A systematic approach, not a set of agents
Alex AI Studio is a full-cycle studio: we build solutions that automate processes and tasks with artificial intelligence, for businesses and for private clients.
We offer not a set of AI agents but a systematic approach and a complete solution with a measurable economic effect.
The difference is practical. A standalone agent closes a task and then runs into the limits of the process around it. We start with the process: where it loses time and money, what within it can be handed to an agent, what control that requires, and how to calculate the result so the number is accepted by the finance director and not only by the project's author.
Six lines of work
From a personal assistant for an executive to a platform on which a company runs its own AI development.
AI assistants
Personal AI assistants for executives and teams: tasks, mail, calendar and projects in one interface.
AI agents
Autonomous performers of routine work: they gather context, calculate, prepare decisions and carry them through to a fact.
Integrations
AI together with 1C, SAP, CRM and ERP: not a front end over the systems but a single ecosystem under full control.
Analytics
AI analysis of processes and bottlenecks: exactly where time is lost, at which step and for what reason.
Industry solutions
Retail, logistics, finance: scenarios where the industry specifics are built into the statement of the task itself.
The Alex platform
A foundation for running AI development inside the company: shared standards, reuse and quality control.
What the approach is built on
The AI part is neither the only one nor the first. Before it come twenty-five years of managing projects where the cost of a mistake was measured in billions and in hundreds of people.
Experience that pilots cannot give you
We have run projects where a decision is made once and costs a great deal: multi-year programmes with budgets in the billions and teams of hundreds. That is why we start not with the model but with the process, the constraints and the economics — and can discuss the result in language a board accepts.
Process automation
Finding bottlenecks and redesigning the process around AI, rather than automating the current mess as it stands.
Complex systems development
ABAP, Python, JavaScript and TypeScript and adjacent technologies — where a solution has to be built rather than assembled from off-the-shelf parts.
AI services and products
LLM agents, integrations and chatbots: from idea and prototype through to rollout and support in production.
ERP-class implementation
SAP S/4HANA and integrations with 1C. Full-cycle projects — from conceptual design to production operation.
Technology that drives real results
The stack is chosen to fit the task and what the client already runs, not the other way round.
Where to start the conversation
The shortest route is to look at what already works and pick a process for a four-week sprint.
What is already deployed and opens from a link
Seven enterprise agents, three of them reaching external tools over MCP, plus eight libraries of the protocol.
Prove the value in four weeks
One process, a prototype on production data, an assessment of effect and risk, a production architecture and a rollout plan.