Frequently asked questions about Tacita's AI interviewers

It depends on the case, but the load on the people who bring us in is always light. The internal point of contact works with us in the initial phase to define objectives, and then again in the final briefing. In between, the AI interviews run on their own. Each person receives a link and takes part whenever they prefer. There are no calendars to coordinate and no days to block out. We adapt the project timeline to your context, not the other way around.

Yes, the complete GDPR documentation is provided before we start. It covers everything a DPO or legal team needs to sign off. Data is hosted on European infrastructure and every aspect of the processing is defined transparently. For us privacy isn't a box to tick, it's a starting condition. And we update it continuously as AI regulation evolves.

Always. Deliverables present aggregated data, never individual data. Session transcripts are accessible only to our team and the project contact, according to the rules agreed before the start. Participants know this, and it leads them to answer more honestly.

Every deliverable is built around the organization's context. In the initial phase we look together at the format you use, the level of detail you need and your internal terminology. If you have internal templates, we respect them. The goal is to hand you material you can use straight away, without having to rework it. We're also experimenting with new output formats as the technology opens up, from interactive dashboards to chatbots you can query about the results.

Absolutely. Each use case works on its own, but the value grows when you combine them. A project can bring together, for example, sentiment analysis and tacit knowledge capture in the same cycle, or market research and internal mapping. We define the setup together based on what you actually need. Many of the combinations we offer today came directly out of client requests. That's how the product evolves.

We define the KPIs together in the initial phase, based on the project objective. In some cases we have measured significant reductions in the time needed for skills mapping, for writing job descriptions and in escalations to senior staff. But every project has its own metrics and we build them to measure, starting from years of experience in organizational consulting. Our way of measuring evolves too, because with every new project we learn something about how to read the results better.

It's one of the things we get asked most often, and the answer is yes. The conversational format makes the difference. People don't fill in a form and don't rate themselves, they talk about what they do. That lowers resistance significantly. And if someone answers vaguely, the AI interviewer knows how to dig deeper with targeted questions. The quality of the conversations improves release after release, because we continuously refine the interview models based on what we observe in the field.

Always. Tacita does not pass itself off as a real person. And in practice that's an advantage. Interviewees don't feel judged, they don't have to manage social dynamics and they answer more naturally. It's something we've observed in every project and it keeps proving itself.

Yes. The AI interviewer can be used with active customers, prospects, former customers and even with contacts within the competitive landscape. The protocol is calibrated on the target group and the objective. It's one of the areas where we're investing most in research, because the scope for gathering market insight with this method is widening very quickly.

Our team works alongside the company to design the engagement strategy. We work on the invitation message, the tone, the right moment to send it and the context that makes taking part easy. Years of consulting have taught us that how you ask matters as much as what you ask. Every project leaves us new data on what works best by sector, role and target group, and we build it into the projects that follow.

No, it isn't necessary. We can start from existing materials or build a framework together in the initial phase of the project. Our method is designed to adapt to where the organization actually is, not to impose a ready-made model on it. It's an approach we keep refining, because every new context teaches us something about making the start-up process smoother.

Yes. In the initial phase we do specific work on terminology alignment, calibrating the language of the questions to the role's domain. It comes naturally to us: we come from consulting and we're used to stepping into very different technical contexts. The framework is validated with the manager before the start. Every time we work in a new sector, the know-how we build up enriches the platform for future projects.

No, and it's what sets us apart most. The value lies in surfacing concrete examples, specific signals and lines of reasoning that belong to that organization. The protocol is built for that role in that context. We use the company's own internal vocabulary, not textbook taxonomies. It's a principle that doesn't change, even as the underlying technology evolves.

It depends on the objective. Often a well-chosen sample is enough and produces results that are easier to read. Our team helps define selection criteria so that they are representative. It's work we do methodically, bringing the experience built up over years of qualitative research and organizational consulting. We're also testing new sampling approaches that take advantage of AI capabilities to adapt better to the specifics of each client and each project.