(- Маркетинг на 100 -)

Digital-агенство полного цикла

Маркетинг, который

работает на результат

Разрабатываем сайты, продвигаем их в поисковых системах и запускаем рекламу. Объединяем аналитику, стратегию и digital-инструменты, чтобы привлекать клиентов и увеличивать продажи.

EXPLORE OUR APPROACH█

Обсудить проект

Смотреть кейсы

1 минута

Seo-продвижение
Geo-продвижение
Разработка сайтов
Контекстная реклама
Аналитика
Управление репутацией

40+ клиентов

4.9/5

1.5к отзывов о нас

Обсудить задачу

с нашей командой

+7 (000) 000-00-00

Отсканируйте QR-код,

чтобы обсудить проект

(Как мы работаем)

Наш подход к Digital

Маркетинг работает, когда все инструменты связаны. Мы объединяем стратегию, разработку, SEO, рекламу и аналитику в единую систему роста.

Процесс работы выстроен на собственных инструментах и сервисе отчётности. Мы последовательно погружаемся в проект, формируем стратегию, запускаем решения, анализируем результаты и корректируем продвижение на основе реальных данных. Клиент в любой момент видит ход работ, динамику показателей и достигнутые результаты.

Денис Кривов

Основатель Digital-агентства «Маркетинг на 100»

DESIGN • BUILD • DEPLOY • DESIGN • BUILD • DEPLOY •

1

2

3

4 /4

(WDX® — 03)

OUR SERVICES

AI Systems Services

Four core capabilities used to design, deploy, and scale AI systems inside real operational environments.

START A PROJECT

001.

AI WORKFLOW AUDIT

AI Workflow Analysis

We examine how work flows through your systems — from data inputs to operational decisions — revealing where AI can automate, assist, and improve reliability across the organization.

WHAT WE ANALYZE

001.

Core operational workflows and system handoffs

002.

Data sources, ownership, and reliability

003.

Manual decision points and exception handling

004.

Existing systems, integrations, and constraints

Output: Operational AI roadmap with identified automation opportunities█

002.

AI AUTOMATION SYSTEMS

AI Process Automation

We design and deploy AI-powered automation systems that execute repetitive workflows, reduce manual operations, and improve process reliability at scale across teams.

WHAT WE ANALYZE

001.

AI agents for operational workflows

002.

Automated data processing and enrichment

003.

AI-assisted task execution and routing

004.

Integrations with existing internal systems

Output: AI-driven workflow automation integrated across operational processes and internal systems█

003.

CUSTOM AI SYSTEMS

Custom AI Systems

We design and build custom AI systems tailored to your operations — from internal AI tools to decision-support platforms used by teams daily across the organization.

WHAT WE ANALYZE

001.

Internal AI copilots for teams

002.

Custom AI tools and interfaces

003.

AI-powered knowledge and search systems

004.

Decision-support and analytics platforms

Output: AI systems integrated with internal tools, and operational infrastructure.█

004.

AI SYSTEMS OPERATIONS

AI Systems Reliability

We support and improve AI systems after deployment — monitoring performance, refining models, and adapting automation as workflows and business needs evolve.

WHAT WE ANALYZE

001.

AI system monitoring and reliability

002.

Model performance evaluation

003.

Operational feedback and improvements

004.

Continuous system optimization

Output: Continuous monitoring of AI systems across production workflows.█

(qtf® — 04)

SELECTED CASES

Case studies

Whether you’re just exploring possibilities
or looking to scale existing tools.

2025

NorthGrid Logistics

We redesigned the company’s freight planning workflows and deployed AI systems that automatically coordinate routes, capacity, delivery schedules, and operational priorities.

Industry

Logistics & Supply Chain

SERVICE USED

AI Workflow Analysis, AI Workflow Automation

Challenge

Freight planning relied on spreadsheets and manual coordination

Technology Stacks

Cogni

Logix

MindX

Pulse

Synth

NovaA

DELIVERABLE: AI freight planning system integrated with routing and scheduling workflows.█

Instead of adding more software, they redesigned our workflows. Automation now handles work that once required entire teams.

