Google Workspace
Govern Drive, Gmail, and Calendar access through policy-gated connections instead of granting every AI agent broad workspace permissions.
Secure agent workflows
Secure agent workflows for Google Workspace, Discord, and sandboxed AI agents.
botYguard helps teams run secure agent workflows where AI agents can use governed productivity data, team chat, Anthropic web-agent-style clients, or GCP hosted AI agents without receiving unchecked access to tools, secrets, or private context.
Each workflow keeps the useful parts of agent automation while moving the trust decision into botYguard. The platform evaluates scope, applies approvals, manages redaction, and records audit trails before sensitive actions become operational risk.
Supported today
Integrations and runtimes for secure AI agent workflows.
A secure agent workflow starts with the systems an agent needs to touch. botYguard currently centers on Google Workspace, Discord, governed external agents, and sandboxed hosted agents so teams can adopt agentic workflows without moving secrets into prompts.
The same control pattern applies whether the work starts in chat, in an external client, or in a managed runtime. The agent asks for a capability, botYguard checks the policy, and only the approved operation continues.
Discord
Use team chat for mediated requests, approval workflows, slash-command redaction, and rehydrated responses that keep sensitive terms away from the agent.
External web agents
Route Anthropic or other web-agent-style workflows through botYguard governance where an external agent needs controlled tool access and auditable decisions.
Sandboxed hosted agent
Deploy a botYguard-managed AI agent in its own GCP sandbox when your team wants an isolated runtime with governed access to tools and secrets.
Choose the runtime
External agent or sandboxed hosted agent.
Teams can connect an existing external agent through botYguard when they want to keep their current workflow but add policy enforcement, approvals, redaction, and audit records. This is the right path for MCP-capable agents or Anthropic web-agent-style workflows that should not hold raw provider keys or integration credentials.
When the runtime should be managed by botYguard, a hosted AI agent can run in its own GCP sandbox. The sandboxed AI agent still goes through botYguard governance before using connected SaaS apps, provider credentials, or downstream tools.
This lets teams choose the deployment model that matches the work. A lightweight research workflow might connect through an external client, while a repeatable internal process can run as a sandboxed hosted agent with a narrower set of approved capabilities.
Policy protects the workflow
Every sensitive action passes through governance.
botYguard policy enforcement decides whether a secure agent workflow can read a Drive file, summarize a Gmail thread, post through team chat, pass a provider key, or continue to a downstream tool. Approval workflows can pause higher-risk actions before side effects occur, while secret protection keeps credentials out of the agent instructions.
The result is a workflow that can still move quickly. Read-only work can run with a focused policy, requests that change data can require approval, and every decision can be reviewed later without relying on the agent to explain itself.
- Identify the agent profile, runtime, and requested workflow.
- Check policy enforcement rules for the integration, resource, and action.
- Apply approval workflows before sensitive writes, shares, or side effects.
- Pass only approved secrets, provider keys, and integration context.
- Record audit trails for the request, decision, approval, and result.
Example secure workflow
Govern a research agent across productivity apps and chat.
A team can connect Drive, Gmail, and Calendar, assign a narrow read-only policy, use chat for mediated requests, and require approval before any write or share action. The AI agent completes useful work, but botYguard records audit trails for the request, policy decision, approval result, secret access, and final response.
This gives the organization a clear path to expand. After the first secure agent workflow is proven, teams can add more folders, channels, actions, and agent profiles while keeping the same governance model for approvals, redaction, secret handling, and audit trails.
The result is a practical adoption path: start with one safe request, inspect the evidence, then broaden access only when the workflow and its controls are understood. That keeps the rollout measurable for security teams and useful for the people asking agents to help.