AI assistant
An AI assistant grounded in your own data: product picker, document Q&A, support triage. Answers from your knowledge base.
Updated
An AI assistant that answers from your own documents and data: customer questions, product selection, help for staff. With a clear plan for where your data is processed. Timeline: 14+ calendar days. Priced after a short brief.
What's included
- RAG search across your docs and databases
- Data stays on your server or in your cloud
- Tone and behavior tuned to your brand
- API for any front-end you have
- Logging and audit for compliance
A general-purpose chatbot doesn't know your prices, policies or product range — and when it doesn't know, it confidently makes things up. An AI assistant for a business has to answer from your sources: the catalog, the help center, contracts, internal guides. We build it on retrieval-augmented generation (RAG): before answering, the system finds the relevant passages in your documents and answers from them, with a reference to the source.
When you don't need one: if customers ask five questions in total, a well-written FAQ and a simple bot with buttons will do the job cheaper and more predictably.
Who it's for
- Support teams drowning in repetitive questions that are answered somewhere in the docs.
- Stores with a large catalog where customers need help choosing.
- Companies with a lot of internal documentation that staff can't find their way around.
- Teams that want to triage incoming requests before a human picks them up.
How we work
- Scoping. We pick one process with a measurable goal — for example, the share of questions closed without an operator — and agree on what the assistant may and may not answer.
- Knowledge base. We collect and clean the sources, split them into searchable chunks and set up updates, so the assistant doesn't answer from last year's price list.
- Model and hosting. We choose where the model runs: your server, a cloud in the required jurisdiction, or an external API with personal data stripped out.
- Integration. Website widget, messenger bot, CRM or internal portal — through an API that fits whatever front-end you have.
- Pilot and tuning. We run it on part of the traffic, review real conversations and adjust the sources, prompts and hand-off rules.
What matters technically
Quality depends less on the model than on the knowledge base: complete, current and well structured. The assistant must know when to hand over to a human, keep a log of conversations for review, and have spending limits on the model API. If you work with personal data of Russian citizens, local storage rules apply, so the hosting choice is made up front, not after launch.
Timeline and cost
A pilot takes 14+ calendar days. Cost is estimated after a short brief and depends on the size and state of the knowledge base, the channels, integrations and where the model has to run.
Example
For example, for an online store with a few thousand products: the assistant asks two or three clarifying questions, suggests suitable items with links, answers delivery and return questions from the store's own policy pages, and passes order issues to a manager in the CRM with the full conversation attached.
What we need from you
Access to the documents and data the assistant should use, a list of typical questions, the rules on what it must not discuss, and a person who will review the pilot results. For the website-side widget see web app development; for automating the steps around it — n8n automation.