We implement AI so a large company actually starts using it

In mid-size and large businesses, AI stalls not because of models. People fear that "we'll be fired," legal and accounting demand the impossible, and IT becomes the only change bottleneck. We first solve a real task, then show how it was solved, and teach management to handle such changes independently.

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3top barriers: fear, legal/accounting, IT bottleneck

1a live business process instead of an abstract course

×scalethe effect grows with the scale of the company

Resistance: "we'll be fired" legal / accounting / information security real process -> AI framework personal assistants at work

Adoption roadmap

The rocky path to AI in a large company

The journey starts with simple questions about payment, access, and rules, passes through resistance and control requirements, and ends with personal AI assistants in the daily work of managers and specialists.

KT.Team AI Workshops: AI adoption for mid-sized and large

Resistance first

Resistance is usually rational: people do not understand what will change in their role, and they protect themselves from the risk of "they will replace us."

Control later

Legal and accounting teams require guarantees that cannot be met with old procedures without a new control platform.

Then the platform

IT stops handling every small change manually and builds a safe environment for business process changes.

Scale in the end

One mastered workflow multiplies across hundreds of people, tasks, and repetitions, so the impact is especially large in a big company.

We do not start with an AI lecture: we take a real process and bring it to a working result.
We show how the solution works so company specialists can reproduce the approach themselves.
Management learns to solve individual work tasks through AI agents instead of waiting in IT's queue.
The user describes the desired result in plain language, and the platform responds with a safe change.

Our clients

FSK Group

SMLT

Tochno

Sber City

+10clients · View cases →

Catalog

Workshops as a set of practical missions

Each card is a practical path: we take a real process, build an AI setup, and teach the team to repeat it independently.

Mission 01

EnterpriseLegacyDORA

Accelerating development of large projects with AI

How to stop drowning in legacy and start delivering value faster.

3 modulesOnline / OfflineJune 10

Mission 02

DORATTUPlan-Driven AI

Accelerating the entire development cycle (Time-To-Use) with AI

From "AI as a chatbot" to "AI as an engineering accelerator" — integrating AI into the TTU methodology.

3 modulesOnline / Offlinedates matched to the task

Mission 03

OpenClawAgentsProductivity

A personal AI assistant with OpenClaw

From zero to a digital worker in 2 hours — self-hosted, multichannel, zero routine.

1 module · 2 hoursOnlinedates matched to the task

Mission 04

HermesPersonal assistantEnterprise

Hermes Agent: a personal AI assistant for executives

An assistant that lives in familiar channels, remembers context, runs routine tasks, and works with company tools under IT control.

2-3 modulesOnline / Offlinedates matched to the task

Mission 05

InfoSecSecOpsShift LeftDORA

AI SecOps: autonomous cybersecurity agents

How to speed up security checks 10x without losing quality — from manual audits to 24/7 agents.

3 modulesOnline / Offlinedates matched to the task

Mission 06

OpenClawClaude CodeSupportAutomation

AI technical support agent

A mix of OpenClaw and an AI IDE (Claude Code) that handles basic support tasks: from answering users to automatically configuring the product.

3 modulesOnline / OfflineJune 12

Mission 07

Claude CodeAgentsAI-IDEEffective development

Advanced Claude Code setup

Advanced Claude Code tools and approaches — highly effective AI-agentic development.

3 modulesOnline / Offlinedates matched to the task

Mission 08

SurfSenseLLM WikiDocumentationAutomation

AI-native documents and reporting for developers

LLM Wiki + SurfSense: a corporate knowledge base that assembles and updates itself automatically.

3 blocksSurfSense + LLM Wikidates matched to the task

Mission 09

Claude CodeCodexPCMTelegram

AI psychologist: insight into yourself, your team, and mentoring

We'll build a personal agent on Claude Code or Codex that helps analyze communications, chats and voice notes.

1 module · 2 hoursClaude Code or Codex + Telegramby invitation only

Mission 10

ClaudeTrainingExecutive leadership

AI coach: hands-on practice with Claude and AI tools

A regular coach treats working with Claude and AI tools as a skill, either for a team or one-on-one for a leader.

Regular formatOnline / Offlinedates matched to the task

First solve the task, then teach change management

The workshop does not start with theory. We analyze a new business process, assemble and test a working solution, and then run a workshop where the company’s specialists learn to repeat that path on their own.

01 · Process review

We look at how the work is set up today: roles, data, decisions, legal, accounting, and information security constraints, and real points of resistance.

02 · Build and validate

We build a working AI-agent setup and validate quality, security, cost, and suitability for daily use.

03 · Workshop and handoff

We show how the solution was built and teach specialists to manage process changes without constantly going through IT.

