How Pyligent AI Is Building the Foundation for AI-Native Finance
The financial world runs on complexity. Every collateral agreement, every risk model, and every liquidity decision is a tangle of data, regulation, and human judgment. At Pyligent AI, we believe this complexity can — and should — be turned into execution.
Our latest research, now published on arXiv, introduces a production-ready Agentic AI framework that combines domain-trained large language models (LLMs) with quantum-inspired optimization algorithms to automate and certify financial decision-making.
🧠 From Understanding to Execution
Traditional automation in finance stops at analysis. We’re building systems that go further — systems that can:
Read and interpret complex ISDA/CSA contracts.
Decide optimal collateral, funding, and liquidity strategies.
Certify every outcome through mathematical and regulatory traceability.
At the core of our platform is an evidence-gated LLM, fine-tuned on real-world financial agreements, that interfaces with a Higher-Order Quantum Approximate Optimization Algorithm (HO-QAOA) engine. Together, they form an Agentic AI workflow capable of both reasoning and optimization — a bridge between language intelligence and quant-grade execution.
⚙️ Quantitative Performance, Real-World Impact
Our system delivers measurable improvements over conventional baselines:
💹 ~10% higher collateral efficiency compared to BL-3 optimizers.
⚡ 65–70% faster convergence using HO-QAOA for constrained portfolio opimization.
🔒 CP-SAT certification guaranteeing every optimization result’s feasibility and compliance trace.
🧾 Audit-grade transparency, with <1.2% hallucination rate in clause extraction.
These results demonstrate that AI and Quant Optimization are no longer separate disciplines — they can coexist in a single production framework that both learns and proves its decisions.
💡 Why This Matters
Global capital markets manage tens of trillions of dollars in collateralized exposures. Even a 1% efficiency improvement can unlock billions in liquidity.
But as regulatory complexity grows, so does the cost of ensuring compliance and auditability.
Our Agentic AI framework solves this dual challenge by enabling:
Real-time, explainable decision-making across collateral, funding, and compliance.
Automated audit trails for every model and optimization.
AI systems that are self-certifying, not just self-learning.
🔭 Looking Ahead
At Pyligent AI, our vision is to make AI-auditable, quant-driven finance the new standard.
We’re actively engaging with banks, asset managers, and infrastructure partners to integrate our solution into live treasury and risk environments.
📎 Learn More
Read the full paper: https://arxiv.org/abs/2510.26217
Contact us: info@pyligentai.com
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