effort of writing a proposal goes into low‑value tailoring. Valuable knowledge already exists, but teams struggle to reuse it efficiently without losing quality or a human tone.
Arryze saw a clear opportunity to do this better.
The approach
Arryze started with a specific business problem. The goal was to reduce repetitive work while improving quality and consistency across bids.
The team designed a suite of AI‑enabled tools to capture, structure and reuse proposal knowledge at scale. These include:
- a CV reuse tool
- a case study reuse tool
- a combined builder tool
- a bid writer with built-in compliance checks.
The tools use large language models and semantic search to help teams find, adapt and reuse proposal content. They run in a secure, closed environment so each client keeps control of their data.
Arryze fine-tuned the tools to match its brand voice and writing style. Content is written in Australian English and designed to sound clear, practical and human.
Human review is part of the process from start to finish. The tools are developed in line with the essential practices, with clear data controls, built‑in safeguards, and people remaining responsible for the final output.
AI helps us reuse what we already know. Our people still review every bid and take responsibility for the final outcome.
– Craig Johnson, CEO, Arryze
The benefits
The tools have delivered clear, measurable results for Arryze and the advisory firms that have licensed them.
Firms using the tools:
- reduce bid preparation effort by 30 per cent or more
- improve consistency and quality across submissions
- increase win rates
- build a reusable knowledge asset that grows over time.
By cutting repetitive work, teams can focus on higher‑value activities. This includes attracting new business, strengthening client relationships and supporting revenue growth.
Video transcript
Video transcript
Craig Johnson, Managing Director, Arryze speaking:
Craig Johnson – I’m the Managing Director of Arryze.
We’re a specialist management consultancy firm primarily targeting business and government of all shapes and sizes. So, the problem we’re trying to solve is – “how do we efficiently and effectively replace low-value work for our very busy consultants in the creation of bids and tenders and proposals for our clients”.
That time-repetitive, knowledge-intensive activity is really ripe for the use of Large Language Models to adopt a more efficient and effective way to achieve those outcomes. It’s really important when we’re developing these tools, for those tools to fully replicate what our team do so that we didn’t have to… We minimize the amount of work that we have to do in oversight.
We’ve been focusing on building a culture of curiosity and continuous improvement, and when you marry those things and the emergence of AI as just another tool that you explore and you seek out to know how it works and where its benefits might be, I think it’s just a natural extension of all that.
Fair amount of our focus is on making sure that our tools remain fit for purpose, remain across the innovations that are coming in the market. And then importantly, we’re commercialising what we’ve learned into other adjacent industries and businesses like ourselves in the professional services market who might benefit from getting on this journey and being able to implement and use tools in a way that’s consistent with where we’ve seen the benefits.