Full source code ownership. Air-gapped deployment. Autonomous agents that reason, act, and execute — inside your classified perimeter, with zero external dependencies.
ibl.ai is a production-grade AI platform — not a proof of concept, not a consulting engagement. It is a complete, deployable system with 1.6M+ users across 400+ organizations, delivered to defense and intelligence customers as full source code they own outright.
For defense departments, intelligence agencies, and military organizations, the deployment model matters as much as the capability. ibl.ai runs entirely on your infrastructure — on-premise, in a secure enclave, or on a classified network — with no telemetry, no callbacks, and no external dependencies of any kind. If the internet disappears, the platform keeps running.
Beyond secure deployment, ibl.ai delivers autonomous AI agents — not chatbots. These agents monitor threat feeds, analyze classified documents, coordinate multi-step workflows, execute code, query databases, and produce actionable intelligence outputs. Every action is logged in a complete, immutable audit trail reviewable by your security and compliance teams.
1.6M+ active users across 400+ organizations including NVIDIA, Kaplan, and Syracuse University. This is not a pilot — it is a hardened, battle-tested platform delivered to your environment.
You receive the complete codebase. No SaaS subscription, no license keys, no runtime dependencies on ibl.ai infrastructure. Your team can audit, modify, extend, and redeploy every line.
Designed from the ground up for disconnected, classified, and sovereign environments. Zero external API calls, zero telemetry, zero data egress. Runs indefinitely without vendor contact.
Deploy with Claude, GPT-4, Gemini, Llama, Mistral, or your own fine-tuned models. Swap or run multiple models simultaneously. No dependency on any single AI provider.
Once delivered, the platform is yours. No renewal gates, no feature paywalls, no forced upgrades. If you never call ibl.ai again, every agent, workflow, and integration keeps running.
Every capability is accessible via RESTful APIs. Model Context Protocol (MCP) connects agents to classified databases, internal tools, and mission systems without exposing data externally.
Autonomous agents continuously ingest classified threat feeds, OSINT sources, and internal reporting. They correlate signals, identify patterns, and generate structured intelligence briefs — without analyst prompting. Agents escalate anomalies based on configurable risk thresholds.
Agents autonomously process captured documents, foreign-language materials, and unstructured data at scale. They extract entities, relationships, and actionable intelligence, then route findings to the appropriate analyst queues or downstream systems via API.
MentorAI-powered agents deliver adaptive, mission-specific training to personnel across classifications. Agents assess competency gaps, assign remediation, track completion, and issue verifiable credentials — all within the classified environment.
Agents orchestrate multi-step operational workflows across systems — querying databases, triggering downstream processes, logging decisions, and notifying stakeholders. They execute complex, conditional logic autonomously without human intervention at each step.
Agents continuously monitor system activity, user access patterns, and data handling against defined policy rules. They flag violations, generate compliance reports, and maintain immutable audit logs — proactively, not reactively.
Agents index, classify, and surface institutional knowledge from classified repositories, after-action reports, and SOPs. Personnel query agents in natural language and receive sourced, contextual answers — with full document provenance tracked.
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 platform is designed to operate with zero external network dependencies. No license servers, no telemetry endpoints, no model API calls leave your perimeter. Deploy on SCIFs, classified networks, or fully disconnected environments and operate indefinitely.
ibl.ai collects no usage data, no behavioral analytics, no performance metrics from your deployment. The source code is fully auditable so your security team can verify this independently. No hidden callbacks, ever.
Every agent action, tool invocation, data access, user interaction, and system decision is logged with full context — who, what, when, and why. Logs are stored on your infrastructure and are tamper-evident, supporting insider threat detection and compliance reviews.
Multi-tenant architecture with granular, role-based access control enforced at every layer. Users, agents, and systems access only what their clearance and role permit. Supports classification-level isolation within a single deployment.
Runs on your hardware, your hypervisors, and your approved cloud regions — including GovCloud, C2S, and SC2S environments. No dependency on commercial SaaS infrastructure. Compatible with existing PKI, SSO, and identity management systems.
Because you own the full source code, your security team or a cleared third-party assessor can conduct a complete code review before deployment. No black-box components, no obfuscated dependencies, no trust-me-it's-secure claims.