Daniella Mercer

Director of Logistics

42 %

Faster tasks planning

13000 +

decisions automated monthly

13 X

Route planning speed

(qtf® — 05)

More cases

VIEW ALL CASES

Orbitra Systems

2026

CinderBay Retail Group

2025

VectorLane Mobility Network

2025

LumenArc Energy

2026

HelioDesk Platforms

2026

IronPeak Industrial Manufacturing

2026

Northbridge Education

2026

We implemented AI systems to personalize learning workflows, automate administrative tasks, and improve execution across educational platforms and internal operations.

Play

Inside Quantum Flux

1:42 min overview

ACTIVITY

Operational
Decisions

1200

Automated decisions

across deployed AI systems

+15%

jun.

+35%

jul.

+53%

aug.

Predictability
over heroics.

Systems beat intuition — every time.

Orbitra Systems

LumenArc Energy

HelioDesk Platforms

HelioDesk

Platforms

HelioDesk

Platforms

HelioDesk

Platforms

40+ teams

Be the next success story

Benchmark

System
Recovery

Faster operational recovery

after AI decision automation

No hype. Just systems
Clarity beats automation
Decisions over demos
Designed for messy reality
Systems that hold under pressure

ANALYZE • BUILD • OPERATE •ANALYZE • BUILD • OPERATE •

1

2

3

4 /4

(QTF® — 06)

Process

Execution Flow

A structured process used to design, deploy, and scale AI systems across real operational environments.

START WITH QUANTUM FLUX

001.

Audit

System Audit & Discovery

We analyze how the system actually operates across workflows, data, and decision points. This step identifies constraints and opportunities before any AI or automation is introduced.

WHAT WE ANALYZE

001.

Core operational workflows and handoffs

002.

Data sources, ownership, and consistency

003.

Manual decision points and exceptions

004.

Existing tools, integrations, and constraints

Technology Stacks

Cogni

Pulse

Synth

MindX

002.

AUTOMATION

Automation Design & Agents

We design intelligent automation systems and AI agents tailored to your operational workflows. This step translates audit insights into executable automation architecture and controlled agent behavior.

WHAT WE ANALYZE

001.

Automation-ready workflows and task clusters

002.

Decision trees, escalation paths, and guardrails

003.

System APIs and integration surface

004.

Human-in-the-loop control mechanisms

Technology Stacks

Kortx

Strat

NovaA

Cogni

003.

ARCHITECTURE

AI Strategy & Technical Architecture

We define the long-term AI direction aligned with business priorities. This step ensures that every AI initiative fits within a scalable, secure, and economically viable architecture.

WHAT WE ANALYZE

001.

Strategic objectives and ROI potential

002.

Data infrastructure maturity

003.

Build vs. buy vs. hybrid scenarios

004.

Governance, compliance, and risk models

Technology Stacks

Cogni

Nexis

Atica

GridX

004.

INFRASTRUCTURE

Data Infrastructure & Foundations

We build the structured data layer required for reliable AI systems. This step transforms fragmented data into consistent, model-ready infrastructure.

WHAT WE ANALYZE

001.

Data sources and ingestion pipelines

002.

Data quality, gaps, and normalization

003.

Storage architecture and retrieval performance

004.

Security, privacy, and access control

Technology Stacks

Logix

Axiom

Lumen

Pulse

What We Deliver
(®)

(qtf® — 07)

SYSTEM OUTPUT

We design and build AI systems that operate
inside real workflows — from idea to production.

Operational AI Expertise

We specialize in AI systems designed for real operational environments — not experiments or isolated prototypes.

Quantum

Flux

Systems That Actually Ship

Our work focuses on production-ready AI tools that integrate with existing infrastructure and workflows.

