Today News

Santander AI Open Source

Sohit Aarya 23 hours ago
3 min read 43.9K views

SantanderAI

 

Open source artificial intelligence projects from Banco Santander AI Lab

Website
License
Code of Conduct
Contact

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

 

ProjectDescriptionLicenseStatus
ralphA configurable Bash/PowerShell loop that runs an AI coding CLI with a fresh session each iteration.Apache-2.0✅ Active
ralph-vault-skillSkill to generate the knowledge vault for projects using the Ralph loop.Apache-2.0✅ Active
auto-bayesianConfig-driven, interpretable Bayesian network training for relational tabular data.Apache-2.0✅ Active
autoguardrailsAlignment-research scaffold (autoresearch-style) for LLM guardrails over a single policy.md surface.Apache-2.0✅ Active
causal-perception-implementationML 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-graphSynthetic fraud graph generator for training and benchmarking graph-based fraud detection models. Scales to 100M+ accounts.Apache-2.0✅ Active
genetic-algorithmA 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-trainerTrain linear embedding adapters with triplet loss to align retrieval embeddings with your queries (RAG).Apache-2.0✅ Active
llm_bridgeA 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-frameworkMechanical Governance for LLM Decisions — model-agnostic governance regimes, hard gates and governance metrics for high-stakes LLM decision systems.Apache-2.0✅ Active
mutatis-mutandisSituation 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-datasetsOpen 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

 

     
                    WhatsApp Channel                             Join Now            
   
                    Telegram Channel                             Join Now            
   
                    Instagram follow us                             Join Now