Visibility, control, and audit for every agent your teams deploy - and every tool they touch. One platform. No shadow AI.
AI adoption is happening inside your organization right now - in pockets, in silos, in ways nobody planned for. Teams are wiring agents to production CRMs, internal databases, email inboxes, and financial systems. They're sharing credentials over Slack, using personal API keys, and building workflows nobody approved or audited. IT and security are caught in an impossible position: block AI and slow the business, or allow it and watch risk accumulate with no safety net.
Nobody knows what agents are running, what tools they're connected to, or what data they're accessing. There is no single pane of glass. You can't govern what you can't see.
Teams connect agents to production systems using personal API keys, shared service accounts, and ad-hoc OAuth tokens. No centralized credential management, no scoped access, no revocation.
When something goes wrong, there is no way to reconstruct what happened. No log of what the agent was asked, what it decided, what tools it called, or who approved it.
Every team picks their own tools, their own models, their own integrations. Six different agents from six different vendors, each with its own access patterns. No consistency, no scale.
Who approves what? Which actions need human sign-off? Without structured approval workflows, teams either skip approvals entirely or get stuck in untrackable back-channel requests.
The real risk isn't the AI you can see - it's the AI you can't. Agents built on personal accounts, copilots with ungoverned tool access, third-party services touching your data without your knowledge.
Every agent action flows through a governed pipeline - identity, policy, tool access, execution, and audit - before a response reaches the user.
A user sends a message through Slack, Teams, email, or the web. The channel adapter normalizes the message and resolves the user's identity through a four-level cascade: organization → department → team → individual. The right persona, tone, guardrails, and topic boundaries are injected automatically.
Before any action is taken, the policy engine runs. Hard guardrails are enforced pre-flight: PII detection and redaction, data access scope verification, approval gates for sensitive actions, model restrictions, and rate limits. Soft guardrails are evaluated post-hoc and flagged for review.
The agent calls only the tools it's authorized to access through scoped OAuth connectors with per-tool, per-user credentials. Every tool call is logged. Honeypot tools catch prompt injection attempts in real time. Unauthorized access triggers immediate security alerts.
The response is checked against policy before delivery - redacted if it contains PII, escalated if it needs human approval, blocked if it violates policy. Every action is recorded in an immutable, tamper-evident audit log. Full replay. Full traceability. No gaps.
From tool access and policy enforcement to audit trails and intrusion detection - one platform covers it all.
Central, owner-managed registry of every external system agents can access. Scoped credentials, approval workflows, and full audit.
Reusable behavior packages for agent competence. Versioned, published, and rollback-capable across teams.
Hard and soft guardrails enforced before every action. PII detection, approval gates, model restrictions, and rate limits.
Immutable, tamper-evident logs for every agent action. Full end-to-end session replay for compliance.
Approval workflows for sensitive operations. Escalation paths for edge cases. Kill switches when needed.
Model-agnostic. Bring your own LLM contracts. Usage and cost tracking by team, tool, and model.
Intrusion detection for AI agents. Catches prompt injection and unauthorized access with zero false positives.
Every action traces to a verified identity. Four-level cascade for persona, guardrails, and accountability.
Dev, staging, and production for agents, tools, and policies. Test before promoting to production.
aura.one sits between your users and the AI models they use - enforcing policy, managing credentials, logging every action, and giving IT full control without slowing teams down. Not a copilot. Not an agent builder. A governance platform built for enterprise from day one.
From the CTO setting strategy to the CISO managing risk - one platform for everyone involved in AI adoption.
You're under pressure to enable AI across the organization. Every team wants agents. The risk isn't adoption - it's uncontrolled sprawl that creates security incidents, compliance gaps, and fragmented vendor contracts. Standardize how the organization uses AI agents. Get the visibility you need to answer to the board. Scale adoption without scaling risk.
You're not anti-AI. You're pro-evidence. You need to know who accessed what, when, and why - and you need to show that to an auditor. Policy and audit are first-class. Human-in-the-loop controls for sensitive actions. Kill switches. Tamper-evident logs with full replay. PII detection and redaction. Honeypot tools that catch prompt injection before it becomes an incident.
You're the one who has to actually implement this. Central tool and skill registries. Approval workflows with clear ownership. Dev, staging, and production separation. Integration with Slack, Teams, and your existing SSO/IAM. BYO-LLM so you keep your existing model contracts. Clean APIs and extensibility. Infrastructure you can maintain - not a science project you have to babysit.
Govern what agents can touch. Trust what they do. See your enterprise AI adoption done right - with visibility, control, and audit built into every action.