AI for business
- Price
- from $3,000
- Timeline
- 2–6 weeks
- Experience
- 100+ projects · 10+ years · 9+ countries
We bring AI into your workflows: Telegram bots, AI agents, assistants and routine automation
- OpenAI
- n8n
- Telegram
Our usual stack. We bring in other tools when the task or the project calls for it.
AI pays off not on its own but when it’s built into a process: answering customers in Telegram, triaging leads, drafting documents, finding answers in the company knowledge base. We find where your team does the most manual work and build a tool that takes it over.
We build on language models, n8n and custom code and connect everything to your CRM, messengers, email and spreadsheets, so AI works with real data, not in a separate chat window.
What we build
- Telegram bots with AI for customers and staff
- AI agents that carry out tasks in your tools
- Website and support assistants grounded in your knowledge base
- Automated processing of leads, emails and documents
- Plain-language summaries and reports
What you get
- Less routine for the team and faster answers for customers
- A solution inside your tools, not yet another tab
- Quality control and human review where it matters
- Clear model running costs at your volumes
AI pays off once it’s in the process
- 78%of AI users bring their own AI tools to work, putting company data at riskMicrosoft, 2024
- 80%of respondents say AI has improved their individual productivityMcKinsey, 2026
- 37%of respondents say AI has contributed to company EBIT — gains need a built-in processMcKinsey, 2026
Where AI starts paying for itself
Reps spend half the day copying email details into the CRM
We find tasks like this while mapping your processes and measure the hours they eat. The model pulls the fields from the email and creates the deal; the rep just checks it.
We tried ChatGPT, but it never got past experiments
Nobody opens a separate chat. We put the model where work already happens — CRM, email, Telegram — and give it access to your data, not just general knowledge.
We're afraid the AI will tell a customer something wrong
We set boundaries: answer only from the knowledge base, hand off to a person when unsure. Before launch we run it on real questions from your inbox and review the misses.
Customers wait until morning for a reply in chat
A bot or assistant answers common questions instantly at any hour and passes the hard ones to a rep along with the conversation history and customer data.
Company know-how lives in a few people's heads
We build a knowledge base from your policies, documents and past conversations. New hires and the bot look things up there instead of pinging senior staff.
What we work with
- AI automationAI in your workflows: lead triage, summaries, reply drafts and reports
- AI Telegram botsBots for customers and staff: they answer, book, take leads and work with your data
- AI agents on n8nAgents that carry out tasks in your tools: they search, fill in, send and report back
- AI assistants for website & supportA website and support assistant that answers from your documents and hands complex cases to a person
AI that pays for itself
Start with the grind
We look for tasks where people spend hours on text work that follows the same rules — that’s where AI pays off fastest.Pilot first
We launch one task on real data, check the quality and only then extend the solution to other processes.People make the call
For the steps that matter — replies to customers, CRM changes, documents — AI drafts and a person approves.The model fits the task
We pick a model for quality, cost and data requirements, not hype. Self-hosted on your server if needed.Grounded in your data
We connect AI to your CRM, email and knowledge base, so answers rest on company facts, not the model’s general knowledge.
Who should bring in AI now
A good fit if
- Your team does a lot of repetitive text work: emails, leads, documents, chats
- You have a CRM, inbox or messenger we can connect to through an API
- Someone on your side can review what the AI does during the pilot
- You'd rather start with one process and expand once it proves itself
Not a fit if
- The process isn't settled and runs differently every time — we'll help you document it first
- You want AI for a slide deck with no measurable task — on a call we'll find where it pays off
- A plain workflow without a model would do — then we'll honestly suggest simple automation
How we work
- 01
Finding the tasks
2–3 daysWe review your processes and pick the ones where AI saves the most time.
You get A shortlist of processes with expected impact and one picked for the pilot - 02
Pilot
1–2 weeksWe build a working version for one process and test it on real data.
You get A working pilot on your data plus measurements of the time it saves - 03
Integration
2–10 daysWe connect the solution to your CRM, messengers, email and knowledge base.
You get The solution runs inside your tools with no manual copy-pasting - 04
Quality control
2–5 daysWe set up checks, logs and alerts and measure accuracy.
You get Logs, error alerts and an accuracy report on a test sample - 05
Launch
1–2 daysWe switch the process over, train your team and outline which processes AI should take on next.
You get A team guide and a 3-month bug warranty after launch
Who builds your AI tools
An AI engineer leads from picking the process to the pilot, then works with a developer and a QA analyst on integration and accuracy.
AI engineer
Picks the model, writes the prompts and agent logic, builds a pilot for one process and tests it on your data.Integration developer
Plugs the bot or agent into your CRM, email, spreadsheets and knowledge base so AI works with live data.QA analyst
Builds test sets of real questions, measures answer accuracy and sets up logs that show where the model slips.Telegram bot developer
Builds the bot itself: commands, buttons, dialog flows and a handoff to a human when the conversation needs one.Project manager
Switches the process over, trains your team and lists the processes AI should take on next.
People, a chatbot or an AI agent
| Manual work | Scripted bot | AI agent | |
|---|---|---|---|
| How it works | A person reads, decides and does it all | Follows predefined buttons and branches | Understands plain-language requests and calls the right tools |
| Unusual requests | Handles them, but slowly | Doesn’t understand — hands off or gets stuck | Handles most, hands the hard ones to a person |
| Speed | Depends on workload and office hours | Instant, around the clock | Seconds, around the clock |
| Cost | Grows with volume — you need more people | Built once, then nearly free to run | Build cost plus model usage per request |
| Quality control | The person’s experience and attention | Predictable: does only what’s scripted | Needs rules, a log and human review of key steps |
| Best used for | Complex negotiations and decisions | Simple repetitive flows | Repetitive work with text and data |
| Discuss AI adoption |
What to prepare before we start
- The tasks that take up most of your team's time
- A couple dozen real inbound items: emails, leads, customer questions
- The tools your team works in: CRM, email, messengers, spreadsheets
- Policies, FAQs and documents the AI can rely on
- Data constraints: what can and can't be sent to external models
- Someone who knows the process inside out and can judge the pilot
A free process walkthrough
In 30 minutes we walk through your processes and mark where AI would remove the most manual work. The call is free. Afterwards we send a pilot plan, a timeline and an estimate.
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Where could AI
take over the grind?
We’ll find where your team does the most manual work, run a pilot on your data and connect what works to your CRM, messengers and email.
With one process full of repetitive text work: customer replies, lead triage, documents. A pilot in a couple of weeks shows the real effect before bigger investment.
From $3,000. The total depends on how many processes go into the first phase, which systems the AI connects to (CRM, email, knowledge base, internal tools) and your data requirements: a hosted model via API or an open model on your own server. We send an exact estimate after a 30-minute process walkthrough.
We pick for the task and your data requirements: models from major providers via API, or open models on your own server.
We use plans that don’t train on your data, or models on your server, and pass the model only what the task needs.
More often it takes routine off their plate: drafts, triage, search. Decisions where mistakes are costly stay with people.
Usually little compared to the time saved. We estimate costs at your volumes during the pilot.
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