Tweeny builds production-ready AI agents for enterprise workflows, combining intelligent automation, retrieval-augmented generation (RAG), multimodal AI, document intelligence, voice and conversational interfaces, and business-system integrations. Our AI agents are designed to connect data, models, tools, and workflows to deliver measurable business outcomes.

Explore common questions about building and deploying AI agents, from development timelines and infrastructure options to data governance, system integrations, and custom enterprise solutions.
1. How long does it take to build an AI agent?
The timeline depends on the agent's complexity, integrations, data requirements, security requirements, and deployment environment. A focused workflow agent can be developed relatively quickly, while enterprise AI agents involving proprietary data, RAG, multiple systems, multimodal inputs, or complex orchestration require more engineering and testing.
2. Can AI agents be deployed on-premise or in a private cloud?
Yes. AI agents can be deployed in public cloud, private cloud, or on-premise environments depending on your security, compliance, data residency, and infrastructure requirements. Deployment architecture can be designed around your existing enterprise environment.
3. Who owns the data used by an AI agent?
Your organization's data remains under your control. AI agent architectures can be designed around your data-governance requirements, including access controls, data isolation, retention policies, private infrastructure, and approved model providers.
4. Can AI agents integrate with existing business systems?
Yes. AI agents can connect with APIs, databases, enterprise applications, documents, internal knowledge bases, communication platforms, and other business systems. This allows agents to retrieve information, use connected tools, execute actions, and support existing workflows.
5. Can Tweeny build a custom AI agent for a specific business or industry?
Yes. Tweeny develops custom AI agents around specific business processes, domain knowledge, data sources, systems, and operational requirements. Agents can be designed for industry-specific workflows while incorporating the security, governance, and deployment requirements of the organization.
We design and deploy custom AI agents around your business workflows, data, systems, and industry requirements. From enterprise automation to domain-specific intelligence, our team can take an AI agent from concept and architecture through production deployment.