Enterprise RAG assurance,
scoped around your risk.
HardRAG does not force a one-size-fits-all price table. Engagements are shaped by your data handling model, audit requirements, deployment constraints, and production timeline.
Audit Readiness Assessment
For teams preparing a RAG or LLM workflow for production, compliance review, or executive approval.
- Pipeline risk and hallucination review
- PII/PHI exposure assessment
- Policy and governance gap report
- Audit evidence roadmap
- Architecture recommendations
Managed Guardrail Pilot
For teams ready to validate guardrails, policy checks, and audit trails in a live or pre-production environment.
- Inference validation workflow
- PII masking and policy enforcement
- Audit dashboard configuration
- Monthly evidence reporting
- Pilot success criteria and rollout plan
Enterprise / Sovereign Deployment
For regulated organizations requiring private cloud, on-premise, or air-gapped deployment with stronger assurance.
- Private cloud or on-prem architecture
- Air-gapped local LLM support
- Custom policy authoring
- SLA and security assurance
- Executive and audit-ready reporting
From first review to defensible production.
The recommended path is assessment-led: prove the risk, define the controls, then decide whether a managed pilot or private deployment is the right next step.
Discovery
Understand your RAG stack, data sensitivity, regulatory exposure, and production goals.
Assessment
Map hallucination, privacy, policy, and auditability gaps into a clear evidence report.
Pilot
Validate guardrails in a controlled environment with measurable success criteria.
Deployment
Scale into managed, private cloud, on-premise, or air-gapped operations as needed.
Open-Core Community
The public codebase supports technical trust, evaluation, and local experimentation. Enterprise assurance, implementation guidance, and private deployment are scoped separately.
Secure Your
Sovereign AI Era.
Audit your existing retrieval models, detect compliance vulnerabilities, and build verifiable trust into your generative AI architecture.