About CodeFish Studio
CodeFish Studio has been in business since 2014, delivering technology projects for clients. The company's main offerings are Custom Software Development and UI/UX Design. Its team includes 10 - 49 specialists working across design, development, and delivery. Clients can expect pricing around $200 - $300 / hr/hr, with projects averaging about $60,000. Their home base is Thebarton, Australia. These details offer a useful starting point when evaluating CodeFish Studio.
Where We Specialize
Industry Expertise
Typical Project Size
CodeFish Studio Reviews
Write a ReviewOur most downloaded release ever, built by a team that truly listened
Derek Holloway / Chief Information Officer - Pinnacle Health SystemsSep 04, 2023
Project summary: Our editorial team was managing content across seven different tools with no single source of truth — we needed a unified CMS that could handle structured and rich-media content equally well.
We ran a structured RFP with seven vendors. Three made it to the technical evaluation stage. This team won on the strength of their technical proposal, their domain knowledge, and frankly on the quality of the questions they asked us during the process. A vendor who asks good questions in the sales phase tends to ask good questions during delivery too. That hypothesis proved correct. The project is now live, performing above the KPIs we agreed, and our stakeholders are genuinely impressed.
Domain knowledge that went beyond generic expertise into our specific industry, willingness to push back constructively, automated test coverage that gave us deployment confidence
The initial project brief document they required was more detailed than we were used to providing, but in hindsight that rigour was part of why the project ran so smoothly
Questions & Answers
Design system that made every screen in our product feel intentional
Stephanie Coleman / SVP of Digital Strategy - Horizon Financial GroupMar 27, 2022
Project summary: Claims fraud detection had been rule-based for years and we were losing ground to more sophisticated patterns — we needed a machine learning model built on our own historical data.
Our industry has specific compliance requirements that many generalist agencies struggle with. This team came with working knowledge of the relevant frameworks, asked pointed questions about our obligations, and built controls into the architecture rather than bolting them on at the end. Our compliance team reviewed the delivered system and had only minor observations, which is genuinely unusual for a first-pass review. That domain awareness saved us significant remediation cost.
Engineering quality that our internal team can maintain without calling the vendor, thorough documentation, proactive risk identification throughout the project
Premium pricing compared to some of the alternatives we evaluated, but the quality of the output and the absence of rework costs made the investment straightforward to justify