Services
AI SDLC consulting for teams that want to do it right
AI tools can make engineering teams faster, but only if the way of working changes with them. We help you build AI into every stage of software delivery - specs, coding, review, testing and release - so productivity gains are measurable and do not leave quality, security or maintainability debt behind.
The problem
Why AI in the SDLC fails without a method
Licences for coding assistants are easy to buy. Getting dependable results from them across a whole team is not.
01
Everyone uses AI differently
Each developer has their own prompts, tools and habits. Results vary from person to person and nothing is shared or improved.
02
Speed moves the bottleneck
Code arrives faster than it can be reviewed and tested with confidence, so defects and rework appear later and cost more.
03
Risk builds quietly
Unclear data handling, unvetted dependencies and code nobody fully understands become security and maintainability debt.
What we offer
Seven offerings, one way of working
Start with the one that addresses your biggest gap today. Each works on its own and fits with the rest.
Loop Engineering
Design the plan, generate, review, test, refine loop your engineers and AI tools work in, with guardrails and review gates.
Spec-Driven Development
Write specs with acceptance criteria and examples that both people and models can execute against, traced through to tests.
Model Selection
Choose a model for each engineering task on quality, latency, cost, data residency and compliance, backed by your own evaluations.
Prompt Engineering
Move from ad-hoc prompting to a shared library of versioned, tested prompt and context patterns.
AI-Enabled Test Automation
Use AI to design, generate and maintain tests across unit, API and UI layers, with coverage that reflects risk.
Right Tool for Each SDLC Stage
Vendor-neutral selection of AI tools from planning to operations, with security review, licensing and integration covered.
AI Training for Teams
Role-based, hands-on programmes for developers, QA, architects and engineering leaders, with follow-on coaching.
Engagement models
Three ways to work with us
We agree scope and duration after a first conversation about your teams, tools and goals.
01
Assessment
A short, focused review of how your teams use AI today, where it helps, where it hurts and what to change first. You get a prioritised plan.
02
Pilot team
We work alongside one team on real work, putting the loop, specs, prompts and tests into practice and measuring what changes.
03
Enablement programme
We take what worked in the pilot to the rest of engineering through playbooks, training and coaching, until your people own it.
FAQ
Frequently asked questions.
It is help with using AI across the whole software development lifecycle - not just code generation, but specs, review, testing, tooling and skills - so teams get faster without lowering the bar on quality, security or maintainability.
We are vendor-neutral. We work with the assistants, agents and models you already use, and when you need to choose we help you evaluate options against your own tasks and constraints.
Most teams start with an assessment or with Loop Engineering, because the way people and AI tools work together shapes everything else. We will suggest a first step after an initial conversation.
We agree a small set of signals with you at the start - such as cycle time, review effort, escaped defects and rework - take a baseline, and track them through the engagement. [TBD: metric]
Related offerings
Keep exploring.
Cloud Consulting and Support
Cost, security, migration and 24x7 support for your cloud platforms.
Infrastructure Security Consulting
Penetration testing, posture reviews, monitoring and compliance.
AI-Generated Code Review
Independent review of code written with assistants and agents.
Software Architecture Review
An independent view of how your system is built and where it will strain.
Contact Stavir
Tell us how your team works with AI today.