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LIQUIDITY Tech Stack

AI-powered private credit platform for mid-market growth financing

Financial Services London, England 51–200 employees Privately Held
liquidity.com LinkedIn

Liquidity deploys $10–$200M in private credit to mid-market and late-stage companies using proprietary decision-science AI. The tech stack—LangGraph, AutoGen, Python, FastAPI, Neo4j, PostgreSQL, scikit-learn, XGBoost, SHAP, MLflow—reveals a machine-learning-first architecture built around credit scoring, risk modeling, and agent-based origination workflows. Active hiring spans finance, data, and product at senior/director level, matching their focus on improving credit accuracy and portfolio monitoring while expanding US market presence.

Tech Stack 25 technologies

Core StackPython FastAPI AWS Lambda RabbitMQ Kubernetes Docker PostgreSQL Neo4j MongoDB CloudWatch Datadog RAG Pandas scikit-learn MLflow PyTorch TensorFlow LangGraph AutoGen AWS Step Functions Langfuse CRM XGBoost LightGBM SHAP

What LIQUIDITY Is Building

◆Challenges

  • Protecting investor capital
  • Elevated credit and operational risks
  • Portfolio performance monitoring
  • Expanding us market
  • Generating deal flow
  • Improving credit scoring accuracy
  • Optimizing portfolio allocation
  • Reducing underwriting risk

▲Active Projects

  • Chat interfaces
  • Agent-based workflows
  • Risk scoring engines
  • Credit scoring model
  • Cash flow forecasting model
  • Portfolio optimization model

Hiring Activity

Accelerating6 roles · 5 in 30d

Department

Finance
2
Data
1
Operations
1
Product
1
Sales
1

Seniority

Senior
3
Director
1
Junior
1
VP
1

Notable leadership hires: Director Origination

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About LIQUIDITY

Liquidity is a London-based AI-driven private credit lender operating globally across North America, Europe, APAC, and MENA. The firm underwrites growth and late-stage funding rounds, deploying between $10 million and $200 million per transaction. The business runs on proprietary AI that automates deal origination, credit assessment, and portfolio optimization—core functions reflected in active projects around risk scoring engines, credit models, cash flow forecasting, and agent-based workflows. Institutional backing includes MUFG Bank, Spark Capital, KeyBank, Cross River Bank, and others. The 51–200-person team operates as a capital markets technology company where every investment decision flows through data-driven models.

HeadquartersLondon, England
Company Size51–200 employees
Hiring MarketsUnited Kingdom, United States

Frequently Asked Questions

What is Liquidity's tech stack?

Liquidity uses LangGraph, AutoGen, Python, FastAPI, AWS Lambda, RabbitMQ, Kubernetes, PostgreSQL, Neo4j, MongoDB, scikit-learn, XGBoost, LightGBM, PyTorch, TensorFlow, and Langfuse for observability—a full ML ops stack centered on credit modeling and agentic workflows.

What does Liquidity's AI do?

Liquidity's AI automates private credit underwriting: deal origination, credit scoring, risk assessment, cash flow forecasting, and portfolio optimization. The system is built around chat interfaces, agent-based workflows, and ML models (XGBoost, scikit-learn) to accelerate investment decisions at scale.

How this profile is built

LIQUIDITY's technology stack, projects, and hiring signals are inferred from public hiring and company data — career pages, public listings, and company web presence — then clustered and de-duplicated. Figures are estimates that refresh over time. Read our full methodology →

This is not an official vendor or customer list. It is a technology-adoption signal inferred from public data, intended for B2B research.