Kademar designs and implements applied AI solutions for businesses: internal assistants, intelligent chatbots, AI agents, process automation, customer service, internal technical support, WhatsApp and Telegram automations, CRM integration, websites, forms, email, internal documentation and knowledge bases.
We do not implement AI as an isolated tool. We integrate it with your processes, your data and the way you actually work.
No. A website chatbot can be part of the project, but it is not the center of the solution.
The real value lies in building a useful knowledge base, connecting AI to real processes and making the assistant useful for specific tasks: answering customers, guiding technicians, finding documentation, classifying requests, creating tasks, preparing responses or triggering automations.
It is the set of information the assistant uses to answer or guide processes: internal documentation, FAQs, manuals, procedures, catalogs, references, PDFs, policies, forms, technical data or any content relevant to the company.
Before connecting AI, that information must be organized, duplicates removed, contradictions detected and the content structured so it is truly useful.
RAG means that the assistant does not answer only with what the model “knows”; it consults a prepared knowledge base with information from your company.
This allows AI to answer using your own documentation, internal procedures or specific references, reducing generic answers and improving usefulness in real processes.
Because connecting a chatbot to a website, CRM, WhatsApp, Telegram or n8n can be relatively quick when the project is clearly defined.
The critical part is preparing the knowledge properly: gathering documents, cleaning them up, structuring them, testing real questions, adjusting responses, defining limits and validating that the assistant helps reliably.
An AI connected to disorganized information can provide inaccurate answers. That is why we place so much importance on RAG and the knowledge base.
Applied AI implementation projects start from €4,000, provided that the project is already defined and the scope is clear.
The final price depends on the volume of documentation, the complexity of the knowledge base, the channels to be integrated, the required automations and the level of reliability needed.
A functional MVP is usually ready in about 2 weeks.
But a production-ready solution, with a well-refined knowledge base, structured RAG, testing, validation and adjustments, can take up to 3 months, especially if there is extensive documentation, technical procedures, catalogs, references or critical information.
The assessment reviews your processes, tools, documentation, channels and real automation opportunities.
It may include:
Yes. The AI assessment is an independent service starting from €450.
If you later decide to implement the solution with Kademar, the assessment fee is deducted from the final implementation quote. This discount applies to the initial implementation, not to the monthly maintenance fee.
The initial assessment is used to detect opportunities and define a first roadmap.
Strategic consulting, starting from €900, is designed for companies with several processes, departments, extensive documentation or the need to define a more complete architecture before implementation: phases, tools, integrations, risks, channels and priorities.
Managed maintenance starts from €450/month and includes:
We do not leave AI installed and abandoned. We maintain, review and improve it continuously.
Yes. We can implement WhatsApp automations for customer service, sales, support, follow-up, bookings, request qualification, incident creation, link sending, human handoff or connection with CRM and other systems.
The workflow is always defined according to the company’s real case and the technical possibilities of the channel.
Yes. Telegram can be very useful for communities, technical support, private groups, internal alerts, notifications, access to documentation or automated workflows.
We can create bots connected to internal processes, knowledge bases or company tools.
Yes. This is one of the most interesting use cases.
We can create internal assistants so technicians, operators or employees can find documentation, procedures, manuals, references or work steps without relying on manual searches across folders, PDFs or scattered systems.
For example, in a mechanical workshop, an assistant can guide the technician to the correct spare-part reference based on model, year, engine, version and supplier, helping them prepare the information needed to request the replacement part.
We do not present AI as a complete replacement for the human team.
We present it as support: reducing repetitive tasks, organizing information, speeding up responses, guiding processes and helping people work with more context and less friction.
For sensitive processes, we recommend keeping human supervision.
Yes. We can integrate the solution with your website, CRM, forms, email, WhatsApp, Telegram, n8n, databases, internal systems, support tools or APIs, depending on the case.
The architecture is defined after the assessment to avoid building unnecessary integrations.
Yes. Academies, communities and memberships often have many repeated questions, enrolment processes, student support needs, content, documentation and recurring communications.
We can create assistants for students, automate enrolments, answer frequently asked questions, connect with learning platforms, improve support and reduce operational workload.
Yes. In ecommerce, it can help with customer service, product questions, post-purchase follow-up, cart recovery, query classification, product description generation, segmentation and sales automations.
It can also be connected to email marketing, CRM or support tools.
Yes. Depending on the case, we can design private, hybrid or external API-connected solutions.
The decision depends on the required level of privacy, the type of data, the budget, the required performance and the volume of use.
Not every company needs a fully private AI solution, but some do need greater control over data, permissions and infrastructure.
It depends on the chosen architecture and the provider used.
At Kademar, we define the solution taking privacy, data control and responsible use of information into account.
When the project requires greater control, we can propose private or hybrid architectures to reduce unnecessary exposure.
It does not need to be perfect.
To get started, it helps to have:
If the documentation is disorganized, part of the work will precisely be turning it into a useful knowledge base.