Turnkey AI agents
An agent for your process: support, sales, analytics, moderation. We integrate it with CRM, ERP and messengers and fine-tune it on your data. Example: the Ceresit AI radar built for Henkel.
The studio of Zhemal Khamidun — Head of AI at an EdTech group, CPO of an enterprise AI platform with 6000+ users — builds AI agents, AI-CRM and automation tailored to your process. Turnkey, with full ownership transfer: not 'yet another chatbot' but a working system.
Zhemal Khamidun — lecturer at a leading technical university · enterprise Agile transformation, 1300+ specialists · ex-Accenture
AI-native development is already here: vibecoding gives us x5–x10 the speed of traditional development, and we ship real systems at this pace — 21 in production. You get the speed of a team of dozens of engineers without growing headcount. The only question is whether you order this pace — or your competitors already have.
While the market debates whether AI will 'take off', we ship working systems built on it: 21 projects in production — AI agents, AI-CRM, automation. Here are the numbers behind why this is happening right now:
'A team of 10 people with AI does the work of 50–100 engineers'
The only question is who will build this for your business: your own experiment, or a studio that has already shipped 21 systems.
Solo developers and non-technical founders are already launching AI products with metrics in the millions — the technology has matured. For a business, the only question is who will build it around your process — with integrations, security and ongoing support. Live examples of what already works:
ZY
$2 Mper month
Zach Yadegari · 18 years old
Single-handedly built the AI app Cal AI: 5 million downloads, $30 million in annual revenue.
TechCrunch ↗
MS
$80 Msold to Wix
Maor Shlomo · solo founder
Built the app builder Base44 alone and sold it to Wix within six months. $189k profit per month.
TechCrunch ↗
SM
$456kper year
Sabrine Matos · marketer
Not a developer. Built the service Plinq in 45 days — 10,000 users.
Source ↗
ML
1 dayper product
Marc Lou · indie maker
Launches profitable AI apps in a single day. Dozens of launches, each generating revenue.
marclou.com ↗
Solo makers do this on pure enthusiasm. Your business gets the same, turnkey — from a studio with 21 shipped systems, integrations and SLA-backed support.
On our side, the process is simple — four steps:
If even one applies to you, it's not 'just how things are' — it's a process an AI system can take over. We've done exactly that 21 times.
We go by jobs to be done, not job titles. Here are the three jobs clients bring us most often — if you recognize yours, you're in the right place.
SMB owners and directors
Managers drown in requests, reports are compiled by hand, every process bottlenecks on you. We build an agent or automation for your process: requests stop getting lost, routine runs itself 24/7, headcount doesn't grow with volume. Our portfolio includes SMB cases from a restaurant to a tutoring school — no Enterprise budget required.
Innovation and L&D leaders in corporations
The board asks 'where's our AI?', while ~40% of pilots on the market shut down before reaching production. We deliver a pilot with a measurable result inside your infrastructure and train your team — you get a working case and numbers to present upstairs. We know this level of requirements from working with Henkel and enterprise clients in energy and banking.
Heads of sales and operations
Managers don't enter data, leads leak between touchpoints, decisions are made blind. We build an AI-CRM that AI runs itself: it captures and qualifies every lead, and the dashboard shows the truth about your sales. Proof: turnkey Phoenix CRM and 6000 B2B leads collected by automation.
Founders and product teams
You have the idea, but development means months in a queue or an expensive staff. We build an MVP sprint: a working prototype on your scenarios within a fixed timeline — vibecoding gives us x5–x10 the speed of traditional development. Then we either scale it to production, or you close the hypothesis at minimal cost.
No need to hire a dev team or break your familiar tools
Your CRM, ERP, messengers and spreadsheets stay in place — we build on top, not instead. We take one process currently done by hand or by a contractor, build an AI system around it — and you compare speed, cost and control on real numbers.
