AI systems built for your business — they answer customers, run your marketing, close your sales.
Not a chatbot, not a one-size-fits-all template. I build a system of agents around your processes, your data and your voice — and take it all the way to results, not to a pretty demo. A system like this has run my own business for a year: last month it carried dozens of customers to a placed order, almost without a human.
Today everyone can code. Anyone can throw together a chatbot over a weekend and go sell it — which is why the market is flooded with demos that look great on video and fall apart on the second real customer.
Between “I need customers answered and leads not lost” and a working system there's usually a chain: a project manager, an analyst, a marketer, a developer. Meaning leaks at every handoff, and what ships isn't what the business meant.
I close that whole chain alone. 20 years in business, marketing and sales: I'm the entrepreneur, I run the marketing, and I build the system with my own hands. I don't need to explain to a developer what the business wants — because I am the business.
So I don't sell “a bot”. I take your business apart and build a system around it — and I own the fact that it works on real customers, not on video.
Everyone's reporting about AI. Yet no one has a clear answer to “what should I actually implement”.
And while you're thinking it over, here's what's happening.
A client writes at 23:40 and gets a reply at 10am. By then they've already bought from whoever answered first.
You've already paid for a bot or a freelancer, got a pretty shell that can't answer real questions, and quietly switched it off.
Every manager answers as best they can: forgets promos, mixes up prices, and sale quality depends on their mood.
The team can't keep up with the messages, and some leads simply get lost.
Off-the-shelf services are generic: they don't know your product, your audience or your voice — so they answer wide of the mark.
There aren't enough hands for content and analytics, and growing the team is slow and expensive.
In the end everything rests on you, and growing out of that is hard.
Sound familiar? Then let's get to the point.
It's not that the technology is raw. It's the gap between business and execution.
An off-the-shelf solution is a “for everyone” kit: at best it answers with templates. A vibe-coder builds a demo over a weekend but won't own your real scenarios, prices, objections and the handoff of a hot lead. Full-scale development means a team and months, where half the budget goes on getting everyone to finally understand each other.
I close the gap because I combine three roles that usually sit in different people.
The difference shows on the first awkward question. A demo starts making up prices just to say something.
My agent works the opposite way: unsure of a price — it double-checks itself, and at worst silently hands the chat to a human. One made-up price costs more than a hundred correct answers.
Understands why the business needs it.
Understands the customer.
Builds it.
conversion to a placed order — almost one in three who wrote in and left a contact made it to a purchase
A year ago I built a system like this for my own running business — official distribution of professional cosmetics. Not a demo, but a live one, on real customers.
Over a single month the agent, on its own, with no manager, ran the social-media conversations, collected contacts and carried people to a purchase. First reply — in seconds, any time of day, not “in the morning when the manager shows up”. For social messaging, where most conversations usually go cold with no reply, that's a different order of numbers.
If in the session I don't see that AI will give you a real return — I'll say so straight and won't take money for a build. The implementation map stays with you anyway.
An agent for marketing, an agent for sales, and a system where they work together.
Separately or as a single organism. Tap to expand the details.
Generates content in your brand's voice: posts, stories, rubrics, briefs for the designer. For several brands at once, each with its own tone.
Pulls social analytics every week: reach, engagement, saves, follower growth, ad performance — from real sources into a dashboard and a clear summary.
Monitors competitors: activity, engagement, promo launches and spikes — what works for them and what doesn't.
Mines competitor audience comments: pulls real pains in customers' own words and turns them into content topics.
Rolls everything into a “thesis of the week” and a content plan — concrete topics, based on data, not intuition.
Writes results where you work: Google Sheets, knowledge base, Notion integration. Works inside the team's chat.
Answers in Instagram and Telegram 24/7 in your brand voice — warm and to the point. Other channels (website, WhatsApp) on request.
Knows the whole range: prices, ingredients, services, promos. Unsure of a price — it double-checks itself, at worst silently hands off to a human rather than lying.
Doesn't “think out loud” in the chat. The customer sees only the finished answer, not the model's internal reasoning — there's separate filtering behind that.
Qualifies the lead on the spot: tells a professional from an end customer (including by a photo of a document), guides each down their own path.
Hands out lead magnets automatically: on a keyword it sends the right guide, with no manager and no sending the same file twice.
Follows up on “let me think about it”: comes back on its own with a personal message based on the conversation, with limits and only at a reasonable hour.
Gently passes a hot lead to a manager: notifies the owner, logs the contact and segment in the CRM, and stays in the chat until a human takes over.
Works with post comments — moves an interested person into DMs and replies publicly.
A second layer — manager's copilot: mid-conversation it suggests a script, an objection response, an upsell technique.
Logs everything in the CRM: contact, segment, deal stage, conversation notes.
A shared source of truth. Prices, keywords, lead magnets, knowledge base in one place. Update it once — every agent sees it instantly.
Consolidate signals: social media, competitors, comments, sales, CRM come together into one picture.
Pass conclusions to each other: the analytics layer tells the content agent what to publish and the sales agent what to push.
Enter data themselves into sheets and CRM and propose decisions — the human confirms the final call.
One or two people start carrying what used to need a whole department. The machine takes the routine; the decision stays with the human.
