Generative AI
Assistants and copilots that sit inside the tools people already use, drafting, summarising and answering from approved material rather than guesswork.
Artificial Intelligence
Intelligence Applied
to Real Work
We put artificial intelligence where it changes an outcome: inside the processes, decisions and daily work your organisation already depends on. Every engagement starts with the business question, not the model.
Overview
AI that earns its place in the workflow
Most organisations do not have an AI problem. They have a process that takes too long, a decision made without enough evidence, or knowledge locked in documents nobody has time to read. AI is useful when it removes one of those constraints.
NOVARA AI works from that starting point. We identify the handful of processes where intelligence changes cost, speed or quality, prove the case on real data, then engineer the solution properly — grounded in your own knowledge, integrated with your systems, and governed so you can explain how it behaves.
The result is not a pilot that never leaves the lab. It is a working capability with an owner, a measurable baseline and a path to the next process.
What We Deliver
Five ways we apply AI
Each can be engaged on its own or combined into a single programme of work.
Agentic AI
Agents that reason over a goal, plan the steps, call your systems and complete the work, with a human in the loop wherever the decision warrants one.
RAG & Knowledge
Retrieval-Augmented Generation over your policies, contracts and records, so answers are grounded in your own documents and cite where they came from.
Decision Intelligence
Forecasting, classification and scoring models that put evidence behind operational decisions, deployed with monitoring and drift alerts.
AI Platform & Enablement
The shared foundation — model access, evaluation, guardrails, cost controls and an internal team trained to build on it without us.
AI Opportunity Assessment
A two-week review of your processes, data and systems that returns a ranked shortlist with effort, value and risk against each item.
How We Work
From question to production capability
Four stages, each with a decision point. If the value is not there, we say so before the build starts.
01
Frame
Pick the process, agree the measure that has to move and confirm the data exists.
02
Prove
Build a working slice against real data and evaluate it against the current way of working.
03
Engineer
Harden it: integration, security review, guardrails, observability and release automation.
04
Operate
Hand over with documentation and training, monitor quality and cost, then choose the next process.
Agent Examples
Agents already at work
Five agent patterns we deploy most often, each scoped to a defined set of tasks.
AI HR Agent
Employee enquiries
HR policy search
Leave assistance
Document generation
HR workflow initiation
AI Recruitment Agent
Candidate screening
CV analysis
Job matching
Interview assistance
Candidate communication
AI Software Engineering Agent
Requirements analysis
Code assistance
Test generation
Documentation
Code quality analysis
AI Support Agent
Knowledge retrieval
Customer enquiries
Ticket classification
Troubleshooting
Escalation
AI Business Operations Agent
Data analysis
Workflow execution
Reporting
Alerts
Business recommendations
Governance
Intelligence you can explain
AI in production needs the same controls as any other system of record: known data boundaries, evaluation before release, and a record of what the system did and why.
Data boundaries
Your content stays inside agreed storage and network boundaries, with access recorded.
Evaluation
Accuracy, refusal and safety test sets run before every release, not after complaints.
Traceability
Prompts, retrieved sources and tool calls are logged so any answer can be reconstructed.
Human oversight
Approval steps on any action that moves money, data or an employment decision.
Technology
The AI stack we build on
Large language models
Model routing & fallback
Vector databases
Embedding pipelines
Agent orchestration
Tool & API adapters
Evaluation harnesses
Guardrails & filtering
MLOps & monitoring
Azure & AWS AI services
Data engineering
Cost & usage governance
Start With One Process
Find the AI case worth building.
Bring us a process that costs too much or takes too long. We will tell you whether AI is the right answer.
Talk to Our Experts →