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FREQUENTLY ASKED QUESTIONS
Straight answers about the platform, security, deployment, and how an engagement works.
Arvenza.ai is the Enterprise AI Operating Layer — a platform for designing, running, and governing AI agents on top of your existing business systems. It unifies an AI agent framework, enterprise integration (hundreds of connectors), and knowledge pipelines (RAG) in a single product, so teams ship working AI solutions in weeks instead of quarters.
An AI operating layer sits between your AI models and your business systems. The model provides raw intelligence; the operating layer provides everything that turns it into a dependable business solution — connections to your systems, grounding in your knowledge, security and access control, human approval workflows, and full operational visibility.
Yes. Arvenza.ai ships as a single self-contained binary, a Docker image, or a Kubernetes chart, and runs entirely inside your own environment — on-premises, private cloud, or edge. Paired with a locally hosted AI model, no data ever leaves your network.
16+ providers, including OpenAI, Anthropic, Azure OpenAI, Google Vertex, AWS Bedrock, Mistral, and locally hosted models via Ollama or vLLM. Switching providers is a one-line configuration change, and tasks can be routed to different models with automatic failover — no vendor lock-in.
Through hundreds of built-in connectors across 33 categories — CRM platforms, SharePoint, Microsoft Teams, databases such as PostgreSQL, Oracle, SQL Server and MongoDB, messaging systems like Kafka and RabbitMQ, AWS and Azure services, SAP, and any REST or SOAP API. Enterprise integration patterns (retries, routing, circuit breakers) handle real-world reliability.
Human-in-the-loop means a person approves an agent's action before it takes effect. In Arvenza.ai, any step can require approval — for example, only risk-flagged requests, or every final decision while the solution earns trust. The agent pauses, a reviewer approves or rejects with feedback, and everything is recorded in the audit trail.
Yes. Every request carries a step-by-step reasoning trail — what the agent checked, in what order, and why it concluded what it did — visible to reviewers and auditors. This makes agent decisions explainable rather than a black box, which is essential for approvals, compliance, and building user trust.
Security is built into the platform: JWT and OAuth2 authentication (works with Keycloak, Auth0, Okta, Azure AD), TLS and mutual TLS, multi-tenancy, PII masking in knowledge pipelines, and a complete audit trail. Because it runs in your environment, it inherits your network and data controls too.
No. Agents, integrations, and knowledge pipelines are described in readable, declarative configuration that an IT team can learn in about a day — no model training, no heavy coding. Deep AI expertise is optional, not required.
A focused proof of concept typically runs in weeks, not months: we agree the use case and success criteria with you, implement in your environment with your data, and demonstrate against those criteria. The same configuration then moves to production without a rewrite.
Frameworks are developer libraries — powerful, but you build and maintain the surrounding system yourself: integrations, security, operations. Arvenza.ai is a platform where those layers ship as one governed product. Frameworks suit teams building custom AI software; Arvenza.ai suits organisations that want business outcomes running on enterprise-grade foundations quickly. See our detailed comparisons.
Licensing is tailored to your deployment size and support needs. Commercials are discussed once we understand your use case — typically after a successful proof of concept. Arrange a conversation and we will walk you through the options.
Ask us directly — a specialist will come back to you the same day.
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