Business process automation with AI
We automate processes where staff manually move data, write similar replies and compile reports: enquiry handling, marketing, sales, documents and internal operations. We build scenarios in n8n and custom services and add language models where text must be understood, a rule-based decision made or a draft prepared. Each scenario gets a log, error notifications and a clear owner.
Processes we automate
Enquiry handling: parsing emails and forms, extracting data, creating deals, replying to the customer and notifying a manager. Marketing: preparing posts and mailings, collecting data from ad accounts and analytics into a single report, checking pages after changes. Sales: lead qualification, reminders, template-based proposals. Operations: reconciling data between systems, generating documents, deadline control.
Tools: n8n, APIs and custom services
For scenarios with ready integrations we use n8n: it connects CRM, email, messengers, spreadsheets and language models with little code and runs on your server. When complex logic, high load or large data volumes are involved, we write separate services in Docker with queues and tests. The approach follows the task: some processes are simpler in n8n, others are more reliable in code.
The role of AI in a scenario
A language model is used in the steps where free text must be understood, an enquiry classified, data extracted from a document or a draft reply prepared. Actions with consequences, such as emailing a customer, changing a deal or making a payment, follow rules and are confirmed by an employee where needed. Automation stays predictable and AI does not make decisions that are hard to undo.
What the work includes
The project covers process review, scenario building, testing and hand-over.
- Process map: steps, systems, data, owners and exceptions
- n8n scenarios or services with queues and retries
- Integrations: amoCRM, Bitrix24, 1C-Bitrix, Google Sheets, Telegram, email, telephony
- Model calls for text parsing, classification and drafts
- Staging, checks on real data and acceptance
- Execution log, error notifications in Telegram, reports
- Deployment, rollback and scenario change documentation
How the work is organised
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Step 1
You describe the process and send examples: emails, enquiries, spreadsheets and reports you compile by hand.
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Step 2
We map the process, choose tools and define where AI is needed and where rules are enough.
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Step 3
We build scenarios on staging and check them on real data together with your team.
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Step 4
We launch, set up monitoring and notifications, hand over documentation and train staff to make changes.
Cost of automation
The cost depends on the number of processes and steps, integrations, reliability requirements and AI involvement, as well as infrastructure. Servers and model usage are estimated separately. For an estimate, send a description of the process, sample data and the list of systems.
Frequently asked questions
Do we need our own server for automation?
A small VPS or your own server is enough for n8n and services; we prepare the infrastructure and backups. n8n cloud plans are also possible when data may be stored with the provider.
Can a process be automated without AI?
Yes. Many tasks are solved with rules and integrations. AI is added only where free text is involved or decisions are hard to describe with rules.
How is the automation monitored?
Every scenario run is logged; errors and stops reach the team in Telegram or by email. For important steps we set up employee confirmation and daily health checks.
What happens when an external service fails?
Scenarios use queues and retries; unprocessed tasks are not lost but wait for the service to recover or go to an employee with a notification.
Will we be able to change scenarios ourselves?
Yes. n8n scenarios are edited in a visual interface, and for services we hand over documentation and settings. Team training is part of the hand-over.
How much does automating one process cost?
It depends on the number of steps, integrations and reliability requirements. After the process review we give an estimate and suggest starting with one scenario to measure the effect.