Protect sensitive data
Help keep protected values out of supported AI interactions before they leave the user environment.
VisIQ applies policy to supported AI interactions and agent workflows, helping security teams protect sensitive data before it leaves and evaluate actions before they execute.
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Control before the action. Tamper-evident receipts after it.
VisIQ harnesses Gemini, Microsoft Copilot, Claude, Perplexity, Claude Code, Cursor, OpenClaw, Codex, GitHub Copilot, Cline, OpenCode, LangChain, LlamaIndex, Vercel AI SDK, Mastra, VoltAgent, Semantic Kernel: every framework is governed inline, before execution.
AI DLP for the enterprise stack
VisIQ is designed to apply policy across browser AI, enterprise copilots, LLM and API traffic, desktop and local AI, agents, MCP, RAG, and multimodal workflows.
The security outcome
The hard part is not building agents. It is trusting them to take consequential actions without creating financial, operational, or compliance risk.
Help keep protected values out of supported AI interactions before they leave the user environment.
Evaluate supported retrievals and tool actions against policy before they execute.
Route configured sensitive operations for human review instead of hiding the decision path.
Keep decision records and supported tamper-evident evidence tied to policy and operation.
How VisIQ gets you there
Start with AI DLP at the point of use, then extend the same control model into supported agent data and action paths.
Context Firewall helps mask protected values before supported browser AI interactions are submitted.
Supported agent operations are evaluated against policy before they reach connected systems.
Decision records preserve what happened, why, and under which policy on supported workflows.
VisIQ Lab Services
VisIQ Lab Services helps enterprise teams design, build, integrate, and deploy agentic workflows, then put the right runtime controls around them from Day 1.
The install
VisIQ installs inside the agent you already have. Pick your framework and language, or wire a CLI agent from the terminal, and watch the status flip.
import { AgentExecutor, createOpenAIToolsAgent } from "langchain/agents"; import { ChatOpenAI } from "@langchain/openai"; const llm = new ChatOpenAI({ model: "gpt-4o" }); const agent = await createOpenAIToolsAgent({ llm, tools, prompt }); const executor = new AgentExecutor({ agent, tools }); const result = await executor.invoke({ input: "What was Q3 revenue?" });
See the VisIQ console and governance workflows with dummy data. No account required.
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Bring your architecture, agent workflows, and risk scenarios for a guided enterprise evaluation.
Ready to evaluate
Explore the full platform with dummy data, start free with your own pilot, or talk through an enterprise rollout.