AI & Intelligent Automation
AI and machine learning solutions
Turn data into predictions, intelligence and action.
Not every problem needs AI, and the ones that do need it applied carefully. We help you find where machine learning or language models create real value, then build and integrate the system so it works inside your operations.
Machine learning, computer vision, NLP, predictive analytics, LLM applications and AI-powered decision systems.
From the problem to a working system.
- 01
The problem
Your data holds patterns that could improve decisions, forecasts and customer experience, but turning it into a working system is a different skill from analyzing it.
- 02
How we solve it
We define the decision to improve, prepare the data, build and evaluate the model or LLM workflow, and integrate it with your applications with monitoring in place.
- 03
What it looks like
Incoming invoices and forms are read by an AI pipeline that extracts fields, checks them against rules, flags exceptions for review and writes clean data into your system.
What we build
01
LLM applications
Retrieval-based assistants, summarization, extraction and classification built on your own content.
02
Predictive models
Forecasting, scoring and recommendation models trained on your historical data.
03
Vision and document AI
Systems that read images, scans and documents and turn them into structured data.
04
Decision systems
AI-assisted workflows that recommend or take action, with human review where it matters.
What it looks like in practice
Incoming invoices and forms are read by an AI pipeline that extracts fields, checks them against rules, flags exceptions for review and writes clean data into your system.
How a typical flow works
Data collected
Model or LLM applied
Result evaluated
Action recommended
Human review if needed
System updated
Common use cases
- Predictive analytics
- Document understanding
- Computer vision
- Natural language processing
- LLM applications
- Decision support
Technology we use
- Python
- OpenAI
- Anthropic
- Google Gemini
- FastAPI
- PostgreSQL
- AWS
- Docker
Questions we hear most
We look at the decision or task, the data available and the cost of mistakes. If AI is not the right tool, we will say so and suggest a simpler approach.
Not always. Many valuable solutions use pre-trained or hosted models combined with your own content. Custom models need more data, and we assess that up front.
We scope data handling at the start: what is sent to which provider, what is stored and what stays in your environment. Requirements specific to your industry shape the architecture.
We track quality, errors and cost, review samples of outputs and adjust prompts, rules or models as your data and needs change.
Ready to talk about ai/ml solutions?
Have a project in mind? Tell us what you're building. We'll help you scope it and get to launch.