Case, citizen and program systems
Service portals, case management, grants, permits, benefits, registry data, correspondence, and contact-centre records.
Private AI for government agencies runs language models, retrieval and agents on infrastructure the agency controls, whether on-premise, in a sovereign cloud or in an air-gapped enclave, so citizen records and mission data never need to reach a commercial AI service. VDF.AI sits above the government, public-sector, and defense systems you already run and coordinates agents for citizen services, records, intelligence, planning, compliance, grants, permits, and incident response. No foreign-cloud dependency. No unmanaged data egress. Every source, clearance gate, approval, and output logged.
Case systems, records, citizen portals, intelligence feeds, policy libraries, logistics data, security signals, and oversight obligations stay where they are. VDF.AI reads the mission context, applies classification and authority boundaries, activates the right agents and tools, and returns evidence with the work.
VDF.AI · sovereign AI · model agnostic · air-gapped capable · any LLM · any stack
Service portals, case management, grants, permits, benefits, registry data, correspondence, and contact-centre records.
Document management, archives, scanned forms, policy libraries, evidence bundles, retention schedules, and handling labels.
Open-source intelligence, internal reports, geospatial layers, operational updates, threat feeds, SIEM alerts, and analyst notes.
Readiness, staffing, assets, procurement, supply, facilities, fleet, GIS, ERP, and scenario assumptions.
Statutes, executive directives, NIST controls, NATO guidance, EU AI Act obligations, FOIA rules, audit findings, and parliamentary questions.
Set the target: reduce permit backlog, prepare intelligence briefs faster, classify records consistently, improve grant review fairness, or assemble audit evidence.
Apply classification, clearance, need-to-know, legal basis, retention, egress, human approval, and model-route policies before any agent acts.
The platform ranks actions by mission impact, citizen experience, backlog reduction, legal authority, classification, evidence strength, operational risk, and required human approval.
Answer service questions, check eligibility, draft responses, route escalations, and keep citizen data inside the public-sector boundary.
Read documents, classify handling level, propose redactions, assemble evidence bundles, and preserve chain of custody.
Correlate source material, signals, timelines, and asset context into cited briefs that remain analyst-controlled.
Map policy obligations, draft control documentation, compile public accountability packs, and route sign-off tasks.
Runs in connected, sovereign, disconnected, or air-gapped footprints with approved models, local embeddings, and controlled tool access.
Stores source, retrieval, classification, model route, approval, output, disposition, and reusable institutional learning.
Grounded answers, drafted correspondence, eligibility checks, and escalations completed with accountable review.
Documents read, labelled, redacted, routed, retained, and logged under handling policy.
Signals and reports correlated into cited briefs with confidence, source, and analyst review status.
Resource, logistics, readiness, scenario, and risk information assembled for decision forums.
Policy changes, controls, approvals, and evidence compiled from primary sources.
Every source, classification gate, approval, model route, and output is inspectable by oversight teams.
VDF.AI starts with the public-sector or mission outcome, then coordinates agents, tools, approvals, and evidence so teams can move faster without losing control.
Connect case management, records, intelligence, logistics, GIS, ERP, security, policy, and citizen-service systems without migrating sensitive or classified data.
Zero rip-and-replaceReduce permit backlog, accelerate intelligence brief preparation, classify records consistently, improve grant-review fairness, or assemble oversight evidence from primary sources.
Objective-first executionThe control plane selects document, search, policy, risk, record-keeping, communications, and planning agents only where clearance, need-to-know, data class, and approval policy allow.
Staged autonomy by workflowThe platform records sources, retrievals, tool calls, model routes, classification gates, approvals, outputs, and dispositions while retaining mission knowledge for future workflows.
Auditable at executionPublic-sector and defense work spans mission systems, sensitive records, legal authority, national policy, citizen trust, and oversight. AI must coordinate execution across that estate while preserving accountability at every step.