Tracks business and personal tasks in one place: reminds, holds context, nothing gets lost.
Consolidates your agents: brings a short digest instead of ten scattered reports.
Separates contexts: knows what's work and what's personal, and doesn't mix them up.
Answers your questions from your own data — from “how are leads doing this week” to everyday reminders.
And not only business. The same approach builds agents for personal life — a coach for health, nutrition and routine, for example. The system is flexible: if a task has data and a repeating process, you can build an agent for it. We'll discuss what's useful for you in the session.
An off-the-shelf solution is something you bend to fit yourself. I do the opposite — I bend the system to fit you.
The agent runs on your range, prices and history, not on abstract examples.
Knows the difference between your segments and speaks to each in their language.
Answers the way your brand speaks, not like a “support robot”.
Built into how you actually work: your channels, your CRM, your sheets.
A vibe-coder ships the demo and vanishes. I keep tuning the system on real customers.
This isn't a subscription to someone else's engine. It's a system built for your specific business.
The agent, the database, the message history and the access live in your perimeter, on your server. Only specific requests go out to services you already use: the model (Claude), Instagram/Meta, your CRM.
Access is stored in environment variables on your server, not in code. By design the agents don't leak the contents of the database, price lists or keys, even if a client asks directly — tested on live conversations.
I don't make you learn a new service. The agent plugs into where you already work. In the live system the managers simply work in their familiar Bitrix and Telegram.
Runs as a service on a server: recovers on its own after a crash, jobs run on schedule. If an external service is down or the model is unsure — it falls back to a safe path instead of making things up.
TypeScript · deployed on your server. The architecture isn't tied to a single model — right now it's Claude, swappable without rewriting the system if needed.
Where to store, which channel to talk through, what to automate first — we decide for your situation in the session.
Data and conversations stay in your perimeter in the EU, processing under GDPR. What can be anonymized is; what doesn't need storing isn't. For EU clients this isn't an option but a requirement — built in from the start.
Every agent action is recorded — you can always pull it up and check what it answered and why. The behavior is tested on real live conversations, not just demo examples.
I look at your processes and find one or two with the fastest payback.
I make the agent around your products, your voice and your rules.
I connect it to your channels and CRM, deploy it in your perimeter.
I train you and the team; the final word always stays with a human.
I keep tuning it after launch on real customers.
All I need from you is access and a couple of calls. The rest is on me.
You sell through messaging and lose leads while you think it over.
You have a range, prices and processes that can be described.
You want a system that works on customers, and you're ready to give access.
You want a cheap “weekend bot” with no involvement from you.
There are no real sales or processes yet — there's nothing to automate.
You're after a magic button and won't leave the final call to a human.
● I take 2–3 projects a month — to carry each to a result, not to a demo.
1 agent / 1 process. Launch ~2 weeks.
2 agents, omnichannel + CRM. ~3–4 weeks.
Several processes, ongoing development.
Start — 50% upfront.
The monthly covers hosting in your perimeter, monitoring, support and iterations, plus model costs within your volume; beyond that — at cost.
For comparison: one in-house SMM or salesperson costs €2,000–3,000 a month and goes on holiday. The system runs 24/7 and pays back not with “image” but with recovered money — night-time leads, forgotten promos, lost prospects — that's leaking right now.
You walk away with a concrete implementation map: which one or two processes to automate first, what it gives in money and time, and in what order to do it all. Even if you don't go into the build, the map stays with you.
Go into the build — I deduct the €200 from the cost. For those who implement, the audit is essentially free.
If in the session I don't see that AI will give you a real return — I'll say so straight and won't take money for a build. The implementation map stays with you anyway.
Book a strategy session →Drop a few words about your business on Telegram or WhatsApp — and we'll set up the session.
My name is Diana Sharova. I've spent 20 years in business, marketing and sales.
I built and run a company — official distribution of professional cosmetics. I know from the inside how real sales, customer conversations and a sales team actually work, because I've done it myself, not read it in a book.
When strong AI models arrived, I didn't go hire a team of developers. I figured it out and built a system of agents myself — for my own business. Now it answers my customers every day, runs analytics and helps sell.
Between “what the business needs” and “what actually works” there's no broken telephone with me — I both set the task and build the solution.
An engineer who understands the economics of a business and feels the aesthetics of communication — a rare combination. That's exactly what makes it possible to build systems that both work and sell.
The case is from beauty, but the system isn't about the industry. It's about messaging, leads and content — and that exists in any business that sells through conversation. In the session I look at your processes specifically.
A cheap bot is an “if-then” script that breaks on a live question. I build a system on your data, with protection against made-up answers and handoff of the hard cases to a human. And I support it after launch instead of disappearing.
For recovered money that's leaking right now: night-time leads, forgotten promos, lost prospects. One such stream is usually worth more than the agent. In the session I work it out on your numbers.
Yes. The agent and the data live on your server, the keys in a protected environment, the database contents aren't handed out. More in the technical section.
Pilot — about two weeks, business build — three to four. From you I need access and a couple of calls; everything else is on me.
If in the session I don't see value for you — I'll say so honestly and won't take you into a build. The implementation map stays with you regardless.