New

AI and Quantum Intelligence for Modern Collateral Management


Pyligent transforms complex derivatives workflows into seamless, certified optimization bridging finance, AI, and quantum innovation.

AI and Quantum Innovation for Modern Collateral Management



At Pyligent, we turn complex CSA workflows into seamless, certified optimization uniting financial logic, AI reasoning, and quantum precision.

Also in : Media Report, arXiv Paper

All Tasks

Operations

  • Eligibility check

    Asset type and issuer verified

  • Haircut calculation

    Market value adjusted by schedule

  • Threshold validation

    Minimum Transfer Amount confirmed

  • Optimization run

    Solver balancing liquidity and limits

  • Audit report generated

    Markdown + HTML pack ready

All Tasks

Operations

  • Eligibility check

    Asset type and issuer verified

  • Haircut calculation

    Market value adjusted by schedule

  • Threshold validation

    Minimum Transfer Amount confirmed

  • Optimization run

    Solver balancing liquidity and limits

  • Audit report generated

    Markdown + HTML pack ready

All Tasks

Operations

  • Eligibility check

    Asset type and issuer verified

  • Haircut calculation

    Market value adjusted by schedule

  • Threshold validation

    Minimum Transfer Amount confirmed

  • Optimization run

    Solver balancing liquidity and limits

  • Audit report generated

    Markdown + HTML pack ready

Evidence-Gated AI Model

Intelligent Contract Engineering

Intelligent Contract Engineering

AI that transforms complex financial agreements into clean, structured data — ready for analysis, automation, and optimization.

Collateral Management

Quantumn Optimization

Quantumn Optimization

Quantumn Optimization

AI-driven, quantum-inspired optimization engines that allocate collateral with mathematical precision. Real-time solvers balance capital efficiency, risk limits, and regulatory constraints — producing certified, audit-ready decisions in milliseconds.

What can we process?

Upload a Credit Support Annex or asset file to extract eligibility terms, optimize collateral, and generate an audit-ready report.

Add document

Extract

Report

Optimize

What can we process?

Upload a Credit Support Annex or asset file to extract eligibility terms, optimize collateral, and generate an audit-ready report.

Add document

Extract

Report

Optimize

What can we process?

Upload a Credit Support Annex or asset file to extract eligibility terms, optimize collateral, and generate an audit-ready report.

Add document

Extract

Report

Workflow Automation

Data-to-Decision Automation

Data-to-Decision Automation

Data-to-Decision Automation

Bridges the gap between unstructured CSA text and actionable optimization outputs. Converts legal data into live models, runs solver-grade analyses, and generates certified reports — all without manual intervention.

Compliance Engine

Governance & Audit Intelligence

Governance & Audit Intelligence

Governance & Audit Intelligence

Evidence-gated workflows that generate markdown and HTML audit packs, ensuring transparency and accountability across every transaction.

Simple, Smart, and Scalable Process

We design, develop, and implement automation tools that help you work smarter, not harder

Step 1

AI Powered Knoeledge Extraction

AI Powered Knoeledge Extraction

Our AI reads complex CSA agreements and converts them into standardized, machine-readable data including eligibility rules, haircuts, thresholds, and rounding schedules.

Analyzing CSA.

Minimum Transfer Amount

Thresholds

Timing & Mechanics

Haircut Matrix

Eligible Collateral

Analyzing CSA.

Minimum Transfer Amount

Thresholds

Timing & Mechanics

Haircut Matrix

Eligible Collateral

Step 2

Higher-Order Quantum Optimizer

Higher-Order Quantum Optimizer

A micro-scale HO-QAOA routine that explores local plateaus, builds a sub-Hamiltonian, and performs a quantum-inspired jump to a better collateral allocation.

  • class MicroHO-QAOA:
    def __init__(self, graph, limits):
    self.graph = graph
    self.n_max, self.k_max, self.p = limits
    def jump(self, x):
    if not plateau(x):
    return x
    S = spectral_select(self.graph, self.n_max)
    H = build_hubo(S, self.k_max)
    ψ = prep(H)
    for γ, β in angles(self.p):
    ψ = mix(β, phase(γ, H, ψ))
    y = repair(sample(ψ))
    return y if feasible(y) and J(y) < J(x) else x

  • class MicroHO-QAOA:
    def __init__(self, graph, limits):
    self.graph = graph
    self.n_max, self.k_max, self.p = limits
    def jump(self, x):
    if not plateau(x):
    return x
    S = spectral_select(self.graph, self.n_max)
    H = build_hubo(S, self.k_max)
    ψ = prep(H)
    for γ, β in angles(self.p):
    ψ = mix(β, phase(γ, H, ψ))
    y = repair(sample(ψ))
    return y if feasible(y) and J(y) < J(x) else x

  • class MicroHO-QAOA:
    def __init__(self, graph, limits):
    self.graph = graph
    self.n_max, self.k_max, self.p = limits
    def jump(self, x):
    if not plateau(x):
    return x
    S = spectral_select(self.graph, self.n_max)
    H = build_hubo(S, self.k_max)
    ψ = prep(H)
    for γ, β in angles(self.p):
    ψ = mix(β, phase(γ, H, ψ))
    y = repair(sample(ψ))
    return y if feasible(y) and J(y) < J(x) else x

  • class MicroHO-QAOA:
    def __init__(self, graph, limits):
    self.graph = graph
    self.n_max, self.k_max, self.p = limits
    def jump(self, x):
    if not plateau(x):
    return x
    S = spectral_select(self.graph, self.n_max)
    H = build_hubo(S, self.k_max)
    ψ = prep(H)
    for γ, β in angles(self.p):
    ψ = mix(β, phase(γ, H, ψ))
    y = repair(sample(ψ))
    return y if feasible(y) and J(y) < J(x) else x

Step 3

Decisions, Auditor-Ready Summary

Decisions, Auditor-Ready Summary

We integrate Pyligent’s optimization engine directly into treasury, risk, and reporting systems, delivering real-time results without changing your existing workflows.

CSA + Data

Actionable Items

CSA + Data

Actionable Items

Step 4

Governance and Audit

Governance and Audit

We generate evidence-gated audit trails for every optimization, providing transparent verification through CP-SAT checks, governance logs, and versioned decision reports.

Parity Check (CP-SAT Verified)

All allocations certified for compliance.

Stable Sweeps

μ and γ tests check robust performance

Audit Ready

Full gov pack generated for review

Parity Check (CP-SAT Verified)

All allocations certified for compliance.

Stable Sweeps

μ and γ tests check robust performance

Audit Ready

Full gov pack generated for review

Key Benefits

Bridge the gap from unstructured data to actionable decision

Lower total cost
Fewer moves
Risk held flat
Audit-ready trust
Weight-aware by design
Fast time-to-value


Bridge the gap from unstructured data to actionable decision

Lower total cost
Fewer moves
Risk held flat
Audit-ready trust
Weight-aware by design
Fast time-to-value


Let's Work Together

Book a Call Today and Start Automating

Pyligent

Pyligent – Automate Smarter, Optimize Faster, and handle collateral better.

Join our newsletter

Pyligent

Pyligent – Automate Smarter, Optimize Faster, and handle collateral better.

Join our newsletter