Case management, records, intelligence, logistics, GIS, policy, and security systems each hold part of the picture. Teams stitch context together manually before they can act.
Access depends on role, clearance, compartment, legal basis, mission, data class, and handling rule. A generic assistant cannot safely cross those boundaries.
Permits, grants, records, benefits, citizen correspondence, compliance reviews, and operational planning cycles absorb capacity while public expectations keep rising.
Oversight bodies need to know what happened, why it happened, who approved it, and which source justified it. Evidence has to be created during execution, not reconstructed later.
No migration
The agentic layer connects what already works.
VDF.AI connects to case management, document repositories, citizen portals, intelligence platforms, GIS, logistics, ERP, SIEM, SOAR, GRC, records, and bespoke classified systems through governed tools. Data remains inside your approved infrastructure; agents receive only the scoped access required for the objective.
Large public-sector system replacement is slow, costly, and risky. A governed control plane starts above existing systems, proves value in one workflow, then expands across the operating model.
Control plane above existing mission and public-sector systems
Objective engine
The plan is ranked by impact, authority, risk, evidence, and review path.
Examples of objective-first government execution:
Mission · service · oversight · resilience
Staged autonomy
Each public-sector process gets the boundary it deserves.
VDF.AI lets agency, defense, security, records, and compliance leaders define autonomy at the process level:
Assistive · delegated · autonomous · escalated
Each workflow combines a defined agent pattern with the tools needed to retrieve evidence, enforce permissions, redact sensitive data, verify sources, request approval, generate records, and export the audit trail.
Answers citizen questions, drafts next steps, and escalates complex cases while keeping data in government infrastructure.
Reads scanned and digital records, assigns handling levels, proposes redactions, routes documents, and logs rationale.
Correlates source material, signals, reports, and precedent into cited briefs with confidence and attribution.
Synthesizes logistics, resources, risk, readiness, and scenarios into planning packs for human decision forums.
Tracks regulation, policy, and control changes, maps obligations, and drafts evidence-backed compliance packs.
Searches policies, procedures, precedents, and internal knowledge with role-scoped retrieval and cited answers.
Checks applications against code, zoning, missing evidence, and approval rules before officials decide.
Screens eligibility, maps evidence to criteria, flags completeness gaps, and supports consistent reviewer packs.
Ingests advisories and internal signals, maps them to assets, and produces prioritized, actionable briefings.
Surfaces runbooks, summarizes logs into timelines, and drafts response records while responders keep control.
| Control area | VDF AI posture |
|---|---|
| Air-gapped deployment | Supported |
| Sovereign infrastructure | On-premise, sovereign cloud, disconnected enclave |
| External runtime calls | Not required |
| Classification controls | Role, clearance, compartment, and data-class scoped |
| Identity | Entra ID SSO built in; CAC/PIV, SAML, LDAP, and custom federation through your SSO proxy; MFA at the IdP |
| Audit evidence | Immutable logs with SIEM and evidence exports |
| Human approval | Required per workflow policy |
| Data protection | Local redaction, permission checks, and retention controls |
VDF.AI is assessed as part of your system, inside the boundary you authorize, rather than under an authorization of its own. Specific national security, procurement, and accreditation packages depend on the deployment environment, jurisdiction, and classification boundary. Defense contractors can check how CMMC and DFARS 7012 apply to AI tools.
