YOUR CHALLENGE
Deliver software faster, measurably and sustainably.
Smarter Product Engineering
Accelerate software delivery by embedding AI across your entire development lifecycle. For organizations that neeed to build better software faster, with the engineering capability to keep pace.
YOUR CHALLENGE
Product and engineering teams are under more pressure than ever: expected to deliver more, faster, at higher quality, with the same or fewer resources. Most organizations are still building software the same way they did five years ago.
AI tools are being adopted ad hoc, without consistency or governance - productivity gains are patchy and hard to measure, and technical debt keeps mounting.
HOW GRAVITY9 ADDRESSES THIS
We help enterprises embed AI systematically and sustainably across the full product development lifecycle. This isn't about giving developers a Copilot licence and hoping for the best.
We establish consistent, repeatable AI-augmented ways of working, assess your current engineering capability, define a clear AI adoption roadmap, upskill your teams, and work embedded alongside them to make the change stick.
Success story
Leading Jewelery Retailer
We delivered a full AI SDLC transformation for a leading jewelery retailer - one of the most comprehensive enterprise implementations of AI-augmented engineering at scale. Recognized by Anthropic as a leading proof point, the program established consistent, repeatable AI practices across distributed teams.
Impact
30%
increase in productivity
BENEFITS
What we help you achieve
Improve code quality and reduce defect rates.
Establish consistent AI practices across distributed teams.
Free engineers to focus on complex, high-impact work.
Build internal AI delivery capability that improves over time.
COVERAGE
Our approach spans the full product lifecysle.
01
Requirements & design
AI-asssisted analysis, user story generation, and architecture decision support.
02
Development
Agentic coding, intelligent code reviews, and AI pair programing at scale.
03
Quality assurance
AI-driven test generation, automated testing, and defect prediction.
04
Delivery & operations
AI-enhanced CI/CD, incident analysis, and release optimization.
OUR APPROACH
Delivering smarter product engineering
Assess
Evaluate tool usage, team readiness, infrastructure, and governance maturity. Typically 2-3 weeks.
Strategy & roadmap
Define trget state, select tools, design a governance framework, and build the business case. Typically 3-4 weeks.
Pilot
Controlled rollout with 2-3 selected teams, with embedded acceleration and training. Typically 8-12 weeks.
Scale
Enterprise tool usage, team readiness, infrastructure, and governance maturity. Typically 2-3 weeks.
Optimize
Expand use cases, deepen context, and improve outcomes continuously.
WHY GRAVITY9
We run an AI-enabled delivery lifecycle ourselves - the same practies, tools and ways of working we help our clients adopt are embedded in how our own teams build software every day. We have delivered AI SDLC transformations inside some of the most complex engineering organizations in the world, across distributed teams, regulated environments, and enterprises where the stakes of getting it wrong are real.
CAPABILITIES
Related capabilities
Artificial Intelligence
Strategy, agentic systems, LLM integration
Software Engineering
Architecture build, modernization
Product & Design
AI product design, UX,digital delivery
Data
Foundations, pipelines, AI-ready architecture
FAQ
Solutions questions answered
What are gravity9's core solutions?
Intelligent Operations (AI-powered process automation), Smarter Product Engineering (AI-augmented software delivery), and AI-Accelerated Enterprise Modernisation (legacy system transformation).
What does Smarter Product Engineering involve?
It's gravity9's service for embedding AI systematically across your software development lifecycle, from requirements and architecture through delivery and operations, rather than issuing developers a Copilot licence and hoping for the best.
Do we need to already use AI coding tools before starting?
No. Every engagement begins by assessing your current tool usage, team readiness, and governance maturity, so the roadmap fits where you are today, not where a vendor assumes you are.
How long does it take to roll out AI practices across engineering teams?
Typically 2–3 weeks to assess, 3–4 weeks to define the roadmap, 8–12 weeks to pilot with a small number of teams, then an incremental, team-by-team scale-up rather than a single enterprise-wide switch.
Ready to engineer smarter?
Empower your engineering teams to move faster, work smarter and deliver high-quality products at scale.