A fit for anyone whose process is still done by hand — and it's holding back growth
For owners, corporate teams, heads of sales and founders. No in-house IT department needed: we handle the technical side — from architecture to deployment in your infrastructure. Not sure it's your case? Let's walk through your process on a free consultation. How a project goes →
You come with a process done by hand. You leave with a working turnkey AI system: the code, access and documentation remain your property.
A composite portrait of the studio's clients: what they come with — and what they're left with after launch. Scope and timeline are fixed before work starts.
A GPT demo takes a week to build — and dies at integration with real work systems. We build differently: the AI system embeds into your CRM, ERP and messengers, runs 24/7 and is transferred to your ownership. Not an experiment but a working process — with someone accountable for the result.
Our vibecoding process gives us x5–x10 the speed of traditional development. You get your hands on a working prototype at the very start of the project — not 'after six months of research'.
We hand over the code, access and documentation. No vendor lock-in: you can evolve the system with us under an SLA, with your own team, or with any other contractor.
The goal and acceptance criteria are fixed before the start, payment is milestone-based. The impact shows up in dashboard numbers — that's how 21 systems were delivered, including projects for Enterprise clients.
Not consulting and not slide decks — working systems in your infrastructure. We take a process, build an AI system around it and transfer it to your ownership: with code, access and documentation.
An agent for your process: support, sales, analytics, moderation. We integrate it with CRM, ERP and messengers and fine-tune it on your data. Example: the Ceresit AI radar built for Henkel.
A CRM and dashboard where AI enters the data: leads are captured and qualified automatically, you see the truth about your sales — not just what managers managed to log. Proof: turnkey Phoenix CRM, 6000 B2B leads.
Pipelines, dashboards, content factories and PM systems: routine goes to the machine, the team focuses on what grows revenue. Proof: 6000 B2B leads by automation, a news factory in 6 languages.
The main thing — the process starts working without you
The agent answers customers 24/7, the CRM runs itself, the dashboard shows the truth in numbers. Headcount doesn't grow with volume — the team focuses on what grows revenue.
Claude Code, Codex, n8n, RAG — our production stack. We integrate with your CRM, ERP and messengers — vibecoding gives us x5–x10 the speed of traditional development.
10+ years in digital transformation — an enterprise Agile transformation (teams and products with 1300+ people), Accenture, corporate consulting for Enterprise
CPO of an enterprise AI platform — his own AI product in production: 6000+ users · implemented AI in the business processes of 54 companies
21 systems shipped to production and 856 hands-on cases · trained 1000+ specialists across 200+ corporate trainings
I build AI in production every day: as Head of AI at an EdTech group, as CPO of an enterprise AI platform with 6000+ users — and as a studio that has built systems for Henkel and enterprise clients in energy. I don't consult from slides — I'm in the code, the deployments and the metrics myself.
That's why I only offer what I've already built and use myself. Bring your process — I'll personally break it down and show you which system will do the work for your team.
Letters of appreciation from Henkel and other enterprise clients in energy, retail and banking — for corporate projects and team training. That's the level of requirements we're used to delivering at.
Trained teams at:
Not a middleman agency with subcontractors: a compact team of practitioners led by Zhemal. The people you see here are the people you'll see working on your system.
Designs AI agents and embeds them into companies' business processes — from brief to production
A graduate of a leading technical university — takes any blocker apart systematically, down to the root cause
On your project — your implementation engineer: deployment, access, integrations and fine-tuning, all the way to a working system in your infrastructure
5+ years in IT startups: launched StorySong (AI songs, up to $6K/month, sold) and 'Revive Photo' (~11K users)
YouTube and Telegram about AI — 11K subscribers, 17M views · master's degrees from two leading technical universities
On your project — marketing and growth: so the system we build brings leads and revenue, not just runs
Real systems with real numbers: Enterprise brands, small businesses and the studio's own products. Click a card to see the details.
All numbers come from the studio's real projects. Some systems are under NDA — we show those cases as screenshots and walk through the details on a free consultation.
No 'months of research, then we'll see'. The project moves through clear stages: you know in advance what you'll get at each one, watch the system come together, and pay per stage. The stack is transparent: Claude Code / Codex, n8n, ERP and CRM integrations, RAG on your documents.
