AI-Augmented SDLC
Build better software by embedding AI across the delivery lifecycle
Make AI Part of How Your Software Teams Build Solutions
Our Services
How AI Improves the SDLC
Achieve better engineering outcomes across the SDLC
AI for Planning & Design
Use AI to accelerate discovery, clarify requirements, and explore design options early—reducing ambiguity before build even starts.
AI-Assisted Development
Embed AI into everyday engineering workflows to speed up coding, refactoring, and reviews—so developers spend more time solving real problems.
Agentic Delivery Automation
Design agentic workflows that handle multi-step development tasks across tools and repositories—reducing manual effort and context switching.
AI-Enhanced Testing & Quality
Improve coverage and confidence with AI-assisted test generation, smarter regression analysis, and earlier quality signals in the pipeline.
AI for Release & Change Management
Make releases safer and smoother with AI-generated summaries, risk signals, and automated documentation that enable clear handovers.
AI-Powered Operations
Apply AI to monitoring, incident analysis, and delivery insights—closing the loop between production behaviour and continuous improvement.
Case studies
Turning Ideas into Real Value
Trusted by Industry Leaders
Managing Hallucinations and Determinism in LLMs
True control and reliability are found in understanding the underlying mechanics of LLMs. Get a technical blueprint for managing two of the most critical challenges in applied AI—hallucinations and non-determinism.
State of AI Adoption 2025 Survey
We surveyed 100 CTOs, Heads of Engineering, and senior product leaders across Europe to understand how companies are leveraging AI, what barriers they face, and what strategies they are prioritising for the road ahead.
AI Product Development Experiment Insights
This white paper presents the key learnings from an internal Zartis experiment aimed at building an end-to-end AI application for processing complex Merger & Acquisition (M&A) Information Memorandums (CIMs)
AI Engineering Insights
Discover how engineering determinism transforms LLMs from unpredictable generators into reliable, production-ready systems.
Let's deconstruct the myth of “randomness” in LLMs to get a technically grounded view - demonstrating engineered determinism.
A practical industry report on context engineering—combining retrieval, memory, tools, and prompt design to scale and govern LLM and agent systems.
Synthetic data generation produces artificial data that mirrors the statistical properties of real datasets to simulate complex scenarios.
Discover why data validation is essential for business success. Learn key techniques, real-world benefits, challenges, and how verified data drives efficiency, compliance, and competitive advantage.
Discover how AI-powered design tools are transforming the early stages of product development — and what it means for your team.
Talk to us about enabling AI across your SDLC, in a way your teams will actually adopt.
