Own the code. Own the data. Deploy autonomous AI agents for compliance, risk, and operations — on your infrastructure, under your control.
ibl.ai is a production-grade AI platform already serving 1.6M+ users across 400+ organizations — delivered as full source code, not a SaaS subscription. Banks, investment firms, and insurers receive the complete codebase to deploy, modify, and operate entirely within their own infrastructure.
For financial services, control is everything. Our autonomous AI agents don't just answer questions — they monitor regulatory feeds, flag compliance anomalies, execute risk workflows, and coordinate across systems without human intervention. Every action is logged in a complete, immutable audit trail built for SOX, SEC, and model risk governance requirements.
With zero telemetry, air-gapped deployment options, and no external dependencies, sensitive financial data never leaves your perimeter. You choose the AI models — GPT, Claude, Gemini, Llama, or your own — and you retain full ownership of the platform from day one. No vendor lock-in. No ongoing dependency. The system runs whether or not you ever call us again.
ibl.ai powers 1.6M+ users across 400+ organizations including NVIDIA's global AI training platform. This is not a pilot or a proof of concept — it is a battle-tested platform ready for enterprise financial services deployment.
You receive the complete codebase at contract signing. Audit every line, modify any component, and deploy on your own terms. No black boxes, no hidden dependencies, no SaaS subscription required to keep the lights on.
Run on your private cloud, on-premises data center, or fully air-gapped environment. Zero external API calls are required. Sensitive financial data, customer records, and model outputs never leave your controlled perimeter.
Bring your preferred AI models — OpenAI GPT, Anthropic Claude, Google Gemini, Meta Llama, Mistral, or proprietary fine-tuned models. Switch models at any time without re-architecting the platform or renegotiating contracts.
Once delivered, the platform operates independently. If you never contact ibl.ai again, every agent, workflow, and integration continues running. Your institution owns the technology outright — not a license to use it.
Every capability is exposed through RESTful APIs. Integrate with core banking systems, risk platforms, CRMs, and data warehouses. Multi-tenant architecture with role-based access control supports complex organizational hierarchies and regulatory isolation requirements.
Agents continuously monitor SEC, FINRA, OCC, and CFPB regulatory feeds, compare new guidance against internal policies, flag gaps, and automatically route remediation tasks to the appropriate compliance officers — without waiting for a human to initiate the review.
Autonomous agents query transaction databases, apply configurable risk models, cross-reference sanctions lists and behavioral baselines, and escalate suspicious activity reports directly into case management systems — all within seconds of transaction completion.
Agents execute scheduled model validation routines, compare live model outputs against benchmark thresholds, generate SR 11-7 compliant documentation, and notify model risk officers when drift or degradation is detected — autonomously and on a continuous basis.
Agents orchestrate the full underwriting workflow — pulling credit bureau data, verifying income documents, running decisioning models, checking regulatory eligibility criteria, and assembling the complete loan file — coordinating across five or more systems without manual handoffs.
Agents automatically collect, organize, and package audit evidence across systems for SOX controls testing. They map transactions to control objectives, identify exceptions, and produce auditor-ready documentation packages on demand or on schedule.
Agents autonomously execute KYC workflows — verifying identity documents, running PEP and sanctions screening, calculating risk ratings, and triggering enhanced due diligence when thresholds are met — coordinating across compliance, operations, and relationship management systems.
Traditional chatbots answer questions. Autonomous AI agents take action, reason over context, and deliver measurable outcomes.
ibl.ai deploys autonomous AI agents that go beyond simple Q&A. Our agents reason, plan, and execute multi-step workflows while you retain full code ownership and infrastructure control.
The entire platform runs within your controlled infrastructure with zero required external network calls. Deploy in fully isolated environments meeting the most stringent data residency and national security requirements. No cloud dependency, no external model APIs required.
ibl.ai collects no usage data, no model inputs, no outputs, and no behavioral telemetry. Customer data, financial records, and AI interactions remain exclusively within your infrastructure. This is architecturally enforced, not a policy promise.
Every agent action, tool call, data query, model invocation, and decision is logged with full context, timestamps, and actor identity. Audit logs are structured for regulatory examination, model risk review, and internal governance — queryable and exportable on demand.
Multi-tenant architecture enforces strict data and workflow isolation between business units, subsidiaries, and user roles. Compliance teams, risk officers, and operations staff access only the agents and data appropriate to their function — with full administrative control.
Because you own the complete source code, your security team can audit every line of the platform — no black boxes, no obfuscated dependencies, no trust-me assurances. Conduct penetration testing, code review, and vulnerability assessment on your own schedule.
Run open-source models like Llama or Mistral entirely on your own hardware. No prompts, no completions, and no financial data are ever transmitted to external model providers. Combine with air-gapped deployment for maximum data sovereignty.
