How CPI Supports Your Business With Forward Deployed Engineering

In this blog post How CPI Supports Your Business With Forward Deployed Engineering we will explain how CPI helps organisations move from promising ideas to secure, working systems that deliver measurable business value.

Many businesses are not short of AI ideas. The problem is turning those ideas into something employees can trust, security teams can approve and leaders can justify financially. Pilots often look impressive in a meeting but stall when they encounter real data, existing systems, access controls and everyday working practices.

Forward deployed engineering addresses this gap. Instead of designing a solution from a distance, a senior engineer works closely with your leaders, employees and technical team. They learn the problem, build a practical solution, test it with real users and keep improving it until it works reliably in day-to-day operations.

What forward deployed engineering means in practice

A forward deployed engineer combines business analysis, solution design and hands-on software engineering. Their job is not simply to install an AI product or write code from a fixed list of requirements.

They stay close to the business problem throughout delivery. If users reveal that a process works differently from what management expected, the solution is adjusted quickly rather than forcing employees to work around unsuitable technology.

We have explored what a senior forward deployed engineer does in more detail. CPI’s support model builds on that role by bringing together AI, cloud platforms, business systems, security and operational experience under one practical engagement.

The technology behind forward deployed engineering

Forward deployed engineering is not a single product. It is a delivery approach that connects several technologies around a specific business outcome.

The AI component may use OpenAI or Anthropic Claude. These platforms use large language models, which are systems trained to understand and generate language. They can summarise documents, draft responses, classify information, answer questions and support more complex business processes.

However, an AI model alone does not understand your organisation. It needs a secure application around it, access to approved information and clear rules about what it can and cannot do.

That surrounding technology may include:

• Microsoft Azure to host the application, store information and provide secure cloud services.
• Microsoft 365 connections that allow approved use of documents, emails, calendars or collaboration tools.
• APIs, which are controlled connections that let different business systems exchange information.
• Retrieval technology that finds relevant information in approved company documents before the AI prepares an answer.
• Identity and access controls that ensure employees only see information they are already authorised to use.
• Microsoft Defender and Wiz to identify security risks across company accounts, applications and cloud environments.
• Monitoring and evaluation to measure accuracy, usage, cost and unusual activity after launch.

The forward deployed engineer brings these pieces together. The goal is not to introduce more technology than you need. It is to build the smallest reliable system capable of solving a valuable problem.

How CPI supports the engagement

1. We start with the cost of the problem

An AI project should not begin with a tool looking for a use. CPI first examines where your organisation is losing time, money or control.

That could be employees repeatedly searching for policies, service teams manually preparing similar responses or managers combining information from several systems to produce weekly reports. We establish a baseline so that improvements can be measured later.

This prevents the project from being judged by whether the demonstration looks clever. It is judged by outcomes such as hours saved, processing time reduced, errors avoided or customer responses improved.

2. We build around the real workflow

Requirements documents rarely capture every exception, manual workaround and unofficial spreadsheet. CPI works with the people performing the process to understand what actually happens.

A working version is then introduced to a small user group. Their feedback exposes missing information, confusing steps and situations where human approval is necessary. Short feedback cycles reduce the risk of spending months building the wrong solution.

This hands-on process complements our guide to aligning business and technology teams through forward deployed engineering.

3. We design security into the system

AI can make information easier to find, but it can also expose weak permissions and poorly controlled data. Security cannot be left until the final review.

CPI considers employee access, administrator privileges, sensitive information, data storage, audit records and human oversight from the beginning. As a Microsoft Partner and Wiz Security Integrator, we can connect the AI project with your wider Azure, Microsoft 365, Defender and cloud security controls.

For Australian organisations, we also consider the Essential Eight, the Australian Signals Directorate’s baseline cybersecurity framework. An AI project will not make a business compliant by itself, but it should support rather than undermine controls such as multi-factor authentication, restricted administrator access, patching and application management.

4. We connect the prototype to production systems

A prototype may work with a small set of clean documents. A production system must handle changing information, unavailable services, incorrect user input and unpredictable demand.

CPI helps connect the solution to approved data sources and existing applications. We add logging, testing, cost controls and recovery processes so your team can see what the system is doing and respond when something goes wrong.

This is the point where many AI pilots slow down. Our approach is designed to provide the practical engineering needed to move from an experiment to the measurable value expected from business AI.

5. We help your team take ownership

Forward deployed engineering should not create permanent dependence on an outside consultant. CPI documents the architecture, operational procedures, security decisions and known limitations of the system.

We also work alongside your internal IT team or existing provider. This gives them the knowledge needed to support the solution, manage routine changes and make informed decisions about future development.

An example of the potential business case

Consider a 180-person professional services company where 12 employees each spend around 45 minutes per day finding information and preparing routine client responses. Across 220 working days, that represents nearly 2,000 hours of employee time each year.

At an average employment cost of A$60 per hour, the annual time value is approximately A$119,000. The company does not need to remove positions to benefit. Recovering even half that time could allow experienced employees to handle more client work, improve response times and reduce overtime.

A suitable forward deployed engineering engagement might create an AI-assisted workspace that finds approved information, prepares a draft and requires an employee to review it before sending. Access controls protect sensitive client records, while monitoring shows usage, cost and the types of requests producing unreliable answers.

The result is not simply an AI chatbot. It is a controlled business system designed around a measurable operational problem.

When CPI’s approach is a good fit

Forward deployed engineering can be particularly useful when:

• You have tested AI tools but cannot move beyond a pilot.
• Your business and technical teams disagree about priorities.
• Your data is spread across Microsoft 365, cloud platforms and specialist applications.
• Security, privacy or Essential Eight requirements are slowing approval.
• You need senior engineering capability without hiring a full internal team.
• Your current provider can manage infrastructure but cannot build custom AI solutions.

With more than 20 years of enterprise IT experience, CPI combines practical engineering with knowledge across Azure, Microsoft 365, Intune, which manages and secures company devices, Windows 365, OpenAI, Claude, Defender and Wiz. We are based in Melbourne and support organisations across Australia and internationally.

Turn one valuable idea into a working outcome

The best starting point is rarely a company-wide AI program. It is one valuable problem, a clear baseline and a small group of users willing to test a better way of working.

If you have an AI idea that is stuck between demonstration and delivery, or you are unsure whether the business case is strong enough, CPI is happy to take a practical look with you. No large transformation program and no strings attached—just a clear discussion about the problem, the risks and the most sensible next step.