SERVICES // APPLIED INTELLIGENCE
AI Solutions
Artificial intelligence earns its place when it removes real effort. We look for the queue nobody wants to staff, the triage step that takes three days, the report someone rebuilds every Monday — and we automate that first.
Our position
Most AI projects stall because they start from the model instead of the workflow. We start from the work: who does it, how long it takes, what it costs when it goes wrong. Only then do we decide whether a model belongs in the loop at all.
What we ship is a system, not a demo. Retrieval you can audit, prompts under version control, evaluations that run in CI, and clear boundaries around what data leaves your environment.
What we build
- Generative AI features inside existing products
- Chatbots and assistants grounded in your own content
- Document processing, extraction and classification
- Workflow automation across internal systems
- Predictive analytics and recommendation systems
- Computer vision and natural language processing
Typical stack
- OpenAI
- Anthropic
- Google Gemini
- LangChain
- Vector databases
- Python
WHAT YOU RECEIVE
Four things leave the engagement. All four are yours.
Opportunity assessment
A ranked list of candidate workflows with the effort each one consumes today, so the first build is the one with the clearest return.
Working system
The model, the retrieval layer, the guardrails and the interface, integrated with the tools your team already uses.
Evaluation harness
A test set and scoring pipeline that tells you whether a prompt or model change made the output better or worse.
Operating handbook
Monitoring, cost controls, escalation paths and the data boundaries the system is required to respect.
HOW WE MEASURE IT
Agreed before the first commit.
- Manual handling time reduced on a named workflow
- Decision latency measured before and after launch
- Model behaviour tracked against a fixed evaluation set
- Running cost per task visible from day one
QUESTIONS WE GET ASKED
Answered before you have to ask.
Will our data be used to train a model?
Not unless you ask for it. We work inside the enterprise terms of the model providers, and we document exactly which data crosses which boundary before anything is connected.
What if AI is the wrong answer for our problem?
We will say so. A rules engine, a better query or a fixed report is often cheaper and more reliable, and recommending one costs us less than maintaining a model that should not exist.
How do you stop the output drifting over time?
Every change to a prompt, model or retrieval index runs against a versioned evaluation set. If the score drops, the change does not ship.
NEXT STEP
Start a ai solutions conversation.
Tell us what the work needs to change in the business. If AI Solutions is not the right answer, we will say so and point you at what is.