Deep Technical Ownership

From architecture to deployment, our team builds and operates the systems we design.

Real Business Impact

Every system is built to improve measurable outcomes — operational speed, reliability, and decision quality.

Clear Collaboration

Transparent communication, defined milestones, and full visibility across every stage of the project.

(qtf® — 08)

OUR JOURNEY

Engineering systems that turn

complex work into automation

From early automation tools to building
production AI systems used by growing companies.

2018 — 2019

Small Team Beginnings

We started as a small engineering team focused on automation and internal tools.

2019 — 2021

First AI Projects

Early client projects focused on AI-powered workflow automation.

2021 — 2023

Systems Expansion

Our work expanded into full AI systems and operational infrastructure.

2023 — Present

Operational AI Studio

Today we design production AI systems used across multiple industries.

Helping teams transform

repetitive work into AI systems

From early exploration to deploying AI systems that support real operational workflows.

START WITH QUANTUM FLUX

No hype. Just systems
Clarity beats automation
Decisions over demos
Designed for messy reality
Systems that hold under pressure

(WDX® — 09)

Our team

The Studio

A focused team of engineers and researchers building production-grade AI systems.

JOIN OUR TEAM

SYSTEM BUILDERS •SYSTEM BUILDERS •

1

2

3

4

5 /5

AI Engineers

A small team of engineers and researchers building production-grade AI systems for real-world operations.

Aisha Coleman

Builds AI architectures that remain reliable in real-world systems.

001.

DEPLOYS AI SYSTEMS INTO LIVE BUSINESS WORKFLOWS

002.

DESIGNS ARCHITECTURES FOR RELIABLE DECISION AUTOMATION

003.

INTEGRATES MODELS WITH REAL DATA AND OPERATIONS

Social accounts —

(qtf® — 10)

ENGAGEMENT MODELS

Access plans

Flexible engagement models for teams
exploring or scaling AI systems.

Quantum brought structure and clarity to our AI roadmap and helped us deploy systems that actually work in production.

David Ramirez

Director of AI Platforms

VIEW ALL CASES

Discovery & Strategy

We analyze your systems, workflows, and data landscape to identify high-impact AI opportunities and define the technical direction.

from

$7000

5000

/project

Timeframe:

Typically delivered in 2–3 weeks

What’s included:

Analysis of existing processes and manual operations across key teams

Identification of high-impact AI and automation opportunities

Identifying high-impact AI opportunities across operations, workflows, and data processes where automation can deliver measurable value.

Review of data structure and integration readiness

Definition of AI system architecture and technical direction

Design of data pipelines and model infrastructure

SELECT ENGAGEMENT MODEL

System Design

Designing the architecture, data pipelines, and technical foundation required to deploy AI systems in production.

from

$9000

7000

/project

Timeframe:

Typically delivered in 3–5 weeks

What’s included:

Analysis of existing processes and manual operations across key teams

Identification of high-impact AI and automation opportunities

Identifying high-impact AI opportunities across operations, workflows, and data processes where automation can deliver measurable value.

Review of data structure and integration readiness

Definition of AI system architecture and technical direction

Defining system architecture, model strategy, and integration approach required to deploy reliable AI solutions in production.

Design of data pipelines and model infrastructure

SELECT ENGAGEMENT MODEL

Deployment & Integration

Building, integrating, and deploying AI systems directly into your existing tools, workflows, and operations.

from

$15000

12000

/project

Timeframe:

Typically delivered in 4–8 weeks

What’s included:

Analysis of existing processes and manual operations across key teams

Identification of high-impact AI and automation opportunities

Identifying high-impact AI opportunities across operations, workflows, and data processes where automation can deliver measurable value.

Review of data structure and integration readiness

Definition of AI system architecture and technical direction

Defining system architecture, model strategy, and integration approach required to deploy reliable AI solutions in production.

