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An AI work room for teams that no longer want to start from scratch.
MetaCore Studio creates a managed AI Workspace Room: project context, files, decisions, tasks, and AI handoffs stay in one operating space.
ChatGPT, Claude, Grok, or another AI can pick up the work from the same state. The team sees what was decided, what happens next, and where the last operator left off.
An AI operating space for the team.
MetaCore Studio unites context, files, decisions, and AI handoffs into one work layer the team can continue without chaos across tools.
One project context
The project has a clear state, file index, decision logic, and working language that another AI or person can take over.
Handoffs without starting over
ChatGPT, Claude, Grok, or a team member receives a handoff state: what was done, why, what remains, and where to continue.
Hygiene and control
An operator watches for drift, manages tasks, protects decision boundaries, and keeps the project from scattering across chats.
Team memory
Knowledge no longer lives only in one person's or one session's head. Studio becomes the place where the project has continuity.
One business process. The full AI team.
A client request should not travel through ten separate chats. Studio unites organization context, specialist AI roles, leadership approval, and project memory into one auditable work cycle.
The request is linked to client history, prior proposals, pricing, technical constraints, and company sales rules.
the workflow
Leadership receives the essence, pricing, key assumptions, risks, unanswered questions, and the proposed next step.
Line architecture, integrations, and a preliminary implementation stage.
Price, margin, timelines, payment stages, and validity terms.
Uncertain data is separated from confirmed facts.
Approve the price, discount, and sending the proposal to the client.
One entry point
Organization knowledge
Specialist work
Clear authority
Approved result
The full task moves through one contextual chain.
Not raw material — a prepared decision package.
Every AI role and human approval point is visible.
The approved result becomes the starting context for the next work.
People do their work. The AI team keeps the shared thread.
Each specialist gets their own assistant, while files, decisions, and tasks stay in one Workspace Room. Master AI coordinates handoffs, and the team lead sees the shared state and makes the important decisions.
AI work grows faster than team memory.
Companies already use multiple AIs, but project history stays in chats, files scatter, and each new session starts from scratch again.
Context disappears
Every AI chat starts without project history, so the team repeats the same briefing.
Files have no single home
Documents live in chats, drives, emails, and personal computers.
Handoffs break
One person or AI starts the work, another takes over, but the decision logic stays unclear.
Workspace Room becomes the project's operating space.
This is not another chat. It is a project room where AI works with the same context, and the team sees decisions, files, tasks, and next actions.
Reflection profile, reports, KR, and human-readable project language.
MetaCloud space, files, history, handoffs, continuity across sessions.
Bridge API, MCP Connector direction, multi-AI connections, and operator discipline.
One place for the project, ordered context, a file index, and a decision log.
Project teams, agencies, consultants, training and business teams.
MetaCore Context Operating Layer + MetaCloud Workspace + Bridge API + MCP direction.
Not a single assistant. A full digital expert team.
MetaCore builds a role-based AI team that works in one company context. Each agent has its own responsibility, while Master AI coordinates the work, unites results, and presents leadership with what needs deciding.
Leadership and decisions
Helps see the whole business, model scenarios, and make informed decisions.
Marketing and sales
Builds positioning, campaigns, sales materials, and customer growth systems.
Products and projects
Manages roadmap, priorities, tasks, testing, and the team's execution rhythm.
IT, systems, and automation
Designs architecture, connects systems, builds workflows, and maintains technical continuity.
Finance, legal, and documents
Prepares budgets, forecasts, document drafts, and risk summaries for human review.
Team and knowledge transfer
Supports hiring, onboarding, training, communication, and building shared work memory.
From a single specialist to a multi-department organization.
For one owner or expert: strategy, content, clients, documents, and day-to-day control.
Clear roles, shared project memory, task handoffs, and work coordination.
Sales, marketing, finance, operations, and IT work in one managed structure.
Multiple workspaces, permissions, audits, agent networks, process integration, and human approvals.
The same AI team logic — for different businesses.
Proposals, client analysis, project management, knowledge bases, and expert content.
Product content, campaigns, customer support, inventory, and sales analysis.
Roadmap, support, documentation, QA, incidents, integrations, and DevOps processes.
Orders, suppliers, warehouses, quality, planning, documents, and operational summaries.
Briefs, ideas, campaigns, client alignment, content production, and project handoffs.
Programs, materials, assessment, community communication, and personalized support.