| Requirement | VDF AI Capability |
|---|---|
| Deployment model | On-premise, sovereign cloud, disconnected site, or fully air-gapped enclave |
| System posture | Overlay architecture above case management, records, document management, citizen portals, intelligence systems, GIS, ERP, SIEM, SOAR, GRC, and custom classified applications |
| Data sovereignty | Models, embeddings, prompts, retrieval indexes, tool calls, orchestration telemetry, audit logs, and generated outputs remain under sovereign legal and physical control |
| Private RAG | Policy libraries, case files, records, operational reports, intelligence notes, procedures, statutes, and technical manuals retrieved only inside approved enclaves |
| Role-based access | Agents, tools, knowledge, outputs, and workflows scoped by role, clearance, compartment, mission, data class, and need-to-know rule |
| Model routing | Policy-directed routing among approved local or sovereign model tiers by classification, task sensitivity, confidence need, latency, and cost |
| Autonomy controls | Assistive, delegated, autonomous, and escalated modes configured per workflow, authority level, data class, and approval policy |
| Audit logs | Immutable records for objective, requester, sources, retrievals, tool calls, model route, classification gates, approvals, output, and disposition |
| Integration examples | ServiceNow, records management, citizen portals, document stores, GRC systems, SIEM/SOAR, GIS, ERP, identity federation (SAML/LDAP, CAC/PIV) through your SSO proxy, and classified connectors via MCP/API |
| Encryption | AES-256 at rest, TLS 1.3 in transit, customer-managed keys, and deployment-specific key separation |
| Operations | High-availability clustering, backup and restore, offline update packages, health monitoring, and SIEM export |
| Procurement evidence | Architecture documentation, security documentation, SBOM support, control mapping, and deployment-specific compliance packs |
VDF AI is available through:
Contact our government team for procurement guidance specific to your jurisdiction, accreditation boundary, and deployment model.
On-premise AI for government puts the language models, retrieval and agents on servers the agency or ministry operates, so no commercial AI provider ever handles citizen records or mission data. Fully on-premises and air-gapped deployment lets public bodies and defense organizations adopt AI agents while sovereignty, classification and public accountability stay in their own hands.
For agency CIOs, CISOs, digital transformation leads, and security officers in government and defense.
A strategic procurement brief for regulated government & public sector environments.
Sovereign, air-gapped AI for agencies and defense.
No. VDF.AI sits above the systems government and defense teams already operate. Case management, records repositories, document stores, intelligence platforms, logistics systems, GIS, ERP, SIEM, SOAR, and classified applications remain the systems of record. The control plane coordinates agents and tools across them under your access, classification, and audit policies.
Yes. VDF.AI can run on-premise, in a sovereign cloud, in a disconnected enclave, or in a fully air-gapped environment. Models, embeddings, prompts, tool calls, logs, and generated outputs stay inside the approved boundary. Updates can be delivered as signed offline packages through your own channels.
Agents, tools, retrieval sources, outputs, and approval paths can be scoped by user role, mission, compartment, classification label, clearance, and need-to-know rule. Every run records who asked, what sources were retrieved, which model was used, which policy gates fired, and who approved consequential output.
Yes. VDF.AI supports staged autonomy by workflow. Citizen answers and records processing can be delegated under strict policies, intelligence and operational planning can remain assistive with analyst or commander review, and irreversible or public-facing actions can require named human approval.
Yes. VDF.AI installs on servers the agency operates, in a sovereign cloud tenancy it controls, or in a disconnected enclave, and serves open-weight models locally. Prompts, documents, embeddings, tool calls and logs stay on that infrastructure, so no commercial AI provider processes agency data and there is no outside inference service to add to your security assessment.
No. VDF.AI is software you deploy inside an environment you already authorize: an on-premise enclave, a FedRAMP High or IL5 cloud tenancy your agency uses, or an air-gapped network. Your team assesses it as a component of your own system under your ATO, and VDF.AI supplies the architecture and security documentation, SBOM and control mappings that assessment needs.
Yes, through your identity provider. On-premises deployments use Microsoft Entra ID single sign-on natively and map Entra security groups to roles, so a CAC or PIV login completed at your IdP carries into VDF.AI. Other SAML or OIDC providers connect through an SSO-aware reverse proxy. Role-based access control then applies roles, permission groups and per-role tool grants.
Start with one objective: citizen services, document classification, intelligence analysis, operational planning, compliance monitoring, permit processing, grant review, or incident response.