Design of data pipelines and model infrastructure

SELECT ENGAGEMENT MODEL

Controlled Architecture

(qtf® — 11)

Insights & Research

Recent articles

Notes on AI systems, architecture decisions,
and lessons from real deployments.

VIEW ALL INGHTS

Data Analysis

Feb 11, 2026

in /

Data Analysis

The gap between AI experiments and production-ready systems explained

(qtf® — 12)

Our newsletters

Stay in the loop

No hype. Just systems
Clarity beats automation
Decisions over demos
Designed for messy reality
Systems that hold under pressure

SUPPORT • INFORMATION •SUPPORT • INFORMATION •

(qtf® — 13)

frequently asked questions

Questions
that matters

A clear set of answers about how we design, build,
and deploy AI systems in real environments.

CONTACT SUPPORT

001.

Is this just a wrapper for ChatGPT?

Absolutely not. While we leverage powerful models like GPT-4o or Claude, the real value lies in our custom architecture. We build specialized RAG (Retrieval-Augmented Generation) systems that sync with your private data silos, ensuring the AI operates within your business context, not just general knowledge.

002.

How long does it take to see a return on investment (ROI)?

Most companies begin to see measurable impact within the first few months. By automating repetitive workflows or improving decision speed, AI systems often reduce operational costs and unlock new capacity across teams.

003.

Can we integrate these AI agents with our existing software stack?

Yes. Our systems are designed to integrate with existing tools through APIs, databases, and internal services. We adapt the architecture to your stack so AI works within your current workflows, not outside them.

004.

How do you ensure our sensitive data stays secure?

Security is built into the architecture from the start. We use controlled access layers, encrypted storage, and isolated processing environments to ensure your data remains protected and fully under your control.

005.

Will AI hallucinations affect the quality of our output?

We reduce hallucinations through system design, not just model choice. Retrieval systems, validation layers, and controlled prompts ensure outputs are grounded in your real data and business context.

(qtf® — 14)

OUR CONTACT

Let's talk

Bring your system, your workflow, or your idea.

We’ll help you understand what it takes to build and deploy it.

+7 (000) 000-00-00

info@marketing-na100.ru

Россия — работаем по всей стране

Working globally —

Remote first

Social accounts —

Send message

Book a Call

Get a job

No hype. Just systems
Clarity beats automation
Decisions over demos
Designed for messy reality
Systems that hold under pressure

PRINCIPLES • VALUES •PRINCIPLES • VALUES •

(qtf® — 15)

OUR PRINCIPLES

What
We Believe

We design AI systems that improve real work —
not just demonstrate technology.

Обсудить проект

We believe technology should solve real problems, not create new ones. If it doesn’t make the work simpler, faster, or clearer — it doesn’t belong.

Our job is not to automate everything. It’s to design systems that remain understandable, explainable, and controllable — even when things go wrong.

Маркетинг, который

работает на результат

1

2

3

4

/4

AI Systems Services

AI Workflow Analysis

AI Process Automation

Custom AI Systems

AI Systems Reliability

Case studies

NorthGrid Logistics

1

2

3

4

/4

Execution Flow

System Audit & Discovery

Automation Design & Agents

AI Strategy & Technical Architecture

Data Infrastructure & Foundations

Engineering systems that turn

complex work into automation

Helping teams transform

repetitive work into AI systems

1

2

3

4

5

/5

AI Engineers

Access plans

Controlled Architecture

Recent articles

AI technology

System Integrations

Automation Features

Automation Tools

Data Insights

Data Insights

Data Analysis

AI technology

System Integrations

Automation Tools

Data Analysis

AI technology

System Integrations

Automation Features

Data Analysis

Questionsthat matters

001.

002.

003.

004.

005.

Let's talk

Email

No hype. Just systems

Clarity beats automation

Decisions over demos

Designed for messy reality

Systems that hold under pressure

What We Believe

Questions
that matters

What
We Believe