Standards, location coordination, SOPs, training, quality control, and a shared knowledge center.
Document flows, projects, applications, reports, communication, and process transparency.
Outcome: one team, one context, a clear leadership role.
AI prepares, analyzes, and coordinates. The human sets direction, manages permissions, and approves important actions.
Leadership no longer walks through systems. The whole team comes into one work stream.
MetaCore Studio turns isolated AI chats into a managed process: a task has context, a responsible agent, interim results, human approval, and preserved team memory.
Direction
Leadership states the goal, priority, and limits in plain language.
The human sets directionCoordination
Master AI breaks down the work, selects agents, and forms a clear execution plan.
Master AI runs the flowExecution
Specialized agents analyze, create, verify, and hand results to one another.
The AI team works togetherApproval
Leadership receives a short essence, risks, and prepared decision options.
Important actions stay with the humanMemory
Decisions, files, and context stay in Workspace Room and become the start of the next work.
The team no longer starts from scratchOne clear view instead of dozens of windows.
Leadership sees only what matters for the decision: status, blockers, responsibilities, risk, and the next action.
AI operates only as far as it is allowed.
Each role gets boundaries, data access, and actions that may only be prepared — or executed only after approval.
Information is collected, grouped, and passed on automatically.
Leadership gets not data noise, but prepared essence and choices.
Knowledge no longer stays in one person's chats or personal files.
New agents, processes, and integrations connect to the existing core.
The leadership AI work portfolio starts with Workspace Audit.
Through the audit we form a real business AI work map: where context disappears, which processes stall, which roles are needed, and how Workspace Room should connect to the leadership decision rhythm.
Workspace Audit
0 € / initial assessment
A short review: current AI work process, risks, handoff gaps, and the first Workspace Room structure direction.
AI Workspace Room
from 1500 € / one-time
A private project room, initial indexes, file structure, handoff rules, decision log, and work protocol.
Team + Care
from 300 € / mo.
Periodic hygiene, decision index, AI handoff supervision, operator support, and team continuity.
AI sessions, file logic, decision history, team handoffs, and process points where time is lost today.
A private Workspace Room, initial context, work protocol, AI team roles, and a clear leadership control path.
Drift, task continuity, the decision index, operator notes, and a clean transition between AI tools.
How we launch the first Workspace Room
Audit
We review files, AI sessions, the team process, and the project goal.
Structure
We create the workspace structure, indexes, rules, and handoff logic.
Operate
The team works in one Workspace Room, AI receives continuous context, and decisions stay visible.
Care
Periodically we clean up drift, tasks, decisions, files, and project memory.
We audit more than tools. We restore the full operating logic of the company.
We follow how a product or service emerges from market demand, how it is created, handed across departments, sold, delivered, and paid for. This creates one contextual company map used to design the AI team and the Master AI coordination layer.
Business model and market
Goals, customers, segments, competitors, value proposition, pricing, growth directions, and decision-making rhythm.
Presentation and demand
Brand, websites, offers, presentations, campaigns, content, channels, leads, and their handoff to sales.
Products and services
Assortment, specifications, labels, documentation, kits, service packages, and quality criteria.
Creation and assembly
Raw materials, components, work stages, responsibilities, production timelines, control points, defects, and approvals.
Suppliers, warehouses, and logistics
Purchasing, supplier terms, inventory, warehousing, transport, order kitting, delivery, and returns.
Customer journey
From inquiry and proposal to contract, order, fulfillment, support, repeat sales, and loyalty.
Cash flows
Purchases, invoices, payments, advances, receivables, margins, costs, budgets, reports, and financial approvals.
Departments and responsibilities
How information, product, and service move between people, teams, partners, and leaders — and where waiting appears.
Systems and data
CRM, ERP, accounting, email, files, clouds, devices, integrations, access, security, and data quality.
Outcome — one contextual company model.
Master AI understands the specific organization's terms, products, roles, rules, dependencies, and process sequence. Then the AI team can not only answer, but coordinately prepare work, monitor progress, and help manage processes according to the company's real specifics.
Help us see how your organization actually works.
The form helps start a full operating-context map. You do not need perfectly documented processes — it is enough to show how products, services, information, responsibilities, and money move today.
The human at the center of the decision. MetaCore is a work and reflection layer, not a decision-maker.
Clear boundaries. This is not a diagnosis, therapy, or legal or financial advice.
Private workspace. Client context is kept isolated and is not used for advertising.