AI agent development
& AI-native software
AI has changed the rules — we build by the new ones.
Production systems 2–3× faster than classical development. Team's engineering experience — since 2012, AI-native approach — since 2023.
10+ лет в IT50+ проектовSenior-командаPrivate-firstNDA по умолчанию
About us
We are DevNeuroX. We build systems where mistakes are not an option.
The team's engineering experience goes back to 2012, with more than 50 completed projects across industries. From document workflow for government structures and ecological monitoring systems with hardware components — to VR simulators for Oculus and SaaS platforms for startups. Two worlds — government and startups. Our engineers have worked in both for over 13 years.
DevNeuroX is the studio where we combined the team's accumulated experience with the AI-native approach. AI tools are plugged into a working engineering team, not the other way around — we are not «a new AI startup without a background». That's why we deliver not «weekend prototypes», but production systems — the same as 10 years ago, just 2–3× faster and 2–3× cheaper.
Today we have two products — custom AI-native development and a line of AI agents for business. The next chapters are about them.
Year — team's practice started
Years of team's engineering experience
Completed projects
Two products — one engineering expertise.
We don't «do everything». There are two directions where we have deep expertise and a polished process. Both are built on the AI-native approach: a senior team plus AI infrastructure.
01 · Custom development
AI-native development
Custom products for a business task: MVP in 4–6 weeks, SaaS platforms, mobile apps, backend and integrations, legacy migrations. A senior team + AI = the quality of classical engineering plus speed that used to be impossible.
02 · Ready-made directions
AI agents for business
Not «a neural net in chat», but an employee for one process. 8 directions: from sales and support to tenders and engineering governance. Each agent — a polished contour: customer data connection, rules, testing, maintenance.
Customers often start with one direction, and within 6 months connect the second. For example: first develop a SaaS platform, then add a Support agent for clients and a Sales agent for the sales team. Or: first a Sales agent pilot in an existing product, then a full rebuild of the product in AI-native.
What we've built.
Clients are usually under NDA, so we show the industry, the task, and the measurable impact. Two public projects (Digital Padel, ecological monitoring) — to show the range: from a product VR startup to an industrial regulated system.
45+ more projects under NDA
Want cases from your industry — we'll send relevant ones.
Over 13+ years of the team's engineering practice — more than 50 projects across industries: fintech, retail, regional projects, e-commerce, industrial, sports. Most are under NDA, so we only publish what's been cleared. Tell us your industry and task — we'll send relevant cases and references from past clients.
Six principles — the same for development and for agents.
We've seen many times how a «technically correct» project failed because of a wrong work process. These six principles are what our team developed over 13+ years of engineering practice and apply equally to development and to agents.
Senior + AI, not «cheap juniors»
Acceleration comes not from «AI writes code», but a senior engineer with AI tools. Architecture, security, business logic — stay with the human. AI removes the routine: boilerplate, types, tests, documentation.
Transparency from week one
A clickable prototype appears in the first 7 days. Weekly engineering brief, real-time progress visibility, no «black box until acceptance». The customer steers the idea while it's cheap, not after the code is written.
Source code stays with you
All code, documentation, infrastructure — the customer's property. Open stack (PostgreSQL, Docker, standard languages) — no vendor lock-in. Can be evolved in-house or handed to another contractor without rewriting from scratch.
Competitive pricing
MVP — from 1.2M RUB (classical model — 3–5M). AI agent pilot — from 250K RUB. Full implementation — from 500K RUB. Not «cheap at any cost», but realistic for production-level. In the pilot we give an honest estimate for your task, not «a range from thin air».
Not vibe coding, not no-code
Vibe coding — for weekend prototypes. No-code (Tilda, Bubble) — for landing pages and simple forms. We do — production systems that the business runs on: with architecture, security, tests, documentation. Different categories, different risks.
AI maintenance agent included
When you order AI-native development, the Engineering Governance Agent is connected for free during the project: weekly brief, project memory, captured architectural decisions. After launch — standard maintenance from 40K RUB/month.