From "how do I pay?" to personal AI assistants

Basic access

The company is dealing with practical questions: how to pay, who may use it, what data cannot be shared, and where accountability is recorded.

Practical application

The team stops just "trying chat" and starts handling repeatable tasks: reports, reconciliations, tickets, documents, analytics, and procedures.

Personal assistants at work

Managers and specialists get personal agents that understand context, help with decisions, and prepare outputs within the workflow.

In a large company, even one mastered process delivers a major gain

× People · many users

When dozens or hundreds of employees adopt one scenario, the effect repeats every day and quickly outweighs the pilot cost.

× Process · many repetitions

AI is especially useful where there are recurring decisions, documents, reconciliations, communication, and exception handling.

↓ IT queue · fewer manual fixes

IT builds a safe platform for change, while users describe the needed result in plain language and get it faster.

Experts

Sergey Korshunov

Overcoming team resistance, a fast move to full-stack, and independent quality assessment of large projects based on Amazon and Google practices.

Alexander Stanovoy

Using AI (Codex and Opus), he onboarded onto a project that had grown for 5+ years without documentation and brought up the dev environment in hours instead of weeks.

Andrey Putin

Embedding AI into the engineering and product processes of enterprise teams, the Time-to-Use methodology.

Alexey Shvets

Automation of engineering processes and agentic development on real enterprise tasks.

Dmitry Krymsky

AI-driven architecture, static analysis of legacy and objective quality control.

Schedule

A separate list of upcoming workshops

The browser highlights the nearest date automatically. Past sessions fade out: recent ones stay visible, the oldest almost disappear.

01 June 10 Accelerating development of large projects Wednesday, 12:30 MSK RUB 20,000 / person
02 June 12 AI support agent Friday, 14:00 MSK RUB 20,000 / person
03 June 17 Accelerating development of large projects Wednesday, 12:30 MSK RUB 20,000 / person
04 June 19 AI support agent Friday, 14:00 MSK RUB 20,000 / person
05 June 24 Accelerating development of large projects Wednesday, 12:30 MSK RUB 20,000 / person
06 June 26 AI support agent Friday, 14:00 MSK RUB 20,000 / person

We do not sell an AI course. We change the company's ability to implement change.

For more than 13 years, we have delivered large enterprise projects and seen where adoption breaks down: not in the model, but in trust, control, processes, and accountability. That is why our workshops are built around results that can already be validated in real work.

Focus

A change in team behavior, not a set of lectures about prompts.

Method

Real process -> working solution -> workshop -> independent changes.

Foundation

DORA/SRE/QSM, weak coupling, a secure platform, and measurable Time-to-Use.

AI is not adopted by order. It is adopted through safe experience, when people see value in their own work.

RoleBeforeAfter

Business userWaits for IT to make updatesDefines the desired result and tests it in a safe environment

ManagerManually compiles reports and statusesKeeps a personal AI assistant for routine tasks

ITMakes every small change manuallyBuilds a platform for safe change and control

A fit

Mid-sized and large businesses with real processes and constraints
Teams with resistance to AI adoption
Management wants to solve personal work tasks through AI agents
IT is ready to build a platform for safe change, not a queue of tasks

Not a fit

Only a motivational lecture about the future of AI is needed
No readiness to provide a real process for analysis
The company is not ready to change roles, control, and accountability

Discuss the AI workshop

Let's learn

Choose a workshop and come with a real process

First we solve the practical task, then we show how it was assembled so the team can repeat the approach safely and independently.

Go to workshops

We implement AI so a large company actually starts using it

The rocky path to AI in a large company

Resistance first

Control later

Then the platform

Scale in the end

Clients and partners

Workshops as a set of practical missions

Accelerating development of large projects with AI

Accelerating the entire development cycle (Time-To-Use) with AI

A personal AI assistant with OpenClaw

Hermes Agent: a personal AI assistant for executives

AI SecOps: autonomous cybersecurity agents

AI technical support agent

Advanced Claude Code setup

AI-native documents and reporting for developers

AI psychologist: insight into yourself, your team, and mentoring

AI coach: hands-on practice with Claude and AI tools

First solve the task, then teach change management

01 · Process review

02 · Build and validate

03 · Workshop and handoff

From "how do I pay?" to personal AI assistants

Basic access

Practical application

Personal assistants at work

In a large company, even one mastered process delivers a major gain

× People · many users

× Process · many repetitions

↓ IT queue · fewer manual fixes

Experts

Sergey Korshunov

Alexander Stanovoy

Andrey Putin

Alexey Shvets

Dmitry Krymsky

A separate list of upcoming workshops

We do not sell an AI course. We change the company's ability to implement change.

Focus

Method

Foundation

A fit

Not a fit

Discuss the AI workshop

Choose a workshop and come with a real process

Continue on the topic

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