Questions enterprise buyers actually ask

Everything you need to know about AI agent governance, deployment, and how aura.one fits into your enterprise stack.

Agent builders help you create agents. We help you govern them at scale. Agent builders focus on the prompt and the workflow; we focus on the control plane — who can access what, what requires approval, what's auditable, and what happens when something goes wrong. You can build agents anywhere. You govern them here.
Copilots are single-vendor, single-model, single-context tools. They're useful, but they're not a platform. We're a governance layer that works across models, across tools, across teams. Copilots answer questions; we manage the infrastructure that makes AI agents safe, auditable, and scalable inside real enterprise constraints.
It means your data lives in your own Postgres instance, on your own infrastructure, isolated from every other customer. No shared database, no shared cache, no shared secrets vault. You control the region, the retention, and the access. Cross-tenant data leakage is architecturally impossible, not just policy-prohibited.
We deploy dummy tools that look like they expose real secrets — database credentials, API tokens, admin access — but return realistic-looking fake data. When an agent reaches for a honeypot tool, the system triggers an immediate security alert, flags the session in the audit log, and can automatically revoke the session. No legitimate user asks an agent for raw database credentials. Zero false positives.
Bring your own LLM contracts. You keep your existing agreements with OpenAI, Anthropic, Google, or whoever you use. You configure your API keys in the platform. We route agent invocations to the models you specify, track usage and cost, and give you full visibility into what's being spent. We don't mark up your tokens or lock you into a single provider.
Yes. The policy engine lets you specify which models are allowed, preferred, or mandatory per team, per tool, or per action type. Engineering can be on Claude, HR on Llama, Finance on ChatGPT — and the platform enforces it. Tool owners can also mandate specific models for operations that touch their systems.
Human-in-the-loop approval workflows are configurable per action type. CRM writes, financial transactions, data exports, external communications — you define which actions require approval, who approves them, and the escalation path. Approvers get notified in their channel. Requests can be approved, rejected, or escalated. Kill switches are available for immediate stops.
Single-tenant deployments are Docker-based and self-contained. Standard deployment is days, not months. We handle infrastructure setup, configuration, and SSO integration. For on-prem or highly customized deployments, timelines vary — but the architecture is designed to deploy cleanly.
We support SAML 2.0 and OIDC integration with Okta, Microsoft Entra ID, and other enterprise identity providers. Your users authenticate with your existing SSO. Your role mappings carry over. Your access policies are enforced. No separate identity system to manage.
Every agent action is recorded in an immutable, tamper-evident audit log. Logs are time-partitioned by week, retained hot for 90 days in your Postgres instance, and archived to your own object storage after that. You control retention, access, and the archive destination. Compliance teams can replay any session end-to-end.

From experimentation to enterprise-grade in one governed layer

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.