thirdmind · AI Compass
The AI Compass meets you wherever you are: without a clear AI idea, with several possible use cases, or with a concrete process that needs to be sharpened in a workshop.
Some teams first need orientation. Others already know which workflow hurts and need to check whether it can become a useful pilot. The AI Compass combines both: potential analysis, process workshop, and a recommendation for the next step.
We examine concrete processes, data situation, feasibility, risk, and internal effort. After that, it is clearer whether you start internally, build a pilot, or set a topic aside deliberately.
Starting point
Many companies already have enough AI ideas: automate support, maintain CRM data, prepare offers, check documents, make internal knowledge usable.
The decision is which of these is mature enough, important enough, and controllable enough to start. This is where the AI Compass separates useful AI use cases from nice ideas.
If no use case is clear yet, we create orientation. If a concrete process is already on the table, we use the workshop part of the Compass to sharpen the task, data, systems, edge cases, rights, and approvals.
We clarify whether you first need orientation, want to compare several use cases, or already bring a concrete process into the workshop.
We make visible where recurring work arises, which steps are manual today, and which handovers are critical.
We evaluate which use cases or process steps have enough operational value to deserve more than a neat AI demo.
We check which data, systems, rights, and control points are necessary for an idea to become a resilient AI process.
We distinguish what your team can handle internally, which process deserves a pilot, and where professional architecture or implementation makes sense.
The result can be used directly by management, departments, and IT. It shows which AI use case makes sense first, which concrete process is ready for a pilot, and what still needs to be clarified before that.
Recurring requests, ticket triage, response preparation, knowledge gaps, escalations.
Example: A digital employee reads new tickets, recognizes topic and urgency, suggests answers, and flags cases that need human expertise.
Lead research, account preparation, CRM maintenance, follow-ups, offer preparation.
Example: A digital employee prepares accounts before a first meeting, researches relevant information, and creates meeting notes for sales.
Document review, email triage, data comparison, internal coordination, recurring approvals.
Example: A digital employee checks incoming documents against defined criteria and only prepares the cases where a decision is necessary.
For IMV, several automation fields were assessed, including documents, knowledge access, communication, and administrative standard processes.
At Innotec, existing AI experiments, process ideas, and operational bottlenecks were translated into a prioritized implementation logic.
For LCI, sales and meeting processes were structured around a possible AI coworker, with a focus on research, outreach, offer work, and follow-up.
The AI Compass is designed to stand on its own. You can then implement with thirdmind, continue internally, involve your existing IT team, or work with another implementation partner.
Our aim is to leave you with a basis you can use without us. You know which use case makes sense, which data and systems are relevant, what scope is realistic, and where the risks are.
If the use case, data situation, and control model are solid enough, the result becomes a limited first implementation step.
If the organization already has the right resources, the result gives your team a decision and scope basis.
If value, data, or risk do not fit, a clear no is a useful result.
We deliberately do not publish a flat rate. Before a potential analysis, we check the scope, data situation, and internal stakeholders. We then propose a sensible framework.
We will discuss the specific framework after the fit check. The AI Compass should be large enough to make reliable decisions and small enough not to become a major project itself.
An AI potential analysis checks which processes are suitable for AI, which data and systems are affected, which risks arise, and which next step makes sense. In the AI Compass, that can lead to orientation, a concrete process workshop, or a scope for the first pilot.
No. The AI Compass evaluates use cases, clarifies concrete processes, and shows whether implementation is worthwhile. The build happens later, either in a separate sprint or internally.
No. The AI Compass is structured so you can use the result independently: internally, with your existing IT, with another implementation partner, or with thirdmind.
We usually need a kickoff, one or two process or workshop conversations, relevant example materials, and a results call. The exact effort depends on whether we start broadly with orientation or go deeper into one concrete process.
No. The data situation is part of the analysis. The AI Compass often shows which data is already usable, what is missing, and which use case is clean enough to start.
Yes. If a concrete process is already clear, we work on it workshop-style inside the AI Compass: task, data, systems, edge cases, rights, approvals, and MVP scope. If no use case is clear yet, we start more broadly with orientation and prioritization.
The AI Compass is best suited for medium-sized companies and B2B teams with operational processes in which repetition, manual checking or information searches take up a lot of time.
If the use case is clear enough after the AI Compass, yes. The result can also be that you should first clarify data, rights, or process responsibility internally.
Start with a few questions. After that, it is clearer whether you need orientation, a process workshop, or a direct pilot.
In 90 seconds, we clarify which next step makes sense.
