One team that designs, engineers, and wires AI directly into your product. No agency layers. No three-vendor coordination. A clean brief on Monday becomes a live URL before the month is out.
// Three things, done well
You describe the outcome — we handle the stack decisions, the integrations, and the launch. Same studio, three directions. AI is the flagship; sites are a first-class direction next to it.
Designed in Figma, built on Next.js.
Landing pages, marketing sites, client portals, admin dashboards. Custom design, no templates. Lighthouse 95+ on mobile. CMS optional — Sanity or Payload when content scales.
Plug AI into your CRM, docs, or data.
RAG search, agents, and automations that connect to systems your team already uses. Self-hostable on your VPS where data must stay private; hosted APIs where speed wins. Auditable prompts and logs throughout.
New site shipped with AI already inside.
Your new site, delivered with AI wired in from the first wireframe — chat that knows your product, copy that updates from your data, dashboards that explain themselves. One contract, no three-vendor coordination.
// The uncomfortable truth about AI in business
of corporate AI projects fail to deliver real value.
Not because the models aren’t good enough — they are. The failures are architectural, and they repeat across companies.
Teams pick an LLM or API model before understanding their data or what the system needs to do. The model ends up fighting the workflow instead of fitting it.
One model handles everything — legal questions, internal data, general requests. Without routing, output quality is unpredictable. Complex queries fall apart.
RAG gets set up over a weekend with default settings and unstructured docs thrown in. Then the team wonders why it hallucinates. The pipeline was never designed for real queries.
// The model is not the product
Four architectural decisions, made on day one and maintained every week. Skip any of them and the deployment behaves like the 90% — looks fine on launch, flat by quarter two.
One model can’t handle everything well. A hybrid router classifies each request and sends it to the right model or agent. Most vendors skip this step entirely — which is exactly why their deployments underperform.
Retrieval quality depends on how documents are chunked, embedded, and indexed. Dumping files into a generic RAG setup and hoping for the best doesn’t work at enterprise scale. We build multi-level pipelines tuned to your content.
An agent that can’t touch real systems isn’t useful. We connect agents to databases, internal APIs, and business tools — and design the full flow: error handling, retries, human approval where it’s needed.
We pick the model last, once the architecture is clear. If the task needs a fine-tuned model, we do it on open-source weights using your own data. No vendor lock-in, no data sent to third parties.
// Three core services
90% of corporate AI projects fail to deliver real value — because teams pick a model first, skip routing, and treat data prep as an afterthought. We do the opposite. Three services, end-to-end.
Scroll slowly — each service pins on top of the previous as you go.
Automate the work, not just the prompt.
We start with the workflow, not the model. Map where time leaks, estimate ROI before any code is written, then build agents that connect to systems your team already uses — and ship with metrics that prove it worked.
Retrieval that actually retrieves.
Most RAG setups are a weekend job — dump documents into a vector store and hope. We design retrieval as a real system: two-level search, content-tuned chunking, and multi-agent flows wired into your databases and internal APIs.
A ChatGPT for your company. On your servers.
Open-source LLMs adapted to your domain, served from infrastructure you control. Familiar chat UX, hybrid routing under the hood, nothing leaving your network. Built for teams that can’t send data to third parties.
// Why teams pick us
We bake AI in, not bolt it on.
Most agencies treat AI as a plugin after launch. We design the system assuming AI is part of it — which changes the architecture, the data model, and the UX from the first sketch.
Same people from brief to launch.
Design, engineering, and AI work live in the same room — sometimes the same head. No account-manager layer. No hand-off gaps where things go missing.
EU-based, GDPR-ready, multilingual.
Based in Cyprus. We invoice from the EU, we host in the EU when you need it, and we deliver in English, Ukrainian, and Russian — with the same quality bar in each.
// Selected work
Same machinery, applied where it counts. Pipelines that automate, agents that act, on-prem LLMs that respect your security policy. The capabilities above didn’t come from a slide deck — they came from shipping these.
Editing a 40-min episode took 2+ hours of manual sync, cut, and assembly. The team spent more time editing than shooting.
A Python tool detects tracks, aligns them by waveform fingerprint, assembles the cut, exports. Editor reviews — no frame-by-frame work.
87% time reduction per episode
Two accountants spent most of their day entering invoices and receipts into 1C by hand — routine, error-prone, and expensive.
An agent reads incoming docs, classifies them, pushes data into 1C via HTTP API. Each entry surfaces a summary; the accountant confirms.
Replaced two full-time roles · human-in-the-loop preserved
The company wanted ChatGPT-like tools for the team — but sending internal docs to OpenAI or Anthropic was off the table.
