AI use stops at code generation
Engineers use AI in the editor, but requirements, testing, review, deployment and learning are unchanged.
For product and engineering teams
AI engineering capability uplift across the delivery lifecycle
Revity helps product and engineering teams use AI across the whole software development lifecycle: moving to AI-assisted, agentic development and applying it from idea and validation to coding, deployment, learning and improvement.
AI-assisted development is more than a coding assistant.
Most teams start by using AI to write code. The larger gain comes from applying AI through the whole product development lifecycle: shaping ideas, validating them, building, testing, deploying and learning from what happens next. This work suits teams building internal or customer-facing applications. If your priority is redesigning a business workflow around AI rather than software delivery practice, see forward-deployed engineers.
Tools spread faster than practice.
Practice varies from person to person
Some people are moving quickly and safely with AI while others have no reliable place to start.
Quality practices are out of step
Review, testing and assurance were designed for a slower pace and do not reflect how AI-assisted work is produced.
We build AI into each stage of the lifecycle, through real work.
Our practitioners work with your developers, analysts, testers and delivery leads on live delivery, not in a classroom.
Idea and shaping
Use AI to explore options, draft specifications and pressure-test scope before the team commits.
Validation
Prototype quickly, test assumptions with users and decide what is worth building.
Build
Adopt AI-assisted and agentic development with clear guardrails for architecture, security and code quality.
Test and review
Bring AI into test design, coverage and code review so speed does not cost confidence.
Deploy and operate
Strengthen the path to production, from pipelines to release checks, for AI-assisted change.
Learn and improve
Use production signals and AI to shorten the loop from what shipped to what to build next.
What changes
AI applied across the lifecycle, not just in the editor
Consistent practice across the team
Faster delivery with quality practices that keep up
FAQ
Questions about AI engineering uplift.
No. We work with developers, analysts, testers and delivery leads on live delivery. The team builds practical AI-assisted habits while shipping work that needs to succeed.
AI can help from idea shaping and validation through to coding, test design, review, deployment and learning. The useful starting point depends on the team’s current constraints and delivery priorities.
We establish clear guardrails for architecture, security, code quality and review. AI accelerates the work, while engineers retain responsibility for the decisions and checks that make a change safe to release.
Make AI part of how your teams build.
Talk to us about the delivery practices you want to strengthen.
Start a conversation