AI automation for small businesses: agents that do real work
Most AI automation pitches are demos. The agents on this page run in production: one manages Meta ads every 20 minutes, one screens job candidates on WhatsApp, and one sells course access inside Telegram.
Small businesses and agencies with repetitive work in sales and marketing
You get
An agent or workflow in production, with limits, logs and handover
Built with
Claude and OpenAI models, Python, MCP and the APIs you already use
Price
Fixed, agreed in writing
In short
Lysechko Digital builds AI automation for small businesses: AI agents that manage ads within set limits, chatbots that answer and qualify leads on WhatsApp, Telegram or your website, CRM workflows, reports, and MCP servers that give AI assistants your data. Eva, an AI marketing agent, paused 64 ad sets, made 32 budget changes and launched 10 campaigns in two weeks, and every action is logged.
64ad sets paused by an AI agent in two weeksall within set limits
195screened leads from 526 chatbot conversations
11tools in an open source MCP server
5clients running their own Telegram bot on one engine
What AI automation is good for
The best tasks to automate are frequent, text heavy and rule based, with a clear limit on what can go wrong:
Answering and qualifying new leads within seconds, at any hour.
Following up with people who stopped halfway.
Watching ad accounts and acting inside limits you set: pausing, shifting budget, swapping tired creatives.
Morning and evening reports in the chat your team already uses.
Drafts of ads, banners and replies that a person approves.
Tasks that need judgment without data, or actions that cannot be logged and undone, stay with people.
Agents with limits, logs and a person in charge
An agent that touches money or customers needs guard rails. Every agent I build has a list of allowed actions, hard limits such as a daily cap on budget changes, a log with the reason for every action, approval steps for anything risky, and a watchdog that alerts you if the agent or a connection stops. Eva, the AI marketing agent in the case study below, works this way: she changed budgets 32 times in two weeks, all within the daily cap, and the team can read why.
What I have built
Eva: an AI marketing agent that manages Meta ads, reviews Google Ads search terms and reports in the team chat.
A WhatsApp chatbot that screens job candidates and creates CRM leads with the ad source.
A Telegram bot that sells access to paid groups and courses, used by five clients.
MCPOrbital: an open source MCP server that gives AI assistants sourced data through 11 tools.
An AI automation agency gives you a team and a process. A specialist gives you one person who builds the automation and also understands the ads, funnels and CRM it plugs into. For a small business the second is often the faster route, because most automation fails on the business details, not on the AI.
Costs to plan for
The build has a fixed price in writing. Running costs are paid by you directly to the providers: AI model usage, hosting, and messaging fees on platforms such as WhatsApp. They are usually small next to the time saved; the WhatsApp chatbot in the case study replaced a paid service that cost 90 USD a month.
How it works
Find the task. A short call about the work that eats your team's time, and which part an agent can take over.
Map it. Inputs, rules, limits, approvals and what success looks like, in writing.
Build and test. The agent or workflow, with test cases that must pass before launch.
Run with logs. A first period where every action is logged and checked, then full speed.
Handover. Code and accounts in your name, documentation and a watchdog alert.
AI automation case studies
An AI agent that manages Meta ads, a WhatsApp chatbot that screens candidates and fills a CRM, and an open source MCP server.
An AI automation agency finds repetitive work in a business and hands it to AI agents and workflows: answering leads, follow ups, reports, data entry and monitoring. Lysechko Digital does the same work as one specialist.
How much does AI automation cost for a small business?
The build has a fixed price in writing, based on the task and the systems it connects to. Running costs such as AI model usage and hosting are paid directly to the providers.
Is it safe to let AI change my ad account?
Only with limits. My agents have a list of allowed actions, daily caps, a log with the reason for every change and alerts. Risky actions wait for a person's approval.
Which AI models do you use?
Models from Anthropic (Claude) and OpenAI, chosen per task by quality and cost. The code is yours, so the model can be changed later.
What is an MCP server?
The Model Context Protocol (MCP) lets AI assistants such as Claude call tools and fetch data from your systems, with permissions you control. MCPOrbital is an open source example with 11 tools.
Can the automation work with my CRM?
Yes, through the CRM's API or webhooks. The WhatsApp chatbot in the case study creates leads with the campaign, ad set and ad in the client's CRM.
I have worked with ads on Google, Meta and TikTok for more than seven years and personally managed ad budgets from $1,000 a day up to $50,000 a month. For the last two years I have built websites, automations and AI assistants with AI every day. I work remotely with clients in Norway and abroad, and every number on this page comes from a project you can open in the case studies. LinkedIn
Related services
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