Full AI chat platform on the company’s own servers: open-source LLM, hybrid router, RAG over their internal knowledge base.
No data leaves the network · security signed off day one
A founder wanted an assistant that knew their business — calendar, inbox, projects, decisions — so they could think instead of operate.
A voice-driven assistant integrated into their tools, with persistent memory across sessions and bounded authority to draft and schedule.
A day of busywork compresses into half
A sales team drowning in manual data entry and weekly reports. Pipeline updates were inconsistent; deals slipped because nobody flagged risk early.
We built a custom CRM with an AI assistant that fills lead data, drafts follow-ups, and watches the pipeline. An analytics agent generates weekly reports and surfaces deals at risk.
Weekly reports generated automatically · risk flagged early
Across 30+ projects: brands needed sites that load instantly, rank organically, scale across languages, and have AI built in — not bolted on.
A standardized AI-native architecture applied per-project: custom design, Next.js engineering rigor, AI chat & search wired in by launch, multi-language ready from day one.
Lighthouse 95+ avg · multi-language ready · AI inside by launch
Editing a 40-min episode took 2+ hours of manual sync, cut, and assembly. The team spent more time editing than shooting.
A Python tool detects tracks, aligns them by waveform fingerprint, assembles the cut, exports. Editor reviews — no frame-by-frame work.
87% time reduction per episode
Two accountants spent most of their day entering invoices and receipts into 1C by hand — routine, error-prone, and expensive.
An agent reads incoming docs, classifies them, pushes data into 1C via HTTP API. Each entry surfaces a summary; the accountant confirms.
Replaced two full-time roles · human-in-the-loop preserved
The company wanted ChatGPT-like tools for the team — but sending internal docs to OpenAI or Anthropic was off the table.
Full AI chat platform on the company’s own servers: open-source LLM, hybrid router, RAG over their internal knowledge base.
No data leaves the network · security signed off day one
A founder wanted an assistant that knew their business — calendar, inbox, projects, decisions — so they could think instead of operate.
A voice-driven assistant integrated into their tools, with persistent memory across sessions and bounded authority to draft and schedule.
A day of busywork compresses into half
A sales team drowning in manual data entry and weekly reports. Pipeline updates were inconsistent; deals slipped because nobody flagged risk early.
We built a custom CRM with an AI assistant that fills lead data, drafts follow-ups, and watches the pipeline. An analytics agent generates weekly reports and surfaces deals at risk.
Weekly reports generated automatically · risk flagged early
Across 30+ projects: brands needed sites that load instantly, rank organically, scale across languages, and have AI built in — not bolted on.
A standardized AI-native architecture applied per-project: custom design, Next.js engineering rigor, AI chat & search wired in by launch, multi-language ready from day one.
Lighthouse 95+ avg · multi-language ready · AI inside by launch
Hover to pause
// Ready to build?
// How we work
A working call, a short brief, and an honest scope. You leave with a price, a date, and a written plan — not a deck.
Wireframes, then high-fidelity Figma. Reviewed in rounds you control. Nothing touches code until you sign it off.
Weekly staging drops. You click around, break things, tell us what to fix. No surprises at the end because there is no end — only the last week.
We deploy to your infra or ours, walk your team through the code, and stay on a retainer if you want one. The repository is yours from day one.
// FAQ
If something’s not here, ask. We’ll reply with the same honesty.
A landing page ships in about two weeks. A multi-page marketing site is three to five. A web app with auth and a database starts at six. AI integrations into an existing product usually run two to four weeks.
Fixed price where the scope is clear — most websites and most AI integrations qualify. Time-and-materials where the scope is still evolving, with a weekly cap so you’re never surprised.
Because an AI agent that writes to your CRM is a different job from a static five-page site, even if both land on “AI integration.” A 15-minute call gets you a real number instead of a fake one.
Wherever you need. Hosted APIs (OpenAI, Anthropic) when latency and quality matter most; self-hosted open-source models on your VPS when data stays on your soil. We document the trade-off and help you pick — no lock-in either direction.
Yes. Roughly half of what we do is bolted onto something that already exists — a site you don’t want to rebuild, a CRM that needs smarter workflows, a dashboard that needs a chat that actually understands it.
The code is yours. We can keep an ongoing retainer for changes and support, or hand everything over with docs and a walkthrough. No lock-in either way.
English, Ukrainian, and Russian — same quality bar across all three. We can coordinate other languages with vetted translators when needed.
// Start a project
Tell us the shape of it. We come back in a business day with questions, a plan, and a real number — not a brochure.