Make company knowledge usable through conversation

A team regularly answers questions about its service packages. The manager wants new employees to understand what is included without a lengthy search. Today, they open several documents or ask an experienced colleague. The initial task is manageable: make a clearly defined, frequently needed area of knowledge easier to access.

The assistant's role is to prepare information for an answer. It does not approve special services or make commitments on the company's behalf. Together, we define which questions it should answer and which should go to domain experts.

The following example describes a possible application using invented documents, not a recorded DataPrism test. An employee asks: “Does the Plus service package include an introduction session, and is it held at the customer's premises?”

The approved service overview says “Introduction by video appointment included” for the Plus package. It does not address an on-site session. An appropriate answer would be: “An introduction by video appointment is included. Source: Service overview, Plus package. This document does not establish whether an on-site session can be offered; that needs clarification from the responsible service team.”

The employee now has a usable answer and a focused open question. Missing information is not turned into a commitment. A follow-up such as “Which packages include an introduction session?” should also rely on the actual available table rows and identify the version used.

Through DataPrism, Corvendor explored technical AI-assistant integration and the use of additional supplied content at pilot stage. This included questions about specific material and summaries of tables. Company-specific information that was not inherently available to the general language model could therefore be brought into the interaction.

That experience provides a starting point for a new project. It does not mean that every required function is already available as a production-ready service. For your application, we assess which existing components can be reused and what needs to be added for source references, access permissions, information updates, and integration.

Your domain experts define the knowledge area, authoritative documents, and appropriate answers to typical questions. Corvendor can prepare the content, supply relevant information for a question, and integrate the assistant into the intended working environment. This does not automatically require retraining a language model; the first issue is what information it receives for each answer.

A usable solution needs visible source references and a defined way to handle outdated, conflicting, or missing information. A source reference helps with checking, but does not by itself prove an answer correct. Access restrictions must be considered when selecting information, not only when wording the response.

Tables also require consistent columns, units, filters, and time periods. Summarizing is different from calculating. Where totals or comparisons are needed, the underlying queries and calculations are deliberately implemented and checked. A conversational interface alone does not make an analysis dependable.

For a pilot, we work with the team to assemble a manageable set of typical questions. These include answerable questions, missing information, conflicting documents, and questions outside the agreed scope. Domain experts establish what an appropriate answer or request for clarification would be in each case.

• Content and sources: Is the answer correct, supported by the stated material, and based on the appropriate version?
• Boundaries: Does the assistant recognize missing details and stay within the approved knowledge and access scope?
• Work required: How do search time, questions to domain experts, and the effort needed to correct answers change?
• Operation: What effort is involved in maintenance, and how do response times and usage costs behave at the intended scale?

The comparison is with current practice, not just the speed of an individual chat response. A fast answer that takes substantial work to correct saves little. The questions are checked again after changes to content or implementation. These checks describe an approach for a new project, not measured results from the DataPrism pilot.

A useful starting point can be an internal assistant for one product group, an approved set of documents, and a small user team. The trial should leave more than example answers: prepared content, evaluation questions, and clear responsibility for maintaining the material. These provide a basis for deciding whether and how to continue using the solution in daily work.

Further topics can follow, such as onboarding support or questions about internal business tables. A customer-facing service needs its own review of content, access, and handoffs; it does not follow automatically from a successful internal test.

Corvendor combines software and data preparation with coordination among users, domain experts, and IT. The goal is to make knowledge easier to use and reduce repeated searching and explanation by experts, while retaining their domain responsibility.