We immerse ourselves in your process and, before work starts, define exactly what we're building and how we'll measure the result — in your business's numbers, not in 'we'll implement AI'.
Stage artifacta brief with the goal, scope and acceptance criteria — it becomes the basis of the contract
goal, scope and project plan locked in; price and timeline named before work starts
We build a working prototype on your scenarios — you evaluate the solution hands-on before paying for the full build.
Stage artifacta working prototype + solution architecture and a full-build estimate
a prototype you can show your team and leadership, and a precise project estimate
The prototype becomes an industrial-grade system: tests, error handling, resilience — production that doesn't fall over, not a demo.
Stage artifactan assembled system that has passed tests on your scenarios
the system is ready for integration with your work tools and launch in your infrastructure
The system lands in your infrastructure and connects to your work tools. This is exactly where most AI pilots die — and exactly the step we take on ourselves.
Stage artifacta system in production, integrated with your CRM, ERP and messengers
the system runs on real data in your infrastructure — your team starts using it
We don't disappear after launch: we monitor, fine-tune on your data and evolve the system along with your process.
Stage artifactregular reports on system metrics + a development roadmap
the system lives on and delivers measurable results — instead of gathering dust like abandoned pilots
The project ends with an ownership transfer. The system, code and knowledge stay with you whatever you decide next: no vendor lock-in.
a working system you own, a trained team and business result numbers
A turnkey system isn't a repository with a 'figure it out yourselves' note. We transfer ownership and stay close: documentation, team training, SLA-backed support.
We implement the system and train the people who will work with it — so it delivers results instead of gathering dust within a month.
We don't disappear after launch: monitoring, fine-tuning, system development and support with guaranteed response times.
Servers, model access, paying for AI services — including when local cards are not accepted. We take the organizational side on ourselves.
The project doesn't end with 'we emailed you everything' — it ends with a handover day: we show the system at work, transfer it to your ownership and train your team. Here's what you get at launch:
A system counts as delivered when it works at your company and there are trained people to run it — not when the last commit is pushed. We bring it to working condition within the fixed scope; further development and SLA-backed support are a separate option, with terms discussed individually.
Launching the system isn't the finale — it's the start of operations. Under a retainer model, we keep it on course: SLA-backed support, monitoring and alerts, fine-tuning on your data, upgrades for new processes. The AI stack changes every month — we keep the system updated so it doesn't fall behind. That's how we run 21 systems in production. The scope and volume of support — discussed individually.
Take 10 seconds to estimate what your manual process costs — and how much automation would return. A system usually pays for itself within the first months of operation.
60% of routine operations are handled by the AI system — we calibrate the share by process type, based on our project experience. GitHub: +55% work speed ↗
Market benchmark: a website + CRM + bot in traditional development usually starts from $50,000 and six months. Vibecoding gives us x5–x10 the speed — we’ll name your project’s price after a free audit.
Without AI capture, some requests simply never reach the CRM: a manager didn't log it, didn't call back, forgot. Across the market, roughly one in ten is lost.
100 requests × 10% lost × $5,000 = up to $50,000/month leaking away
This is an estimate, not an exact calculation: the real leak only shows in your funnel. We'll break it down on a free audit — along with how much of it an AI-CRM would recover.
This is an approximation: 4.33 working weeks per month. We'll calculate the exact economics for your process on a free audit — along with the project price and payback period. All amounts are in USD.
And that's just the savings. An AI system can also earn: an agent answers a request within a minute and pushes it to a deal, an AI-CRM doesn't lose leads — we've collected 6000 B2B leads for clients with automation. What that means in money for your funnel — we'll calculate on a free audit.
Usually a system like this is assembled piecemeal: one team does development, another does integrations, documentation and support come 'as an afterthought'. We deliver everything as one project — and transfer it to your ownership:
When a system is assembled piecemeal — studio, integrator, technical writer, support — you pay for and manage every seam between contractors yourself. We deliver the system with one team and one contract: code, infrastructure, access, documentation, training and support. The price is fixed for your scope after a free audit — payment is milestone-based.