Your cleared security engineers receive the complete codebase prior to deployment. Conduct a full static analysis, dependency review, and security assessment. No black-box components, no compiled-only binaries, no hidden logic.
Defense and intelligence missions evolve. With full source code, your development team can modify agent behaviors, add classified data connectors, implement custom workflows, and extend the platform without waiting for vendor approval or release cycles.
Deploy on-premise in a SCIF, on a classified cloud region, on an air-gapped network, or across multiple environments simultaneously. The platform has no infrastructure opinions — it runs where your mission requires.
Vendor relationships end. Contracts expire. Companies get acquired. With full source code ownership, your platform continues operating regardless of ibl.ai's future. No renewal gates, no forced migrations, no operational risk from vendor changes.
Full source code ownership directly supports SCRM (Supply Chain Risk Management) requirements. Your team controls every dependency, can pin versions, and can rebuild from source — eliminating third-party software supply chain risk.
ibl.ai delivers the complete platform source code, documentation, and deployment tooling to your team. We work with your infrastructure and security teams to configure the environment — on-premise, air-gapped, or classified cloud — and validate the deployment against your security requirements.
Our engineers work alongside your team to configure agents for your specific mission workflows, integrate with your classified data sources and internal systems via MCP and APIs, and build any custom capabilities required. Your team learns the codebase throughout this phase.
Your team takes the platform to production. You own the code, the infrastructure, and the operational capability. ibl.ai is available for ongoing support and development, but the platform runs indefinitely without us. No dependency, no lock-in, no ongoing vendor requirement.
Autonomous agents handle document exploitation, data synthesis, and routine reporting — freeing analysts to focus on high-judgment tasks. Organizations report 3–5x throughput increases in intelligence production workflows.
Adaptive AI tutoring agents deliver personalized, mission-specific training at scale. Personnel reach operational readiness 35–50% faster compared to traditional instructor-led or static e-learning programs.
Automated audit trail generation, continuous policy monitoring, and AI-assisted compliance reporting reduce the labor cost of audit preparation and ongoing compliance management by 60–70%.
Full source code ownership eliminates perpetual SaaS licensing fees, per-seat costs, and vendor dependency. Organizations with 500–5,000 users typically eliminate $500K–$5M+ in recurring AI platform licensing costs over a five-year horizon.
Autonomous agents eliminate manual coordination steps in recurring operational workflows — status reporting, data aggregation, notification routing, and escalation management — reducing labor overhead by 60–80% on targeted processes.
International Traffic in Arms Regulations and Export Administration Regulations govern the handling of defense-related technology and data. AI platforms processing controlled technical data must ensure no unauthorized export — including to foreign cloud infrastructure.
Air-gapped deployment ensures all data, model weights, and processing remain within your controlled environment. Full source code ownership allows your legal and compliance teams to verify no data egress paths exist. Zero telemetry is auditable at the code level.
The NIST Risk Management Framework and SP 800-53 control catalog are the foundation of ATO (Authority to Operate) processes for federal and defense systems. AI platforms must satisfy controls across access control, audit, configuration management, and system integrity.
Complete audit trail logging satisfies AU control families. Role-based access control and multi-tenant isolation address AC controls. Full source code enables configuration management and integrity verification required for ATO documentation and assessment.
DoD and CISA mandate Zero Trust Architecture principles for new system deployments — never trust, always verify, assume breach. AI platforms must enforce least-privilege access and continuous verification at every layer.
ibl.ai's multi-tenant architecture enforces role-based access at every API and agent layer. Every agent action is authenticated, authorized, and logged. The API-first design integrates with existing ZTA identity and access management infrastructure including CAC/PIV authentication.
Cybersecurity Maturity Model Certification requirements apply to defense contractors and their supply chains handling Controlled Unclassified Information (CUI). AI systems processing CUI must meet CMMC Level 2 or Level 3 controls.
On-premise deployment keeps CUI within your accredited boundary. Immutable audit logs support CMMC audit and accountability requirements. Source code ownership enables the configuration management and documentation required for CMMC assessment and certification.
See how ibl.ai deploys autonomous AI agents you own and control — on your infrastructure, integrated with your systems.