What this covers
- Document processing that reads invoices, forms, and contracts and puts the fields into your systems
- Enquiry triage that categorises, prioritises, and routes incoming email and support tickets to the right person
- Internal search across your documentation, policies, and past projects, answering with the source alongside the answer
- Forecasting and classification from data you already collect — demand, churn risk, stock levels
- Workflow automation joining the manual steps between systems into one process that runs on its own
- The monitoring around all of it, so you can see accuracy, cost, and what happened on any given run
How we approach it
The first conversation is about whether AI is the right tool at all. Plenty of automation problems are better solved with a scheduled job and clear rules, which costs less to build and far less to run. We will tell you when that is the case rather than sell you a model you do not need.
Where a model is right, we establish how accuracy will be measured before building anything, then run new versions against that same test set. Without it, "the AI seems better now" is an opinion nobody can check.
Anything with real consequences keeps a person in the loop — the system proposes, a human approves. Your data is handled deliberately: we agree what may be sent to a third-party model and what must stay inside your infrastructure, and that boundary is enforced in code rather than left to convention.
Tools we use for this
The platforms we reach for on this kind of work. The right choice depends on what you already run, and we will tell you when your existing tooling is the better answer.
- Anthropic
- OpenAI
- Python
- Jupyter
- pandas
- NumPy
- Keras
- OpenCV
- Apache Airflow
- Apache Spark
- Databricks
- PostgreSQL
- Elasticsearch
- Snowflake
- Apache Kafka
- Hugging Face
- Ollama
- Replicate
Common questions
Will our data be used to train someone else’s model?
Not without your explicit agreement. We use API arrangements that exclude your data from training by default, and where information is too sensitive to leave your environment we build with models that run inside your own infrastructure instead.
How accurate is it going to be?
That depends entirely on the task, which is why we measure it on your real data during a short evaluation phase before committing to a build. You get a number to make the decision with, rather than a promise.
What does it cost to run each month?
We estimate running costs during scoping and design to keep them predictable — caching repeated work and using smaller models where a larger one adds nothing. Ongoing spend is visible in your monitoring, not a surprise on an invoice.
Talk to us about ai & automation
Tell us what you are trying to achieve and we will tell you honestly whether we are the right fit. We reply within 1 - 2 business days.
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