AI and automation
Most AI projects fail because they start from the technology rather than a task worth automating. We start from the task, and will tell you when a rules engine would be cheaper and more reliable than a model.
Why teams come to us
What this fixes.
- Staff re-keying data from documents
- Support volume that scales with headcount
- Decisions made on stale reporting
- Unstructured data nobody can query
Capabilities
What the work covers.
Document processing
Extracting structured data from invoices, forms and scans, with confidence thresholds and human review where it matters.
Assistants and chat
Retrieval-grounded assistants that answer from your content, cite it, and say when they do not know.
Predictive analytics
Forecasting and scoring on your own data, with honest accuracy reporting and a baseline to beat.
Language and voice
Translation, transcription and classification — including for languages the large providers serve poorly.
Evaluation and guardrails
Test sets, regression checks and fallbacks, so quality is measured rather than assumed.
What you get
Working pipeline with evaluation harness
Accuracy baseline and reporting
Human-in-the-loop review where needed
Cost and latency budget
- Python
- PyTorch
- Hugging Face
- Model APIs
- PostgreSQL
Questions
Before you ask.
We scope that with you before anything is built — what leaves your infrastructure, what is retained, and by whom. Where the answer needs to be 'nothing leaves', we build for that.
An evaluation set built before the system, and measured against a simple baseline. If the model cannot beat the baseline we say so.
Talk to us about ai and automation
Send a short brief and we will tell you within two working days whether we are the right fit.
Start a project