How a major financial institution automated 80% of AML workflows by deploying AI inside its own secure infrastructure.
AML workflows automated
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Sovereign, deterministic, quantum-resilient AI, deployed inside your secure infrastructure and operated by your team or ours — cloud, on-prem, or fully air-gapped.
Deterministic by architecture. Built to pass model-risk review.
Book an AssessmentSovereign you can verify: deterministic, reproducible, air-gapped, quantum-resilient. In production at six of the top-20 U.S. banks.
Six of the top-20
U.S. banks run Frontier Foundry in production.
10+ and 10+
Hedge funds and registered investment advisers.
Fully air-gapped
Deployed for defense, intelligence and regulatory agencies.
Quantum-resilient
Post-quantum cryptography ships as standard.
See how we verify it →The market is full of "sovereign AI"; Frontier Foundry holds technology vendors to a stricter definition.
Reproducible outputs, versioned models, and end-to-end audit trails give your model-risk and examination teams the evidence they ask for — including under the agencies' revised model risk guidance (SR 26-2).
Runs entirely inside your environment — cloud, on-prem, or fully air-gapped. Your data never leaves your network.
You own the trained models and the weights, and any improvement derived from your data.
Your team can operate, extend, and audit the system — no vendor dependency.
Every solution we build is designed to perform under the regulatory, operational, and security constraints your industry demands.
Deploy AI across AML case review, transaction monitoring, risk analysis, and trading workflows with full audit trails, model provenance, and proprietary data that stays inside your infrastructure.
Explore BankingOn-prem AI for asset managers, hedge funds, and CIOs at major banks: Skyra (portfolio intelligence) and Fiducium (multi-manager oversight). Built on Kundi.
Explore Asset ManagementDeploy AI to analyze clinical and operational data within secure healthcare systems while operating within HIPAA and PHI handling guidelines.
Explore HealthcareOperate AI inside sensitive government environments to support data analysis, decision-making, and mission-critical workflows while air-gapped deployment options and full chain-of-custody logging keep classified information secure.
Explore GovernmentLocal AI runs inside your environment, meaning your data never leaves your network, and you keep the models and weights too.
Every deployment is tied to quantifiable KPIs defined up front with your team.
Systems designed around your specific data, processes, workflows, and regulatory requirements – not generic platforms reconfigured after the sale.
Every decision path is deterministic: the same inputs, model versions, and configuration produce the same output, with an audit trail for every operation. Our generative AI is custom-built and not transformer-based, so it is deterministic and directly auditable too, and it is never the final decision-maker.
SR 26-2 validation pack
Scope analysis, inventory template, conceptual soundness, reproducibility, outcomes monitoring and audit-trail evidence. Available under NDA.
Limni runs, governs, and orchestrates AI models inside secure environments through a simple LLM interface.
Deploy Limni where data must stay on-premises and outputs must be controlled, auditable, and reliable.
Explore LimniAn ensemble reasoning engine that executes analytical work across documents, policies, and structured data at institutional scale
Deploy Kundi to surface insights, identify risks, and support complex decision-making where human expertise cannot scale.
Explore KundiHow a major financial institution automated 80% of AML workflows by deploying AI inside its own secure infrastructure.
AML workflows automated
How a Leading Hedge Fund Achieved a 40% Sharpe Ratio Improvement — Without Touching the Cloud.
Sharpe ratio improvement
A defense and intelligence agency consolidated classified analysis pipelines using Frontier Foundry inside an air-gapped environment. Details available under NDA.
How a healthcare services organization unlocked $7–10M in digital engagement revenue with AI deployed inside its own infrastructure.
Read the Case StudyFrontier Foundry moves AI from concept to live deployment inside regulated environments, then stays involved through scale and operation by offering SRE support, model monitoring, and periodic evaluations to ensure our systems improve over time.
See How Implementation WorksMap regulatory constraints and operational requirements.
Build and implement inside your environment.
Evaluate performance to guarantee system reliability at scale.
Frontier Foundry was founded by leaders with decades of experience building custom AI models, working in regulated industries, and mitigating institutional risk.
This firsthand experience gives us a deep understanding of the regulatory, political, and operational realities that determine whether AI deployments succeed or fail.

Founder, Chairman & CEO
Sultan Meghji is Frontier Foundry's founder, Chairman, and CEO, with thirty years at the intersection of AI, cybersecurity, and regulated industry. He served as the inaugural Chief Innovation Officer of the FDIC and has advised defense, intelligence and regulatory agencies. Under his leadership, Frontier Foundry has gone from founding in 2023 to production at six of the top-20 U.S. banks, and shipped AutoCEN, Limni, and Kundi into production at banks, hedge funds, and defense, intelligence and regulatory agencies.

CTO
Dr. Roque Martinez is Frontier Foundry's CTO and the visionary behind its AI platform, bringing over 30 years of fintech experience and a tenure as CTO of SmartStream. He applies deep expertise in machine learning, data analytics, and AI infrastructure to build secure, custom systems for Frontier Foundry's clients.

Managing Director
Reem Abbassi is Frontier Foundry's Managing Director, translating client goals into engineering work that delivers. Over her 20+ years in financial services, she has spearheaded firm-wide automation and AI initiatives alongside major modernization projects, from enterprise data migrations to OMS implementations.