What Autonomous AI Agents Do
OmniGate’s AI agents are software programs powered by large language models (LLMs) that can plan, reason, and take multi-step actions without a human approving every individual step. You define a goal; the agent figures out how to accomplish it.
In practice, agents can read data from connected services, draft content, trigger API calls, generate reports, and hand off tasks to other agents — all within the boundaries you configure.
API & Integration Access
Agents interact with connected tools (GitHub, Gmail, CRMs, databases) using the credentials you authorize — and only those.
LLM Reasoning
Each step is processed by an LLM (currently Anthropic Claude) that interprets context, selects the next action, and produces outputs.
Multi-Step Execution
Agents can chain dozens of actions in a single run, including calling sub-agents and branching based on intermediate results.
Persistent Memory
Agents store execution logs, generated reports, and task history so they can reference past context in future runs.
Your Governance Controls
Autonomous does not mean unaccountable. OmniGate is built with layered controls so you can see exactly what agents are doing, override decisions, and define hard limits.
Pause & Resume
Disable any agent instantly from the dashboard. Active executions are stopped gracefully and scheduled runs are suspended until you re-enable.
Full Audit Trail
Every action an agent takes is logged with timestamps, inputs, outputs, token cost, and the model version used — queryable at any time.
Approval Workflows
Configure agents to pause and request human sign-off before executing high-impact actions like sending emails, creating PRs, or publishing content.
Scoped Permissions
OAuth tokens are granted per-integration with minimum necessary scopes. Agents cannot access services you haven’t explicitly connected.
Cost & Usage Limits
Set per-agent and per-company operation budgets. Agents that approach a limit pause and notify you before incurring additional cost.
Data Deletion
Delete any agent, execution record, or stored credential at any time. Deletion is permanent and cascades through all linked records.
Current Limitations
We believe in being upfront about what OmniGate’s AI agents cannot or should not do. These limitations reflect both technical constraints and deliberate policy decisions.
- ⚠API discovery is read-only by default. When an agent explores a new integration, it reads schema and metadata only. Write operations require explicit enablement in agent configuration.
- ⚠No financial or investment advice. Agents may surface financial data and flag anomalies, but they do not provide advice regulated under financial services law. Do not rely on agent output as professional financial guidance.
- ⚠No medical or health advice. OmniGate agents are not trained for, and must not be used for, clinical decision support, diagnoses, or any regulated health context.
- ⚠LLM outputs can be incorrect. Agents reason using probabilistic models and can produce factual errors, misinterpret context, or generate unsupported references. Significant agent outputs should be reviewed by a human before acting on them.
- ⚠No direct database write access to third-party systems. Agents interact with external services through official APIs only — they cannot connect directly to your production databases.
- ⚠Context window constraints. Each agent run has a finite context window. Very long documents, large codebases, or extensive histories may be truncated, and critical details may be missed.
- ⚠Agent decisions are not legally binding. Outputs generated by AI agents (contracts, agreements, legal summaries) carry no legal weight and must be reviewed by qualified counsel before use.
Contact Us with AI Concerns
If you observe unexpected, harmful, or concerning agent behaviour — or have questions about how OmniGate’s AI systems handle your data — please reach out directly. We respond within one business day.
AI Safety & Concerns
Email us at omnigate@polsia.app with the subject line AI Concern. Include your account email, a description of the agent behaviour, and — if possible — the execution ID from your audit log.