Manager's control panel app
An app for a business owner: see where an answer is needed, what waits for approval and whose move is next.
AI Automation and Chatbots for Business
Automate what repeats every day and affects revenue: answers to common questions, lead triage, CRM data entry, draft preparation. Rare and disputed cases stay with people, and the bot hands them to a manager together with the context. We start with one process, measure the result and only then expand.
When you need it
- Managers spend half the day answering the same questions about prices, lead times and availability.
- Enquiries arrive at night and on weekends, and the customer goes to whoever replied first.
- Someone copies data by hand from emails and messengers into the CRM or a spreadsheet.
- You need to process hundreds of product cards, documents or reviews, and there are not enough people.
- Company knowledge sits in people's heads and old files, and new hires keep asking the same things.
What is included
Process audit
We look at real conversations and spreadsheets, and count how much time an operation takes and what a mistake costs. We pick the first area where automation pays back fastest.
Chatbots
WhatsApp, Telegram or a chat widget on your website. Button-based flows for simple choices, a language model where people write free text.
AI assistant on your knowledge base
It answers from your documents, price lists and policies, with a link to the source. If the answer is not in the knowledge base, it says so and calls a team member instead of inventing terms.
Lead and document processing
Sorting incoming emails, extracting fields from files, assigning leads to managers, drafting replies and product cards. A person checks the result before anything is sent.
Integrations
HubSpot, Pipedrive, Zoho, Google Sheets, Airtable, email, Make, n8n, Zapier and custom services. A lead from a conversation lands in the right pipeline with the full history.
Data protection
We decide up front where personal data is stored and what goes to the language model. For sensitive data we anonymize the text or choose suitable infrastructure, with GDPR and local requirements in mind.
Tikhiy Tsekh: a request from MAX
A B2B bot that collects an acoustic panel request and passes the drawing to the sales team. MAX is a Russian messenger.
Plodomer: AI fruit inspection
Visual control on a sorting line: mark the fruit in the image and pass the damaged area to a person for review.
Web app for working with AI
An interface for tasks and chats: search, work states and commands available from the browser.
How we work
Review on real data
We ask for an export of enquiries or sample documents. They show the frequent topics and what the bot can be trusted with right now.
Scenario and rules
We describe what the bot does on its own, when it hands over to a person, what tone it uses, which topics it avoids and how it reacts to off-limits questions.
Build and test set
We build the first version and run it against a set of real questions with reference answers. The same set then checks every update.
Launch with a safety net
First the bot drafts replies for your staff, then it answers on its own within a narrow topic. We read the conversation log and extend the knowledge base.
Measure and expand
We compare response time and team workload with the period before launch, and decide which process to take next.
What we need from you
- An export of conversations or enquiries, or sample documents.
- Price lists, policies and answers to common questions, in whatever form they exist.
- CRM and messenger access, or the contact of your administrator.
- A team member who knows the process and will check the first answers.
What you get
- A working bot or workflow in your channels, on your accounts and with your keys.
- A knowledge base your team can extend without a developer.
- A test question set and a conversation log for quality checks.
- Clear numbers: how many enquiries the automation closes and how much time it frees up.
Price and timeline
The price is for the whole project: after discovery we scope the work and fix the amount before it starts. We do not bill by the hour. The cost depends on the number of scenarios, channels and integrations, and on the state of your knowledge base. Language model and service costs are paid by you directly at their rates, and we show in advance how they grow with the number of enquiries. We give the timeline together with the price.
Questions
Will the bot start making things up for customers?
A language model can make a confident mistake, so we constrain it. Answers come only from your knowledge base, prices and terms are pulled from the source, and doubtful questions go to a person. We review the conversation log and turn errors into new rules and checks.
A regular bot or one with AI?
If customers pick from clear options, buttons are cheaper and more reliable. A language model pays off when people write free text, send files, or ask questions too varied for a decision tree. A common setup is buttons at the start and AI for the open question.
Which process should we automate first?
One that repeats often, is easy to verify and costs a lot when done by hand. Usually that is first replies to leads, moving data into the CRM or preparing product cards. Inside our own studio, similar pipelines score incoming leads and compile project summaries, and the final decision always stays with a person.
Can you connect the bot to our CRM?
Yes, if the CRM has an API or webhooks. Most popular systems do. For older systems without an API we set up an exchange through spreadsheets and files. We confirm the method during discovery, before the estimate.
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