Built the right way, AI gives your team a colleague that never gets tired. We build assistants that speak from your company's own data and work on your website, on WhatsApp and inside your internal systems. This service is designed for e-commerce and service businesses that can't keep up with customer questions, support teams answering the same questions all day, and organizations whose knowledge is scattered across documents.
Our assistants run on a RAG (Retrieval-Augmented Generation) architecture: before answering, they look up your product catalog, your FAQs and the internal documents you approve. Information that changes, such as prices, stock and order status, is read from your live systems, not from the model's memory. When a question isn't covered by the knowledge base, the assistant doesn't guess; it says so and hands the conversation, with its history, to your team.
We don't stop at a chat window that answers questions. By connecting the assistant to your CRM, ERP, accounting software and e-commerce platform, we automate repetitive work such as order lookups, booking appointments, saving leads to your CRM and preparing quotes and reports. For broader processes, we build AI agents that carry out defined steps within the rules and approval points you set.
Typical scenarios include an e-commerce assistant that answers shipping and returns questions and recommends the right product, a WhatsApp assistant for appointment-based businesses that checks the calendar and books the slot, and an internal knowledge base assistant that searches procedures, contracts and technical documents and answers with its source. We decide together where to start by looking at the work that costs the most time and whose results are easiest to measure.
We start with a discovery call: we review your processes and the data you have, and together pick a single scenario with measurable results that will pay back fastest. Then we gather and organize your knowledge base, choose the model based on the accuracy, speed and cost the job requires, and build the integrations. Before launch we test the assistant against a set of real customer questions and deliberately tricky ones, and sign off on answer quality with you. We also define when, how and to whom the assistant hands over, separately for business hours and after hours.
We don't treat security as a setting added at the end. We process only the personal data that's actually needed, place the privacy notice in the assistant's first message, restrict access with role-based permissions and keep an audit log. For critical output, such as legal, financial or health-related answers, human approval is part of the flow. We work under enterprise API terms that don't use your data for model training; if the model provider is abroad, we plan from the start for the data transfer to rest on a valid legal basis under KVKK, Turkey's data protection law, and if needed we deploy a setup that keeps data in Turkey or on your own servers. On WhatsApp, we design the assistant to comply with Meta's platform rules, as a customer service tool limited to your business's topics.
At the end of the project we hand over the working assistant, the prepared knowledge base, the integrations and a dashboard where you can follow conversations. You own all rights to the code and infrastructure. Because we build the infrastructure to be model-agnostic, you can later switch to a better or more economical model or continue the work with another team; you never stay dependent on us.
We stay involved after launch. We track the share of requests resolved automatically, conversations handed to your team and unanswered questions, and add what's missing to the knowledge base. We also monitor model usage, hosting and channel costs, making your assistant more accurate and its running cost more predictable every month. When your products, prices or campaigns change, we keep the knowledge base up to date, because an assistant is only as good as the information it draws on.
