Synopsis

Envitia undertook a structured project to evaluate and deploy the most effective AI tools to support software engineering and delivery teams. The goal was to assess real-world applicability, integration potential, and operational value of a range of AI platforms, frameworks and productivity tools and to identify those that could be configured for industrial use. The project demonstrates Envitia’s ability to translate experimentation into mature, secure, scalable, industrialised capabilities that accelerate software development whilst meeting stringent security, integration and usability standards.

Client Goals

• Improve productivity, reduce cost and accelerate benefits realisation by using AI tools to reduce manual and repetitive software development tasks.
• Enhance delivery quality through the use of AI-assisted development, testing, and deployment.
• Embed AI responsibly, by selecting tools that meet high security assurance, compliance and integration standards.

Client Challenges

Government departments are under increasing pressure to secure the best possible value from the software, systems, and digital services they procure. They expect suppliers to deliver higher quality outcomes, faster, and at lower cost – while also demonstrating robust security, compliance and supportability.

Envitia recognised that one of the most effective ways to meet this expectation was to optimise its own software development capability. By embedding carefully selected AI tools into our engineering workflows, we have significantly increased productivity, reduced rework, and accelerated time-to-value – enabling us to deliver better solutions to Government customers at a lower cost and reduced delivery risk.

How Envitia helped

Envitia’s innovation teams led a structured programme to evaluate and deploy AI tools that would deliver measurable benefits to software quality and efficiency. This included:

• Comprehensive trials of developer tools, AI frameworks, automation platforms, and deployment environments.
• Mapping each tool to real use cases (e.g. code generation, automated testing, data labelling, documentation, bid support).
• Selecting only those tools that could be deployed in secure, scalable, supportable environments aligned with government standards.
• Assessing security, compliance, usability, cost and integration with our existing toolchain (Azure, Databricks, DevOps, IntelliJ).

Key tools successfully adopted include:

• Junie – an AI coding assistant embedded in IntelliJ that generates boilerplate code, optimises existing code, and resolves issues without copy-pasting into external platforms.
• Warp Drive – an AI-enabled terminal that streamlines command execution and boosts developer productivity without disrupting workflows.
• Streamlit – for rapid prototyping of user interfaces, enabling earlier feedback from stakeholders.
• Azure OpenAI and Databricks – for scalable, secure deployment of LLM-based solutions and data pipelines.

Tangible benefits

By industrialising these AI capabilities within our software delivery lifecycle, the client can now:

• Accelerate delivery – compressing development timelines and enabling Government customers to realise benefits sooner.
• Enhance quality – reducing defects, improving code consistency, and strengthening security from the outset.
• Reduce costs – cutting the engineering effort required per feature, lowering total cost of ownership.
• Lower risk – delivering mature, supportable, and fully compliant solutions first time.

This approach directly supports Government’s drive for Most Economically Advantageous solutions by combining speed, quality and value. Ensuring taxpayer-funded programmes achieve maximum return on investment.