An astronaut in space — a metaphor for the journey from zero to a working AI deployment
0→1
Zero → ONE deployment programme

From zero to your own
AI Assistants.

Two thirds of AI projects stall at the pilot stage.
Zero → ONE walks your organisation through it step by step — from the first conversation with a chat to agents that get work done.

Book a call See the stages

— The offer in brief —

trending_down 66% of AI projects stall at the pilot stage — Zero → ONE is a direct answer to that risk
rocket_launch Full PLC ONE platform deployment in 4 business days
payments Licence from 35 USD per tenant per month + 30% support
— How an organisation matures —

The AI maturity curve.

You cannot jump straight from zero to agents. Before a company can build advanced solutions, it has to learn how to use AI. Zero → ONE mirrors that natural order — which is where the name comes from.

AI maturity curve in a company
STAGE 01 forum

Chat

Getting comfortable with AI and prompts.

STAGE 02 folder_managed

RAG

Working with company knowledge — your documents.

STAGE 03 smart_toy

AI Assistants

Translators, trainers, control, working with text, day-to-day help.

STAGE 04 account_tree

AI Agents

Adopting task-driven AI. Carrying out tasks, comparisons and work.

— Four stages of deployment —

An order that works.

Every stage builds the capability the next one needs. We do not start with agents, because without the skills acquired earlier an organisation cannot sustain them.

01
Chat — a tool for talking to AI

Chat is essential for teaching employees to use more advanced applications. Users first have to master the conversation with a model before they can reach for the tool's advanced features, assistants and agents. PLC ONE provides core chat functionality at a fraction of the market price — and at the same time closes the door on Shadow AI.

02
Private work with company documents

Models trained on internet knowledge need to be supplemented with the organisation's own expertise. That is what the RAG technology built into PLC ONE is for: a knowledge base and intelligent document processing. Company documents become a source of knowledge for training, marketing material, reporting and sales support — with descriptive attributes, advanced search and Deep Search analysis.

03
Building AI Assistants

The platform lets you build shared workplaces — tenants — with private user groups, your own document content and full control over how the models work. Assistants do more than answer: they search documents and the internet, analyse data, generate finished documents and presentations, and perform operations in company systems — email, calendar, CRM, and work and ticket management systems. Their defining qualities are full control, security, accountability and task-level repeatability.

04
AI Agents and custom solutions

Once the organisation has mastered building assistants, we recommend moving towards advanced agent systems and individually developed solutions. For those, PLC ONE acts as the operating system — providing the expert tooling needed to build processes involving many agents and to integrate different data sources. The platform is under intensive development, and our team supports you by taking on the engineering work.

Not sure where to start in your organisation?

Every organisation runs on different processes and different data, so instead of a generic feature list we would rather walk you through the use cases that fit your company. Thirty minutes, no commitment, no sales pitch.

Let's talk about what's possible
— Why start now —

Shadow AI is already running in your company.

Shadow AI is employees using public, unauthorised AI tools for work purposes — without the knowledge or approval of the IT department. Every company should provide and control its own corporate AI chat.

visibility_off

A total loss of control

No oversight of how and where company documents and code are processed. Data leaves the organisation and nobody records it.

psychology

Bans do not work

The phenomenon comes from a natural wish to make complicated tasks easier. Blocking the tools does not remove the need — it only moves it out of IT's reach.

verified_user

The answer: a company chat

PLC ONE gives employees the tool they are looking for — under IT control, with corporate sign-in and oversight of the data. Core chat functionality at a fraction of the price available on the market.

— Scope of deployment —

We get the platform running in four days.

A fixed-price deployment within the Zero → ONE programme. A defined scope and a defined date — no open-ended budget and no stage where the project gets stuck.