Choose an engagement modelWhile you're choosing a contractor, get real value for free. We'll break down your process, show what can be automated, and honestly tell you where AI will pay off — and where it won't yet. No obligations: request — review — a short report.
We map how the process works now: where requests, hours and money get lost. We find the spots where AI will deliver impact fastest.
online, via ZoomWe show what the solution will look like: architecture, integrations, timeline. For suitable tasks — a clickable prototype.
architecture + timelineA short document: what to automate first, what later, and what not to touch. It stays with you even if we don't end up working together.
yours to keepServers, model access, paying for AI subscriptions when local cards are not accepted — a frequent blocker for corporate projects. We take this part on ourselves so the project doesn't stall over a card or a VPN.
Message us on Telegram — we'll discuss the task in chat. Or leave your email: we'll ask a couple of clarifying questions and suggest a time for Zoom.
Chat on TelegramMessage us on Telegram — we'll ask 3–4 questions about your process and honestly tell you whether automation makes sense.
The format depends on the task: test a hypothesis, build a system end to end, or evolve what's already running. Price and timeline are fixed before the start — after a free process audit. Payment is milestone-based; we work under contract with legal entities.
We work under contract: invoice from a legal entity, NDA, closing documents. Payment is milestone-based — tied to the stages in the brief. We'll pick the exact format and budget on a free consultation.
Built by the team of Zhemal Khamidun — Head of AI at an EdTech group, CPO of an enterprise AI platform with 6000+ users · 21 systems in production · Enterprise clients in energy, retail and banking
We work with legal entities: invoice, contract, NDA and closing documents. Pilots in a private environment and on-premise — we align the architecture with your security team.
We don't just build AI systems for clients — the studio has its own product. Nomad is an agent app: Claude Code runs on your computer while you direct it from your phone — from a taxi, on a walk, between meetings. An idea strikes — you message the agent; you open your laptop in the evening — the prototype is already built. That's the level of product we deliver.
You write in plain language, no commands or code. The agent plans, does the work and shows the result on its own.
Phone, tablet, messengers — the agent is reachable wherever you already chat.
It runs on top of Claude Code with the studio's battle-tested configuration — hundreds of ready-made skills in action.
Every result is saved as an artifact: back at your laptop, you pick up right where you left off.
Below are live app screens, not images — browse with the arrows.
Nomad is nomadnet's own product. Want this level of quality for your own process — let's talk. agent.nomadnet.ai →
4 short questions — we'll show you exactly where to start: an agent, an AI-CRM or automation.
Answer 4 questions about your process — at the end we'll show the right type of system and a similar case from our portfolio. Any result can be discussed on a free consultation.
1. What matters most to solve right now?
2. Where does the team lose the most time?
3. How many people will the system affect?
4. When do you need a working result?
Answer 4 questions — we'll show the right system and a similar case ↓
The same routine-heavy process — four different endings six months later. No sales pitch, just the experience of 21 shipped systems:
'We'll get back to this next quarter.' Meanwhile the routine grows with volume, requests get lost, and you have to expand headcount. AI won't get simpler if you wait — while competitors are already running unit economics on it.
routine keeps growingA junior dev, n8n and GPT will assemble a demo in a week — an honest way to test an idea. But production that doesn't fall over, plays well with your CRM and ERP, and survives the enthusiast leaving is a different job. That's how pilots end up on the shelf.
a demo, not productionMonths on specs and approvals, revisions billed separately, AI bolted on for show — if at all. The result: yesterday's system and dependence on someone else's team.
slow and expensiveFixed scope and a measurable goal before the start, a working turnkey system, data in your infrastructure. We transfer ownership: code, access, documentation, team training. That's how we shipped 21 systems — from AI agents to AI-CRM.
turnkey Discuss Your ProjectWe're practitioners, not middlemen: our own enterprise AI platform runs in production — 6000+ users, 800+ paying. Our portfolio includes 21 shipped systems and Enterprise clients in energy, retail and banking. We sell what we've already built and use ourselves.
