Accelerating Enterprise Intelligence
while safeguarding your sovereign data
Empowering businesses on their safe and human-centered journey to a native AI Enterprise
Why Shiva-AI
Generative AIs most useful business application - answering questions about your private corporate data, drafting from your records, summarizing across your documents - requires sending your content to a model for interpretation. Often employees are sending data to a third-party AI application operated by someone you do not have a business agreement with, hosted in a jurisdiction you may not control, running on an infrastructure you cannot inspect.
Unless you want to give up your intellectual property, sending material non-public information (MNPI) to a third-party to process, and hoping for the best, is a doomed strategy.
With Shiva-AI's Citorum platform, your biggest concerns are addressed. Corporate data stays inside the environment you control. Inference runs on infrastructure you control. Every answer is independently audited for truthfulness, resulting in auditable plain-language labels of validity. Every retrieval, prompt, response, and confidence score is logged with chain-of-custody metadata. See the architecture →
Flexible Deployment Models
Aligns with your IT Strategy.
On-premises
On your hardware in your data center. Everything lives entirely inside your firewall. Call outs are minimized to opt-in aggregated telemetry.
Virtual Private Cloud
Inside your Virtual Private Cloud (VPC) — Amazon Web Services, Microsoft Azure, Google Cloud Platform, or Oracle Cloud Infrastructure. Single-tenant.
Citorum Managed Cloud
Your single-tenant deployment, operated by Citorum in a managed cloud account. Documented privileged-access controls.
The Truth Meter builds Confidence
Unlike other AI models. Citorum never presents unverified output as authoritatively truthful. With every answer to a user query, Citorum scores it against the sources it was drawn from, combining multiple grounding signals by Shiva-AI's proprietary judge, and assigns one of three labels.
- Verified - Factual sources support the model's answer assertions. It is safe to act on, with citations.
- Review - The model's answer is plausible, but is judged as unverifiable. Inspection by a human is recommended.
- Unreliable - The data sources do not support the answer, or contradict the assertions made by the model.
The Truth Meter rides alongside every answer, building user confidence and removing hallucinations doubts. The truth is known in real time, building confidence in the dependent processes, downstream workflows, reviewers and auditors. How adjudication works →
Built for regulated industries
Offering Security, Privacy and Trust
Legal
Discovery, contract review, and regulatory research with chain-of-custody preserved across every retrieval and response.
Healthcare
Clinical reference, claims analysis, and HIPAA-aware document workflows under a Business Associate Agreement (BAA).
Financial Services
Customer-file research, regulatory reporting, and material non-public information (MNPI) handling that satisfies SOX and the rest of the audit perimeter.
Public Sector
Federal, state, and local programs where data residency, the Federal Risk and Authorization Management Program (FedRAMP) trajectory, and audit are non-negotiable.
Compliance & Regulated Operations
SOX, the Payment Card Industry Data Security Standard (PCI DSS), the European Union's General Data Protection Regulation (GDPR) — risk teams running RAG over the policy and control documents the audit hangs on.
Ready when your security team is.
The Security & Architecture Whitepaper covers the threat model, controls inventory, key management, and incident response. Our engineering team takes the rest.