/solutions/predictive-ai

Predictive AI & applied ML.

Forecasting, vision, NLP, LLM systems. In production, on real data — not pilots that never ship.

AI shipped across finance, agriculture, media and industry

Moonsyst · commodities trading teams · RTL · food-industry producers · sports-medicine clinics

What we build with AI

Five categories. All in production.

[ 05 / 05 ]
01 · forecasting
Forecasting & predictive models

Time-series and event prediction on noisy real-world signal.

→ moonsyst_oestrus-calving
→ commodities_price-prediction
02 · vision
Computer vision

Detection, classification and measurement from video and imagery.

→ food-industry_defect-cv
→ musculoskeletal_video
→ agridron_parcel-analysis
03 · nlp
Document understanding & NLP

Structured signal out of unstructured documents and text.

→ music-rights_reconciliation
→ invoice_processing
04 · llm-agents
LLM-based systems & AI agents

Workflow automation, structured extraction, RAG assistants, human-in-the-loop agents. Specifics under NDA — happy to discuss in confidence.

05 · synthetic-data
Synthetic data & training infrastructure

Synthetic data generation and training pipelines where real data is scarce, sensitive, or imbalanced.

Featured AI work

Selected projects.

All AI case studies →

Methodology

How we approach AI.

Every AI project lives or dies on what surrounds the model, not the model itself. Three rules we don't break:

01
Eval harness before the model

If we can't measure whether it's working, we don't ship it. Evaluation comes first, not last.

02
Human override before autonomy

Every autonomous path has a human stop. Autonomy is earned with evidence, not assumed.

03
Observability before celebration

A demo isn't production. We instrument behaviour in the real world before calling anything done.

Your data & IP

your-data_yours weights_delivered no-shared-training providers_transparent

Get in touch

An AI project, or an AI idea you're not sure how to ship?

We'll tell you honestly whether ML is the right tool — and if it isn't, what is.