Consulting knowledge base with AI search
The consultant finds appropriate methodologies and lessons from previous projects under access rights. The answer prepared by artificial intelligence is checked against sources and the situation of a specific client.
Market data, interview insights, methodologies, analysis models and previous recommendations are stored in presentations and employee memory. Consultants repeat the work already done, and new employees have long absorbed the experience of the organization.
How the solution works
- Select a message to reuse
- Check permissions and remove inappropriate client information
- Describe the conditions and limits of the method
- Find previous material suitable for a new client assignment
- Check customization and add tutorial
Key challenges
- Research and knowledge of previous projects are repeated from the beginning
- The use of IoT is not integrated into the managed consulting process
Solution capabilities
Knowledge Purpose
The method, the example and the measured result of the previous project are marked differently. The case describes the model, scale, time and most important conditions for the activity.
Right of re-use
Deletion of the client name alone does not necessarily eliminate recognition. Checks contractual restrictions, licenses and the right of a specific recipient.
Method Boundaries
Unsuccessful applications and reasons are also stored. The number of benefits of an earlier project does not translate into a promise to another client.
Managed IoT Response
The search respects document accesses. The source of the answer is checked, and insufficient information must be clearly displayed.
Knowledge Care
The expert responsible confirms the correction of the method or the restriction of its use. The previous version is preserved along with the calculations and conclusions of the project in which it was applied.
Business context
- Research and knowledge of previous projects are repeated from the beginning
- Market data, interview insights, methodologies, analysis models and previous recommendations are stored in presentations and employee memory. Consultants repeat the work already done, and new employees have long absorbed the experience of the organization.
- The use of IoT is not integrated into the managed consulting process
- Consultants use different tools for client documents, analysis and presentations without uniform sources, confidentiality, assumptions and verification rules. The risk of data leakage, unreasonable conclusions and equally sound but weakly applied recommendations increases.
- Previous experience applied to a specific customer question
- The client hopes that the consultant will use the available knowledge, but will assess the differences in its performance. The assumptions, sources and usage rights of the methods help with this review. The team can more effectively prepare the analysis while retaining the specialist's responsibility for the final advice.
Core features
- Knowledge Purpose
- Right of re-use
- Method Boundaries
- Managed IoT Response
- Knowledge Care
Key integrations
- Project documents and licensed sources of information
- Only selected and legally reused material.
Potential impact (%)
The ranges indicate an illustrative relative change in the metric under the stated assumptions. Results depend on the starting position and actual use of the solution. Percentages for different metrics must not be added together.
Finding the Right Method Work
16–42%Decreasing
This illustrative scenario assumes that 40-70% of information searches and repeated cross-checks can be addressed. That share is assumed to fall by 40-60%. Company data is needed to verify both the addressable workload and the resulting change.
Measure minutes to find the right method with its limits based on the actual issue of the order.
Work corrected due to incorrect previous example
5–25%Decreasing
This illustrative scenario assumes that 20-50% of missed actions can be identified through task and deadline tracking. That share is assumed to fall by 25-50%. Company data is needed to verify both the addressable share and the resulting change.
Compute conclusions corrected for an unwarranted transfer of a previous client sample.
Conditional calculation scenarios. The assumptions have not been validated against client measurements.
When this solution is relevant
- The team is looking for material from previous methodologies and similar projects in multiple repositories.
- Previous findings are used for a new client, but it is difficult to verify their assumptions and application limits.
Implementation requirements
The team agrees on what methodologies and lessons from previous work can be used in a common knowledge base. The materials include application conditions and access rights. Artificial intelligence responses are checked by the consultant against the provided sources.
Further development options
- Other methods and cases of AI help only after testing their accuracy, access, and misuse.