Monarch Web Studio

An AI Agents Team tailored to your project

We design and launch teams of AI agents: architect, frontend, backend, tester, reviewer — working in parallel on your project.

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One agent - one ceiling

The context window overflows, quality drops, the frontend waits for the backend. Multi-agent orchestration removes these limitations: several specialized agents work in parallel, each in their own area of responsibility, in an isolated Git worktree.

How the team is structured

We design the roles and interaction patterns to fit your stack and processes. The lead agent decomposes tasks and distributes them among specialists — code reaches main only after automatic review, linting and tests.

  • CEO/Lead agent — decomposes tasks from the backlog, distributes them among specialists, and oversees quality gates
  • Specialized agents — architect, frontend, backend, tester, reviewer, documenter
  • Git worktree isolation — each agent in its own branch, no conflicts during parallel work
  • Custom Skills for each role - the agents know the stack, conventions and specifics of your project
  • Quality gates before merging - automated review, linting, tests on every PR
  • Monitoring dashboard — progress, agent logs, performance metrics, task status

What this gives in practice

Tasks that took a single developer a week are closed in hours through the parallel work of 5-8 agents. Need more capacity — we add agents without hiring, onboarding, or losing context. The developer becomes a manager of an agent team: assigns tasks, reviews results, makes architectural decisions.

Client pain points

Familiar problems?

We understand the challenges our clients face and know how to solve them

One agent cannot handle complex tasks

The context window overflows, quality drops. The agent loses focus at 80% of context usage.

Development proceeds sequentially

The frontend waits for the backend, the tests wait for the code. There's no parallelism, the deadlines stretch out.

Hard to scale the team

Hiring, onboarding, and getting in sync take months. But the tasks need to be handled right now.

No systematic approach to AI development

Everyone uses AI in their own way. There's no single pipeline, no standards, and no quality control.

Service scope

What's included

We design the roles, areas of responsibility and interaction patterns of the agents to fit your project and stack.

Each agent is an expert: architect, frontend, backend, tester, reviewer, documenter.

The lead agent decomposes tasks, distributes them among specialists, and oversees quality and merging.

Each agent works in its own worktree. No file conflicts, parallel work without risks.

Code goes through automatic review, linting and tests before reaching the main branch.

A dashboard with progress, agent logs, performance metrics, and task status.

Our advantages

Why clients choose us

We build long-term partnerships and create products that deliver results

Parallel development

5–8 agents work simultaneously. Frontend, backend and tests in parallel, not in a queue.

Speed = agents

Tasks that took a single developer a week are closed in hours through parallel work.

Isolation without conflicts

Each agent in its own Git worktree. No conflicts on merge, a clean commit history.

Built-in quality control

Automatic review, linting and tests at every stage. Code reaches main only after it's been verified.

Process transparency

The dashboard shows which agents are doing what, how many tasks are closed, and where the bottleneck is.

Scales instantly

Need more power - we add agents. Without hiring, without onboarding, without losing context.

How we work

Work stages

Clear process, predictable result. No surprises at the finish line

01

Project analysis

We study the codebase, architecture, development processes, and current bottlenecks.

02

Team design

We define agent roles, interaction patterns, quality gates and the coordination system.

03

Agent development

We create configurations, Skills, system prompts and tools for each agent.

04

Pilot launch

We run the team on real tasks from the backlog. We measure speed, quality, and stability.

05

Optimization and scaling

We refine based on pilot results, set up CI/CD, and configure monitoring and alerts.

Want to discuss your project? Leave a request — we respond within an hour

Portfolio

Our projects

Real results for real businesses

n8n-flow

Optimization of n8n for a medical AI bot

Diagnostics and optimization of an n8n workflow for a medical chatbot that works with a vector knowledge base. The bot advises patients using up-to-date medical information.

Details
n8n-chat-app

AI bot for booking a doctor's appointment

We added an automatic patient appointment-booking feature to a medical organization's existing AI bot. The bot itself selects a time, checks availability, and books the appointment.

Details
All projects
Pricing

Packages and pricing

Choose the right package or request a custom solution

Pilot

from 80,000 ₽

What's included

  • A team of 3 agents
  • 1 project / repository
  • Basic orchestration
  • Setup and launch
Recommended

Team

from 150,000 ₽

What's included

  • Up to 8 specialized agents
  • Lead agent with decomposition
  • Quality gates and CI/CD integration
  • Custom Skills for each role
  • 2 months of support

Pipeline

from 250,000 ₽

What's included

  • Unlimited agents
  • Multi-repository orchestration
  • Monitoring dashboard
  • Self-learning from the project's history
  • Integration with Jira/Linear/GitHub
  • 6 months of support

Didn't find the right package? Let's discuss a custom project

Discuss a project
Reviews

What clients say

Honest reviews from those who have already worked with us

We needed a store that works equally well in Estonian and Russian — not just translated buttons, but a full-fledged experience in both languages, including product cards and SEO. On top of that, we have a catalog of several thousand items and our own CRM, with which everything has to work in sync. Vitali from Monarch Web got to grips with the specifics, built a proper multilingual architecture, and connected our CRM so that stock levels and prices update themselves. Filtering works fast even with the full catalog.

A

Alexey

Founder

We struggled with Senler for a long time — for simple newsletters it's fine, but we needed proper segmentation and personalization, not just "send everyone the same thing." We couldn't solve it on our own. The guys suggested linking Senler with N8N and adding AI for responses. Honestly, at first it sounded complicated. But in the end we got a bot that sorts subscribers into segments on its own, triggers the right sequences, and replies to people like a human rather than with templates. Conversion on the newsletters rose noticeably, and there's far less manual work.

D

Dmitry

Manager

Artyom Ledovskikh Founder, the «VraChat» platform «I saw how clinics lose patients simply because no one picks up the phone at lunchtime or after six. The idea was to build a SaaS that any clinic on MedFlex connects in a couple of days and immediately gets an AI assistant with real appointment booking, rather than yet another chatbot with «ask an operator a question» buttons. I came to Monarch with the concept, and the guys didn't just write a botthey designed the product architecture: multi-tenancy, semantic search across each clinic's knowledge base, a unified pipeline on N8N. Now we're connecting clinics one after another with no custom rework. Essentially, they built me a ready-made SaaS engine on which I'm building a business.

D

Dmitry

CEO

FAQ

Frequently asked questions

Answers to the most commonly asked questions

Contact

Ready to start a project?

Leave a request and we will get back to you within 1 business hour. First consultation is free.

info@monarchweb.ee
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