Your security, compliance, and engineering teams receive the complete source code to review, audit, and validate. No black boxes. No obfuscated logic. Satisfy internal model risk management requirements and regulatory examiner inquiries with full transparency into how the platform operates.
Build proprietary workflows, integrate with internal systems, and extend platform capabilities without filing a feature request or waiting for a vendor roadmap. Your engineering team owns the codebase and can evolve it at the speed your business demands.
Run on AWS GovCloud, Azure Government, your private data center, or a fully air-gapped on-premises environment. The platform has no hard dependencies on any specific cloud provider or external service. You control the deployment architecture entirely.
SaaS vendors can change pricing, deprecate features, get acquired, or shut down. With full source code ownership, none of those scenarios affect your operations. The platform runs indefinitely on your infrastructure regardless of ibl.ai's future business decisions.
Regulators and boards increasingly require financial institutions to demonstrate control over critical technology. Source code ownership provides the evidence of control, auditability, and operational independence that examiners and directors expect for AI systems in regulated workflows.
ibl.ai delivers the complete source code and deploys the platform within your infrastructure — private cloud, on-premises, or air-gapped environment. We configure your chosen AI models, establish API integrations with your core systems, and validate the deployment against your security and compliance requirements. You own the code from day one.
Working alongside your compliance, risk, and operations teams, ibl.ai configures and builds the specific autonomous agent workflows your institution requires — regulatory monitoring, KYC orchestration, risk scoring, audit evidence packaging, or custom use cases. Your team learns the platform architecture throughout this phase.
Your engineers and operations staff take complete ownership of the platform. ibl.ai provides documentation, training, and transition support. From this point forward, your institution operates, modifies, and scales the platform independently — with no ongoing vendor dependency required to keep the system running.
Autonomous agents handling regulatory monitoring, evidence collection, and reporting workflows eliminate the majority of manual compliance labor hours — delivering measurable cost reduction in compliance operations headcount and contractor spend.
Agent-orchestrated underwriting workflows that coordinate across credit, income verification, compliance, and decisioning systems compress origination timelines from days to hours, directly improving pull-through rates and customer acquisition economics.
Automated evidence collection, control mapping, and exception identification by autonomous agents dramatically reduces the internal hours and external audit fees associated with annual SOX compliance testing cycles.
Agents that autonomously execute validation routines, monitor model drift, and generate SR 11-7 compliant documentation reduce the per-model governance burden, enabling risk teams to maintain oversight across larger model inventories without proportional headcount growth.
End-to-end KYC orchestration by autonomous agents — from document verification through risk rating and EDD triggering — eliminates manual handoffs and reduces the operational cost of onboarding institutional and retail clients across all business lines.
SOX requires financial institutions to maintain rigorous internal controls over financial reporting, with documented evidence of control execution and exception handling accessible to external auditors.
ibl.ai's autonomous agents generate complete, immutable audit trails for every action taken within financial workflows. Agents autonomously collect and package SOX control evidence, map exceptions to control objectives, and produce auditor-ready documentation — all within your air-gapped infrastructure where no evidence leaves your perimeter.
The Federal Reserve's SR 11-7 guidance requires financial institutions to maintain a robust model risk management framework including model validation, ongoing monitoring, and governance documentation for all models used in material decisions.
The platform's complete audit trail, model-agnostic architecture, and autonomous validation agents directly support SR 11-7 compliance. Every model invocation is logged with inputs, outputs, and context. Agents execute scheduled validation routines and generate governance documentation. Full source code ownership satisfies examiner requirements for transparency and control.
Bank Secrecy Act and Anti-Money Laundering regulations require financial institutions to maintain effective transaction monitoring programs, file Suspicious Activity Reports within prescribed timelines, and demonstrate the effectiveness of their compliance programs to examiners.
Autonomous agents continuously monitor transactions, apply configurable risk rules, cross-reference sanctions and PEP lists, and autonomously initiate SAR workflows when thresholds are met. All monitoring logic, decisions, and escalations are logged in a complete audit trail demonstrating program effectiveness to FinCEN examiners — with zero data leaving your infrastructure.
The Gramm-Leach-Bliley Act and an expanding set of state privacy regulations require financial institutions to protect customer financial information and maintain control over where that data is processed and stored.
Air-gapped deployment with zero telemetry ensures customer financial data is processed exclusively within your controlled infrastructure. No prompts, completions, or behavioral data are transmitted to external AI providers. Full source code ownership allows your legal and compliance teams to verify these properties architecturally, not just contractually.
See how ibl.ai deploys autonomous AI agents you own and control — on your infrastructure, integrated with your systems.