AI Runtime Control & Enforcement for AI Agents | Vaikora
AI Runtime Control & Enforcement for AI Agents
Vaikora is the AI runtime control and AI security platform for AI agents, copilots, and LLM-powered systems. It sits inline between AI systems and the actions they execute, enforcing deterministic decisions (allow / block / constrain) and producing audit-grade receipts for every action.
Vaikora brings real-time AI security and runtime control to protect APIs, data, and agent-driven workflows.
Open-source MCP Data Proxy for instant adoption. Enterprise control plane for attribution, approvals, and compliance.
Control What AI Does — Before It Does It
- AI is no longer “generating text.” It’s calling tools, moving data, and triggering real workflows.
- Monitoring and post-event alerts are too late. You need a layer that can intercept every action, evaluate risk in real time, and enforce a deterministic decision before anything executes.
This approach transforms traditional AI security into real-time control at the moment of execution.
AI is acting. Vaikora decides in real time.
What We Offer
Two Products, One System
MCP Data Proxy (Open Source)
- Drop-in proxy for MCP servers and agent tool calls
- Deterministic allow / block / constrain
- Policy packs: secrets redaction, tool allowlists, egress controls
- Local receipts + simple dashboards for fast debugging
Vaikora Control Plane (Enterprise)
- Agent activity attribution (who/what did what, with ownership)
- Central policy lifecycle: versioning, rollout/rollback, approvals
- Audit retention + exports (SIEM/OTel/log pipelines)
- Managed intelligence connectors + reliability controls (timeouts, caching, fail posture)
What You Get
A Firewall for AI Execution — Plus Receipts You Can Prove
Deterministic runtime enforcement
Evaluate every AI request in real time to enforce AI security policies before execution.
Constrain mode (not just allow/block)
Rewrite or restrict actions safely: redact secrets, clamp parameters, rate-limit, require approval.
Receipts + audit-grade evidence
Produce a receipt for every action: what was requested, what was decided, why, and what was enforced.
Inline control across MCP + API egress
Control MCP tool calls and outbound webservice traffic from one enforcement plane.
Intelligence-enriched decisions
Enrich decisions with semantic/intent risk and infrastructure reputation (IP/ASN) via pluggable TI connectors.
How AI Runtime Control Works
Enforcement Happens Before Execution — Not After
AI runtime control ensures every action is evaluated and enforced as part of a real-time AI security model.
Intercept
AI requests route through Vaikora / MCP Data Proxy, creating a single control point before tools, APIs, databases, or external services are reached.
Normalize & Enrich
Vaikora normalizes each request into a canonical event and enriches it with intent and semantic risk signals, as well as destination intelligence such as IP, ASN, and domain reputation.
Decide (Deterministic)
A deterministic policy engine evaluates the request and returns a clear outcome — allow, block, or constrain — based on defined policies and real-time context.
Enforce
Vaikora applies the decision instantly, blocking unsafe actions, constraining risky behavior, or allowing safe execution to proceed without disruption.
Receipt + Visibility
Every action produces a receipt for debugging, auditing, and governance—exportable to your logging/security stack.
Cloud-deployed
Deploy through the cloud in one day. Immutable journaling source for G Suite, Exchange, Hybrid Exchange, and O365 deployments.
Use Cases
Runtime Control Across the Systems AI Touches
Real-time AI security across agents, APIs, and data workflows.
AI Agents & Automation
Control tool/API access in real time. Prevent unsafe actions before execution.
Customer Support Bots
Block data leakage and unsafe behaviors with inline enforcement and redaction.
RAG & Web Pipelines
Constrain retrieval, validate external content, and reduce prompt injection exposure.
AI Code Assistants
Restrict commands, protect repos, and require approvals for high-risk operations.
Fintech & Banking
Enforce transaction controls and protect sensitive financial workflows.
Healthcare & MedTech
Protect PHI with runtime enforcement + receipts for regulated audits.
Legal & Compliance
Ensure privileged content handling and maintain defensible records of AI actions.
E-commerce & Retail
Prevent fraud and constrain automation workflows safely.
Competitor Comparison
Why Vaikora by Data443
Monitoring tells you what happened. Vaikora ensures AI security by enforcing decisions before execution, and produces receipts you can prove.
| Capability | Vaikora | AI Governance | AI Security | DLP / CASB | SIEM |
|---|---|---|---|---|---|
| Inline enforcement before execution | Yes ✅ | No | Limited | Limited | No |
| Deterministic allow/block/constrain | Yes ✅ | No | Limited | No | No |
| Agent tool call control (MCP + non MCP) | Yes ✅ | No | Limited | No | No |
| Constraint engine (rewrite/limit/approve) | Yes ✅ | No | Limited | No | No |
| Receipts (replayable action evidence) | Yes ✅ | No | No | No | No |
| Threat intel enriched decisions (intent + IP/ASN) | Yes ✅ | No | No | No | Limited |
AI Runtime Control & Enforcement FAQs
What is AI runtime control?
AI runtime control is a modern AI security approach that evaluates and enforces decisions on AI actions in real time – before execution. Vaikora does this deterministically and produces receipts for every action.
What decisions can Vaikora enforce?
Vaikora returns deterministic outcomes: ALLOW, BLOCK, or CONSTRAIN (rewrite/limit/require approval).
Does this work with MCP?
Yes. Use the MCP Data Proxy (open source) to protect MCP tool calls (including local stdio and remote HTTP transports), and use Vaikora to extend governance across broader API/tool traffic.