AI 4 Finance Lab
Build the best AI systems in the world for finance.
Not "good enough for a demo". Not "generic models used for finance sometimes".
We want models, tools, and environments designed from day one for financial data, decisions, and
controls.
Our Ambition
We believe finance is where the most important AI systems will be built.
- The data is rich and structured.
- The stakes are high and very real.
- The rules are strict and cannot be ignored.
This is the perfect place to push the state of the art in model design, reasoning under constraints, and learning from real decisions over time.
ai4f aims to be the place where:
- The strongest small finance foundation models are built
- The most practical neuro-symbolic systems are proven
- The first serious RL environments for capital are developed
Why finance needs its own AI
Most modern AI is built around open text, chat, and search. Finance is different.
Messy but Structured
PDFs, scans, screenshots, CSVs. Underneath the mess, there is structure: tables, ledgers, schedules, policies.
Real Cost of Mistakes
A wrong number isn't just a hallucination. It can break a month-end close or damage trust. Precision matters.
Rules are Mandatory
Accounting standards, tax, risk limits. You cannot ignore them and "mostly get it right".
Generic models are good at language. They are not built for precise numbers, strict schemas, long-running workflows, and hard constraints. That gap is exactly where ai4f works.
What we are working on
Three major tracks forming a new kind of AI stack for finance.
Finance Foundation Models
Small, Fast, Correct
We are building models that are small enough to be fast, tuned for financial language/layouts, and focused on correctness. Not chasing 100B+ parameters, but genuine usability.
- Document → JSON (Schema-aware extraction)
- Entity & Field Extraction (Parties, accounts, tax fields)
- Transaction Tagging (Fraud risk, disputes, adjustments)
Neuro-symbolic Systems
Models + Rules + Code
Neural components handle perception (OCR, extraction). Symbolic components handle structure (schemas, formulas). We treat finance tasks as small programs.
- Composability (Reusable steps)
- Transparency (Inspectable workflows)
- Correctness-by-construction
Finance Gym
RL Environments for Finance
A family of RL-friendly environments where decisions (payables, collections, treasury) can be simulated and improved safely.
- Reconstruct decision loops from logs
- Define clear state, actions, and rewards
- Build simulators and evaluation harnesses
How We Work
Start from real workflows
We sit with how people actually close, reconcile, pay, collect, and report.
Measure against real baselines
Field accuracy, schema validity, cash impact, risk metrics, time saved.
Integrate, not replace
Our models plug into existing ERPs and data warehouses.
Humans in the loop
Review queues and clear logs are part of the architecture, not a patch.
Who We Work With
We collaborate with finance teams, engineering teams, and researchers who care about correctness and control.
If you care about building the best AI systems for finance — not just good demos — ai4f is meant to be a place for you.
Get in Touch