0
business days of deployment
0
scope items included
0
training paths
fact_check
Verification of the infrastructure prepared by the client
rocket_launch
Deployment and launch of the PLC ONE application
manage_accounts
Configuration of the integration with the user system and global roles
workspaces
Planning and creating the first tenants (a maximum of 3–4)
tune
Configuration of the core application and tenant parameters
receipt_long
Configuration and walkthrough of ordering and settling AI tokens
school
Administrator training on operating and managing the application
support_agent
Walkthrough of raising issues and handling service requests
menu_book
Handover of technical documentation and the application manual
— How to read the offer —

Four items that add up.

The offer is modular — you pay only for what you actually use. The figures below are indicative; we will prepare an exact calculation during the call.

01
Licence
Choosing the number of tenants — working groups and departmental assistants. The minimum is 10 tenants. The fee is monthly and can be cancelled ad hoc. from 35 USD / tenant / month + 30% support
02
Token pre-paid
For the AI models' work you pay the token price offered by their providers, itemised and billed on the platform. We suggest a small initial order — consumption at that point is negligible. ≤ 200 USD / to begin with
03
Deployment
A fixed fee for installing the application and the core deployment within the Zero → ONE programme. Four business days, nine scope items. fixed fee quoted after the call
04
Training
Chosen à la carte, according to your individual needs and your team's experience. Six paths mapped to three roles in the organisation. quoted after the call

Early Adoption until 1 January 2027

Within the Early Adoption programme you receive the application with the full functionality of the Enterprise edition — including features as they are released — at a special price.
The amounts given are indicative and do not constitute a commercial offer within the meaning of the Polish Civil Code.

— The 0 → 1 training programme —

Six paths, three roles.

We match the training to the role a person holds in the organisation. All sessions are delivered online.

Role Training path Indicative duration
End user S1S2 4 h
Tenant owner / AI Lead S1S2S3 6 h
Platform operator (technical role) S4S5S6 from 5 h

S1.1 Why a company assistant rather than a free tool

  • How Shadow AI works, with concrete examples
  • What the user gets in return
  • Data admissibility rules: “allowed / conditional / not allowed”
  • Corporate sign-in (SSO)

S1.2 Choosing an assistant and the anatomy of a conversation

  • The assistant picker, layouts, your own ordering
  • Why there are several assistants rather than one
  • Choosing a model mid-conversation and the cost–quality trade-off
  • Four working modes: extended reasoning, internet, short answers, Deep Search
  • Stopping and resuming an answer
  • Resilience to an interrupted session
  • Editing a question and answer variants
  • A visible trace of the assistant's work
  • Keeping conversation history in order
  • Copying, saving formulas and amounts, light/dark mode, interface language, message length limit

S1.3 Practical prompting

  • The skeleton of a good instruction
  • Iteration instead of a single shot
  • Anti-patterns
  • What you do not need to type
  • Answers picked from a list
  • The prompt as a team asset; nominating candidates for Skills
  • Exercise: your own end-to-end task, timed before and after

S1.4 Verifying answers and the limits of trust

  • Where hallucinations come from
  • Reliable and unreliable tasks
  • Reading source references and the excerpt preview
  • Three markers: source used, source found but unused, the model's general knowledge
  • Platform safeguards: relevance checking, no quoting from memory
  • The rule: you sign it with your name — you check it
  • Reporting a bad answer to the tenant owner

S1.5 Output, integrations, token budget

  • Output files: documents, spreadsheets, presentations, images
  • The connected accounts panel — linking your own account and its permission scope
  • Approving irreversible operations
  • Invoking Skills
  • Budget: warning, block, how the model and mode affect consumption
  • Awareness of conversation oversight

S1.6 Attachments in a conversation

  • Only for assistants permitted to work with files
  • An ad-hoc file in a conversation versus a document in the knowledge base
  • How a knowledge base works and what that means for how you phrase a question
  • What the platform does automatically, and what the user does not have to do
  • Narrow versus broad questions; questions about completeness
  • Filtering by descriptive attributes
  • When to switch on Deep Search
  • Working with a long document
  • Numerical data and tables
  • Spotting a gap in the base and reporting it to the owner

