Tumeryk Solutions for the Public Sector
1. AI POSTURE INTELLIGENCE
Problem It Solves
Security and risk teams lack visibility into the full scope of AI usage within their organisations. Unapproved tools proliferate across functions, AI assets are unregistered and unassessed, and risk exposure cannot be quantified because the AI surface area is unknown.
What It Does
AI Posture Intelligence provides real-time visibility into how AI tools, models, and agents are used across the government and enterprise. It discovers Shadow AI, maps the AI usage landscape, and continuously assesses risk exposure across all AI interactions - without requiring workflow disruption or intrusive enforcement.
How It Works
Tumeryk scans network traffic, endpoints, and application usage to identify all AI tools, models, and agents in operation. Discovered assets are catalogued in a centralised AI Asset Catalogue with ownership and usage mapping. Risk simulation and automated red teaming are then run against these assets to surface vulnerabilities. The AI Trust Score™ provides a continuously updated risk view across all catalogued systems.
Key Capabilities
- Shadow AI Discovery: identifies unapproved AI tools, models, and agents across network traffic, endpoints, and application usage
- AI Asset Catalogue: centralised inventory of AI models, tools, agents, and services with ownership and usage mapping
- AI Red Teaming: simulates adversarial attacks including prompt injection, hallucination exploitation, and unsafe output generation
- Risk Simulation and Scoring: evaluates AI systems across risk dimensions and generates continuous AI Trust Score(tm) insights
Business Impact
- Visibility: Real-time, comprehensive view of the enterprise AI surface including Shadow AI
- Risk prioritisation: Quantified risk scoring enables proportionate resource allocation
- Compliance: Audit-ready reporting for regulatory submissions and governance reviews
- Early detection: Vulnerabilities identified in simulation before real-world exploitation
2. WORKFORCE AI SECURITY
Problem It Solves
Employees interact with external AI tools at scale, without oversight. Sensitive government and enterprise data - client information, financial records, source code, and strategic content - is submitted to external AI systems without any organisational control, creating data loss, regulatory, and contractual exposure.
What It Does
Workforce AI Security provides a controlled access and monitoring layer for all employee AI interactions. It governs how tools such as ChatGPT, Copilot, and Claude are accessed and used across the workforce - monitoring prompts and responses, enforcing data handling policies, and preventing sensitive information from reaching unauthorised AI systems.
How It Works
A lightweight agent layer is deployed across browsers and devices (via MDM integration) to intercept and inspect AI interactions in real time. Policies define which tools are approved, which data categories may not be submitted, and what response content triggers enforcement. Usage analytics are aggregated into dashboards for compliance and HR teams, with audit-ready exports for regulatory reporting.
Key Capabilities
- Secure Chatbot Access: policy-based, role-controlled access to approved AI tools across the workforce
- Browser Protection: real-time monitoring of prompts and responses, with sensitive data exposure prevention
- Data Loss Prevention: blocks confidential government and enterprise data from being shared with unauthorised AI systems
- CodeRails for Developers: enforces guardrails on AI-generated code and developer tool interactions
- MDM Integration: extends governance to mobile devices and endpoint-managed environments
Business Impact
- Data protection: Prevents sensitive information from exiting the government and enterprise via AI tool usage
- Compliance: Demonstrates controlled AI usage for GDPR, DPDP, and sector-specific obligations
- Workforce enablement: AI adoption continues without security teams having to block tools wholesale
- Audit readiness: Full interaction logs and policy enforcement records available on demand
3. AGENTIC AI GOVERNANCE
Problem It Solves
Autonomous AI agents can independently access data, invoke APIs, and take consequential actions across government and enterprise systems - often without human oversight or approval. Unlike conversational AI, errors or policy violations by agentic systems can propagate at machine speed, creating irreversible business, regulatory, and reputational harm.
What It Does
Agentic AI Governance provides a real-time trust, governance, and security layer for autonomous AI systems. Every agent action, decision, and outcome is continuously assessed against security, compliance, and policy parameters. The platform enables consistent governance across AI agents, copilots, and multi-agent orchestration workflows.
How It Works
Tumeryk integrates into the agent execution environment - including Kubernetes-based deployments via the Nemo Claw runtime - as a governance and control plane. A Unified Policy Management layer combines Open Shell policies and Nemo Guardrails into a single governance interface. The AI Trust Score™ Controller evaluates agent interactions in real time, controlling access to external tools, data sources, foundation models, and RAG providers based on contextual trust scoring.
Key Capabilities
- Agent Access Control: policy-based control over agent permissions, execution paths, and approved actions
- Runtime Guardrails: automated enforcement preventing unsafe actions, data misuse, or unintended behaviour during execution
- Observability: real-time inspection of agent decisions and outcomes to detect non-compliant or off-policy behaviour
- Model Risk Audit: ongoing red teaming, testing, and audit-ready visibility into foundational AI models
- Multi-cloud support: governance across agentic AI workloads on AWS, Azure, GCP, and hybrid environments
Business Impact
- Control: Prevents unauthorised agent execution paths and autonomous actions outside defined boundaries
- Accountability: Immutable audit trail of every agent decision and action for regulatory and legal purposes
- Incident prevention: Real-time detection and blocking of unsafe or unintended agent behaviour before harm occurs
- Scale: Governance maintains integrity as agentic deployments grow across the government and enterprise