Four differences — from other AI studios on the market.
There are many AI studios now. Most share one problem: they appeared in 2024 with no engineering experience before AI. It becomes obvious on the first complex project. Here's what makes us different.
13+ years of engineering experience isn't «a new AI startup»
There are many AI startups in 2024-2025, and most have no engineering background. They know prompts but not system design for load, compliance, working with banking legacy. Our team came to AI-native from engineering, not from a startup: engineering practice since 2012. This matters when it's about production systems the business runs on.
Two worlds — government and startups
Most studios work in one of the two worlds. Our engineers — in both for over 13 years. That gives us judgment: where corporate discipline and audits are needed, and where startup speed and iterations are. When a customer comes with a task, we see which world it's closer to and pick the right tempo.
Not only web — we have hardware experience
We built the ecological monitoring system with hardware: sensors, gateways, data transmission, certification. The VR simulator Digital Padel — with a patent-pending Smart Racket Adapter. Not «a studio that only does websites». If a task requires going beyond the web stack — we do it.
AI-native is a behavior, not a service
We don't have a «dev department» and an «AI department». Every engineer on the team works with AI tools as part of daily work. It's not «let's plug AI into the project» — it's the base model for how every PR, every migration, every test is written. That's why the acceleration is systemic, not one-off.
Talk to an AI agent right here on the page.
On the right — a working Business Requirements Document AI agent, one of those we build to order. Not a recording or a simulation: a real production agent running on this very page.
How to use it
- 01Briefly describe the task or product you want to launch.
- 02The agent will ask follow-up questions — answer freely, like in a normal conversation.
- 03In the end it will assemble a structured brief — you can download it or pass it to the form.
- 04Based on the brief we'll come back with a realistic timeline and budget estimate.
Technical details
The agent is built on our production stack: streaming responses, session context memory, RAG over our knowledge base. Under the hood — a modern LLM wrapped in an engineering quality control layer. It's an example of what we deploy to clients as Personal or Business agents.
Agent is typing…
We don't just deploy — we teach people to use AI properly.
In 2–3 years AI tools will be the standard in engineering and business teams. Whoever starts learning now will gain a competitive advantage that latecomers won't have. That's why we have a separate direction: training client teams, so that AI tools and agents don't become «a toy for 3 months», but turn into part of the working process.
Corporate programs for adopting AI in development
For company engineering teams that want to switch to the AI-native approach. A 2–4 week program: review of the team's stack, selecting AI tools for the tasks, training on using them, ramp-up to regular production use. Not a «theoretical course», but a real shift in how the team works.
CTO, tech leads, developers · teams 5–50+
Client team onboarding for working with AI agents
Once we've deployed Sales, Personal, Support, RAG or another agent — we train your team to work with it well. How to adjust scenarios, write prompts for typical tasks, handle complex cases, give the agent feedback for improvement. Without this even a well-deployed agent gets «abandoned» in 3 months.
Client operational teams · typically after agent deployment
«Where to start with AI» mentor sessions for executives
Short individual sessions with CEOs, CTOs, business owners: which AI tools actually work, where to start in your company, how to link AI to business goals, how not to burn budget on «let's try something trendy». Sessions — 90 minutes, with a concrete roadmap as the output.
CEO, CTO, owners · 90-minute sessions
Open learning materials in the Telegram channel
A free column in our Telegram channel @dxaiblog. AI tool reviews, practices from real projects, mistakes and how to avoid them, reviews of new models and platforms. Anyone can subscribe — engineer, owner, product manager. This is the public part of our education, no commitment.
Anyone exploring AI · public channel · free
Training cost is discussed individually — depends on team size, format (online/hybrid/corporate visit), program depth, and whether you need a process built from scratch or accompaniment of an existing one.
If you want to start small — subscribe to the Telegram channel @dxaiblog. All materials there are free. That's our «step zero» of training.
Tell us the task — we'll say what's actually doable
We reply within 2 hours during business hours. In the pilot call we'll show where the agent pays off and where it shouldn't be tried.