AI agents for companies

The simplest implementations start from PLN 9,900 net. An AI-agent with a knowledge base RAG usually starts from PLN 21,900 net. A business agent with integrations, logs and work on processes starts from PLN 39,900 net. A workflow agent or multi-agent starts from PLN 59,900 net. System or enterprise projects start from PLN 89,900 net. AI audit starts from PLN 2,900 net.

A simple AI agent can be ready in 1-3 weeks. Agent with knowledge base RAG typically requires 3-6 weeks. Solutions with integrations, multiple scenarios and security testing may require 6-12 weeks or more.

A chatbot typically handles a single-channel conversation and often follows a script. The AI-agent can use the company's knowledge, tools, integrations, context memory and perform several steps in the process. A chatbot can be part of an AI agent, but an AI agent is a broader solution.

RAG is an approach in which the AI-agent responds using a selected knowledge base, documents or company procedures. This allows answers to be based more on validated sources rather than just the model's general knowledge.

AI should not be treated as an infallible tool. That's why we design instructions, tests, limitations, knowledge sources, logs and escalation to humans. In important processes, AI should prepare a draft or recommendation, and a human should approve the final decision.

Yes. The agent can use PDF documents, procedures, FAQs, regulations, technical documentation, CRM, files and other sources of knowledge. Before implementation, it is worth organizing the documents and determining which sources are current and approved.

Yes. Depending on the system and available API, an agent can retrieve data from CRM, prepare lead summaries, generate response drafts, create tasks, or save notes. The scope of integration depends on the technical capabilities of CRM.

Yes, but such activities should be designed carefully. An agent can prepare a task, a memo, a draft message or a recommendation. In the case of activities that influence customer, financial data, statuses or business decisions, it is worth adding human approval.

Yes, but we recommend distinguishing between low-risk responses and responses requiring human control. Simple FAQ questions can be handled automatically, while offers, complaints, decisions and sensitive matters should have an acceptance stage.

Security depends on the implementation architecture, model provider, data storage, permissions and integration. We design solutions with access control, logs, limitation of knowledge sources and the possibility of implementation in a more controlled environment if the process requires it.

Yes. The knowledge base should be updated as procedures, documents and the company's offer change. This can be done manually, periodically or as part of ongoing monthly care.

The purpose of the AI-agent is not to replace the team, but to relieve it of repetitive tasks, search for knowledge and prepare materials faster. Employees continue to make decisions, evaluate responses, and handle matters requiring accountability.

Yes, you can build a voice or realtime agent that recognizes speech, responds with voice and connects to selected systems. However, such a project is more complex and requires more thorough conversation tests, transfer to a human and monitoring.

Yes. Most often, we recommend starting with one scenario, e.g. AI-agent of company knowledge, FAQ, document analysis or sales support. After checking the quality and effects, further scenarios can be developed.

It is best to prepare sample questions, documents, procedures, FAQs, process descriptions, a list of company tools and information about who will use the agent. If the company has a lot of documents, it is worth indicating which ones are current and approved.