---
title: "Santander AI Open Source Projects on GitHub"
url: https://stacklist.com/card/92708210-17a0-47df-9c10-52f5dae42be5
source_url: "https://github.com/SantanderAI"
stack: https://stacklist.com/stack/c691055b-de15-47a1-ad6a-6c4ecec55f18
summary: "Santander AI Lab's open source repository features AI tools and projects designed for small models, responsible AI, MLOps, and graph machine learning in the financial services industry. The repository includes 12 active projects with Apache 2.0 licensing and a transparent governance process managed by their Open Source Programme Office."
tags: "open-source, artificial-intelligence, machine-learning, financial-services, responsible-ai, mlops, graph-learning"
key_entities: "Banco Santander (organization), Santander AI Lab (organization), ralph (technology), auto-bayesian (technology), gen-fraud-graph (technology), llm_bridge (technology), mech-gov-framework (technology), responsible-ai (concept), causal-perception (concept), Madrid (location)"
classification: "reference"
content_hash: "sha256:9f31ac184c5bc8c81aeb98698550d35cd7ebc69a4300690a48014f3707b99de8"
acp_version: "0.2"
token_counts_approximate: 903
visibility: public
agent_accessible: true
status: "final"
---

# Santander AI Open Source Projects on GitHub

SantanderAI Open source artificial intelligence projects from Banco Santander AI Lab Our mission We build and open source AI tools that advance small models, harness engineering, evolving agents, responsible AI, MLOps and graph machine learning for the financial services industry. By contributing back to the open source ecosystem we help raise the bar for trustworthy AI in banking — and we give back to the community whose work powers our own innovation. Featured projects Project Description License Status ralph A configurable Bash/PowerShell loop that runs an AI coding CLI with a fresh session each iteration. Apache-2.0 ✅ Active ralph-vault-skill Skill to generate the knowledge vault for projects using the Ralph loop. Apache-2.0 ✅ Active auto-bayesian Config-driven, interpretable Bayesian network training for relational tabular data. Apache-2.0 ✅ Active autoguardrails Alignment-research scaffold (autoresearch-style) for LLM guardrails over a single policy.md surface. Apache-2.0 ✅ Active causal-perception-implementation ML research code for causal perception — comparing competing structural causal models via interventional and counterfactual distributions, applied to fair credit decisions. Apache-2.0 ✅ Active gen-fraud-graph Synthetic fraud graph generator for training and benchmarking graph-based fraud detection models. Scales to 100M+ accounts. Apache-2.0 ✅ Active genetic-algorithm A dependency-free Python genetic-algorithm engine with pluggable fitness criteria — a reusable search core for an LLM/AI autoresearcher. Apache-2.0 ✅ Active linear-adapter-trainer Train linear embedding adapters with triplet loss to align retrieval embeddings with your queries (RAG). Apache-2.0 ✅ Active llm_bridge A tiny, vendor-neutral LLM client library — one interface with pluggable adapters for OpenAI, AWS Bedrock and Google Gemini, or bring your own backend. Apache-2.0 ✅ Active mech-gov-framework Mechanical Governance for LLM Decisions — model-agnostic governance regimes, hard gates and governance metrics for high-stakes LLM decision systems. Apache-2.0 ✅ Active mutatis-mutandis Situation testing for discrimination analysis with counterfactual comparators — research code for the paper 'Mutatis Mutandis: Revisiting the Comparator in Discrimination Testing'. Apache-2.0 ✅ Active sota-stressed-datasets Open benchmark datasets republished in stressed form to evaluate ML/LLM robustness. Curated by Santander AI Lab. CC BY 4.0 + Apache-2.0 ✅ Active All projects use synthetic or anonymised data only . No real customer information is published. Open source governance Our Open Source Programme Office (OSPO) runs a transparent two-track review for every project considered for public release: Fast Track — forks, generic tools, tutorials, datasets, SDKs without business logic. Reviewed by OSPO Lead with automated scans (SLA < 4 hours). Full Track — AI models, frameworks with IP, code that touched internal data. Reviewed by a FOSS Review Board (OSPO Lead + Legal + CISO + Architect). SLA 2-4 weeks. Full policy: GOVERNANCE.md Contributing We welcome contributions from everyone. Please read: CONTRIBUTING.md — how to submit issues and pull requests CODE_OF_CONDUCT.md — Contributor Covenant v2.1 SECURITY.md — responsible disclosure All contributors agree to our Contributor License Agreement (CLA) on first PR Contact General open source / partnerships: opensource@gruposantander.com Security: security@santander.com Website: santander.com Careers in AI: santander.com/en/careers Built with ❤️ by AI Labs · Banco Santander · Madrid 🇪🇸 Open code · Responsible AI · For the community