Software development
AI Product Development
LLM-powered features, assistants and AI workflows built into real products, and validated with the full rigour of our QAI Engineering practice before they reach users.
Shipping AI is easy. Shipping AI you can trust isn’t.
A working AI demo takes an afternoon. An AI feature that gives accurate answers, fails gracefully, protects user data and behaves the same next month takes engineering discipline.
We build AI features into products and internal workflows, from LLM-powered search and assistants to document processing and AI-assisted tooling, using the same engineering standards as the rest of your software.
What makes us different is how we test it. Our QAI Engineering practice evaluates accuracy, hallucination, bias, security and privacy, so you have evidence the feature works before you put it in front of customers.
What we build
AI features with evidence behind them
LLM-powered features
Assistants, search, summarisation and content features built into your product with sensible guardrails.
AI workflows & automation
AI-assisted internal processes and tooling that save real time without hiding risk.
Evaluation & validation
Test sets and automated evaluations for accuracy, hallucination and regression across model and prompt changes.
Responsible AI & governance
Bias, security, privacy and governance considered from the start, not retrofitted after an incident.
How we work
Prove the value, then prove it’s safe
- 01
Find the right use case
Identify where AI genuinely helps your users or teams, and where it doesn’t.
- 02
Prototype with evaluation
Build a working prototype alongside the test set that measures whether it’s good enough.
- 03
Engineer for production
Guardrails, monitoring, fallbacks and cost controls, built like any other production feature.
- 04
Monitor and re-evaluate
Re-run evaluations whenever models, prompts or data change, so quality doesn’t silently drift.
Technology we work with
Model-agnostic: we choose providers and models to fit your data, cost and governance requirements.
- Application
- TypeScriptNode.jsReactNext.js
- AI
- Hosted LLM APIsLocally hosted modelsRetrieval-augmented generation
- Platform
- AWSAzureDocker
- Quality
- LLM evaluation suitesPlaywrightQAI Engineering
FAQs
Common questions
How do you test an AI feature when its output changes every time?
We build evaluation sets of realistic inputs with expected qualities, then score outputs automatically for accuracy, grounding, tone and safety. Those evaluations run whenever the model, prompt or data changes, the same way regression tests run for normal code.
Can you add AI to our existing product?
Yes. Most AI work is adding capability to an existing product or workflow rather than building something new from scratch.
What is QAI Engineering?
QAI Engineering is Novaeris’s approach to quality in the age of AI: using AI responsibly within testing, and rigorously testing AI-enabled products. It underpins how we validate every AI feature we build.
Engineering confidence into digital delivery
Ready to Release with Greater Confidence?
Whether it’s quality engineering, automation, delivery assurance, AI-ready testing or sourcing the right people, let’s talk about where you are and where you want to be.