S3.1 Designing an assistant and dividing work into tenants

  • From task to assistant: an assistant, a Skill or a prompt
  • The assistant card
  • Tenant boundaries: confidentiality, knowledge ownership, billing
  • Assistant groups and permissions
  • The assistant lifecycle; the limit on the number of assistants
  • Visual identity and the welcome message

S3.2 Creating assistants

  • The library of ready-made assistants
  • When to use the library, when to use the Wizard
  • The assistant Wizard — a full walkthrough
  • The draft prompt for approval
  • The Wizard's safety rules
  • What the Wizard does not know — the owner's remaining work

S3.3 System prompt — workshop

  • The structure of a prompt
  • The hierarchy of knowledge sources
  • The balance: prompt / knowledge base / Skill / model
  • Boundaries of responsibility
  • Rules that limit hallucinations
  • Tone and answer format
  • Prompt versioning

S3.4 The knowledge base — the owner's work

  • Qualifying a document for the base
  • Adding documents, statuses, reprocessing
  • OCR for scans
  • Descriptive attributes and bulk completion
  • Designing an attribute set — an exercise on the client's own corpus
  • Document structure and navigating by headings
  • Spreadsheets: preparation and analysis
  • Configuring Deep Search per assistant
  • Maintaining the base as an ongoing process

S3.5 Skills — when and what for

  • What a Skill is and why it exists
  • The anatomy of a Skill
  • Deliberate and automatic invocation
  • Executable Skills and the sandbox
  • Bulk import of Skills
  • Assigning Skills to assistants
  • Exercise: building a Skill

S3.6 Models, tools and permissions within an assistant

  • Assigning models and per-model features
  • ZDR and the EU region requirement per model
  • The minimum tool set
  • Three operation modes: allowed / requiring approval / blocked
  • Access to external information and address allow-lists
  • Formats of generated material and their limits
  • Permissions down to a single configuration field

S3.7 Quality, cost and maintenance

  • Diagnostics: “what to do when the result is poor”
  • Oversight of conversation quality
  • Assistant analytics
  • Cost optimisation based on data
  • Maintaining an assistant

S3.8 Closing workshop

  • Building a departmental assistant from scratch to a test set, with a demo for participants
  • The model catalogue
  • ZDR and the EU region requirement
  • Tenants and their lifecycle
  • Users and accounts
  • Roles built from elementary permissions — exercise: three intermediate roles
  • User groups
  • Corporate identity and SSO
  • Active Directory / Microsoft Entra ID; onboarding and offboarding
  • Organisation and assistant-group analytics
  • Billing by operation type
  • Limits and balance; ordering tokens
  • Background work and scheduled tasks
  • White-label
  • The performance-quality settings panel
  • A method for tuning parameters
  • MCP — what it is and what it is for
  • Connecting an MCP server
  • Microsoft 365 — the configuration wizard and permission mapping
  • Zoho — CRM, mail, calendar, processing regions
  • Atlassian — Jira, Confluence, Compass
  • ServiceDesk Plus — permission control and audit logging
  • The sandbox for executable Skills
  • Integration diagnostics
  • Integration hygiene
  • Assistant versus agent
  • Integration with external data; MCP as the route to industry systems
  • How to recognise a process suited to an agent
  • Human-in-the-loop
  • Safeguards and operating boundaries
  • What questions should I be asking — workshop
  • Disclosure obligations and accountability
  • From idea to deployment with PLC
— Let's work together —

Let's talk.

Looking for an ITSM system, an RFID solution, or want to deploy AI in your company? Briefly describe your need — we'll get back to you and figure out the best next step together.

schedule We reply within 24 h (on business days)
engineering A conversation with an engineer, not a salesperson
handshake 30 minutes, no obligations
mail konsultant@plc-solutions.pl phone +48 61 657 62 30

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