The same people you talk to. We're not a middle-layer agency with subcontractors: the studio is led by Zhemal Khamidun — Head of AI at an EdTech group, CPO of an enterprise AI platform — and the work is done by his team on their own production stack. No reselling of other people's hands: whoever designs your system at the audit is the one who ships it to production.
A demo can be assembled that way in a week, and it's a fine way to test an idea. Production that doesn't fall over, is integrated with your CRM and ERP, and keeps running after the enthusiast quits is a different job. That's exactly what we deliver: with deployment, integrations, tests and support.
We start with a pilot: fixed timeline, measurable result, milestone-based payment. We bring the system to working condition, implement it and train your team — so it delivers results instead of ending up on the shelf like 40% of AI pilots on the market.
We work inside your infrastructure: private deployment, on-premise, compliance with local data-protection law. Data never leaves your perimeter, and we sign an NDA. For corporate clients, we align the architecture with your security team.
No. We transfer the code, access and documentation to your ownership — the system is yours. SLA-backed support is an option, not an obligation: you can evolve the system yourself or with any other team.
We don't ask you to take our word for it — we do the math. Before the start, on a free audit, we pin down the economics: how many hours of routine the system will remove, what that means in money, and when the project breaks even. If the numbers say AI doesn't pay off for you yet, we'll say so honestly at the audit — not after implementation. Payment is milestone-based: you pay for each stage's result, not for a promise.
It depends on the task: a turnkey project, a fast MVP sprint or ongoing support. We name the price and timeline before the start — after a free process audit; payment is milestone-based. Cost is discussed individually.
It depends on the scope — which is exactly why we fix the timeline before the start, at the brief stage, together with the acceptance criteria. You get your hands on the first working prototype long before final delivery: the project moves in stages, and at each one you hold a concrete result, not 'research is underway'. We'll give the exact schedule for your task after a free audit.
No. Launch is a stage, not the finale: we hand over the code, access and documentation, train your team, and then provide SLA-backed support: monitoring, model fine-tuning, system development and guaranteed response times. And support is your option, not a leash: the system is your property, and you can run it yourself at any moment.
That's the number one reason AI projects end up on the shelf, which is why adoption is part of our project — not 'handed over and gone'. We build the system around your real process rather than forcing the process to fit the system, and we train the people who will work with it. Corporate AI training is the studio's home turf: Zhemal teaches at a leading technical university and has trained teams at Enterprise companies.
With a free process audit. You leave a request — we walk through your process on Zoom, show what can be automated and where AI will pay off, and hand you a short roadmap. It stays with you even if we never end up working together. No obligations — it's an honest way to test us in action before any contract.
A fair question — 40% of AI pilots on the market never reach production. We build the process so yours does: here are four guarantees baked into every project.
We start with a pilot: a fixed timeline and a measurable result, locked in before work begins. Payment is milestone-based — you pay for completed stages. Bringing the system to working condition is part of the contract, not a promise.
We deploy in your infrastructure: private cloud or on-premise, in line with local data-protection law. Data never leaves your perimeter, and we sign an NDA before the first call about your processes.
Systems 'end up on the shelf' when no one is there to use them. So we don't just hand over code — we embed it into your processes and train your people. Corporate AI training is Zhemal's core competence: Head of AI at an EdTech group, lecturer at a leading technical university.
The system is your property: we hand over the code, access and documentation. SLA-backed support is optional. Want to evolve it yourself or with another team — nothing holds you back.
Still have doubts? Let's talk them through on a free consultation, before any contracts.
30 minutes on Zoom: we'll break down your process, show similar cases from 21 shipped systems and honestly tell you where AI will pay off. No obligations.
P.S. This website — with all its waves, particles and animations — was built by our studio, without a front-end developer, over a few evenings. We'll build your system the same way.