Fintech2026
AI-assisted document processing for lending
An LLM-powered pipeline that reads, classifies and validates loan documents, with human review only where it matters.
Service 04
AI & Data Engineering
We help teams move from AI experiments to dependable features. That means clean data pipelines, evaluation before launch, and guardrails around cost, privacy and quality, so AI adds value instead of risk.
What we deliver
- LLM-powered product features and assistants
- Retrieval-augmented generation (RAG) over your data
- Document processing and intelligent automation
- Data pipelines, warehouses and dashboards
- Model evaluation and monitoring
- AI readiness and data-strategy workshops
(01)Approach
How we approach it.
- 01
Problem before model
We define success metrics and failure modes before choosing a model or vendor.
- 02
Evaluate continuously
Test sets, automated evals and human review keep quality measurable.
- 03
Privacy by design
Data minimisation, access control and clear retention rules from day one.
Typical stack
- Python
- Claude
- OpenAI
- LangGraph
- pgvector
- SQL Server
- dbt
- BigQuery
- Snowflake
- Airflow
We recommend tools per project. Your existing stack is always a valid starting point.
(02)Related work
Recent examples.
(03)FAQ
Frequently asked questions.
Will our data be used to train public models?
No. We use providers and settings that exclude your data from training, and we document every data flow.
How do you measure AI quality?
We build an evaluation set from real cases, agree on thresholds with you, and track them in CI and in production.
Now booking projects for Q1 2027