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AI adoption and solutions

From AI curiosity to AI capability

Most organisations do not differ in whether they want AI. They differ in how far they have got, and that decides what they can usefully do next. We start with the work, not the technology, and move one level at a time.

  • 3 daysFrom question to working application
  • 2 peopleTypical team to get there
  • 1Application in use at the end

Book a 30-minute conversationSee the four offers

Where you are now

Four starting points, four different needs. Find the row that sounds like your organisation and start there.

The Ionita path

We move a client up one level at a time

We do not start with the technology. We start with the work, and each stage ends with something the business can actually hold.

  • 01

    Learn

    Understand AI and use today's tools properly, against the team's own tasks rather than a demo.

    A team that can already save hours this month.

  • 02

    Identify

    Map the work, the tools and the bottlenecks, then quantify what AI could actually save.

    A prioritised roadmap with numbers attached.

  • 03

    Solve

    Take one real business problem and test AI against it with your own experts in the room.

    Evidence before investment.

  • 04

    Build

    Build the agents, automations and private AI environment around the company's own data.

    AI inside the workflow, not beside it.

The four offers

Each one stands on its own, and each one ends where the next begins.

Offer 01

AI Essentials

For teams that are cautious, or have simply not started.

A practical crash course, roughly 80% hands-on and 20% explanation. People work on their own tasks, not on worked examples, and leave with use cases they chose themselves.

  • What actually changed in 2026: language models, multimodal, agents, automation
  • The working toolkit: ChatGPT, Copilot, Gemini, Claude, and the research tools around them
  • How to prompt properly: context, task, constraints, examples, iteration
  • Live exercises on two or three real tasks brought by the room
  • Where AI goes wrong: hallucination, confidential data, and how to verify output
  • Everyone leaves with two or three concrete use cases of their own

Offer 02

AI Opportunity Scan

For organisations experimenting in several places without a plan.

A review of the work rather than of the tool market. We interview the people doing the job, map the workflows, and score where AI would actually pay for itself.

  • Workflow mapping across the areas that matter
  • Opportunities identified, scored and prioritised
  • A value calculation in hours and euros, not adjectives
  • A now, next and later roadmap

The six dimensions we scan

  • PeopleLiteracy, resistance, and roles that change
  • ProcessesRepetitive work, administration, bottlenecks
  • TechnologyTools in use, data, systems, integrations
  • AgentsWhere autonomous workflows genuinely fit
  • RiskPrivacy, security, oversight, governance
  • EconomicsHours spent, hours saved, effort, return

Offer 03

AI Research Hub

For a real problem that has resisted the obvious answers.

Bring one problem. An Ionita team works on it alongside your internal experts. Knowledge-intensive work cannot be solved from outside, so the value comes from your domain expertise and our AI capability on the same problem.

  • Define: what exactly are we solving, and what does good look like
  • Research: which tools, models and approaches already exist
  • Experiment: test them against real business material, not demo data
  • Validate: your expert checks quality, reliability and relevance
  • Recommend: build, buy, automate, or do not do it
  • Prototype: optionally, turn the validated answer into a working tool

Offer 04

AI Solutions

For organisations ready to put AI into production on their own data.

A private AI environment built around the company's own documents, data and workflows. The point is not to buy another AI tool, but to build the environment the business actually needs.

  • Ingestion: PDF, DOCX, XLSX and Confluence content becomes searchable instead of scattered across drives
  • RAG retrieval with a preprocessor, so the model receives only what is relevant and hallucinations are cut before they reach a user
  • Model routing across more than twenty models, including the Anthropic, Gemini and OpenAI families, chosen on cost and fit
  • Specialised sub-agents, with MCP for tool access to your own systems
  • Orchestration, guardrails and a testing agent that continuously checks answers stay reliable
  • Human approval before output, and a web interface where employees ask questions and run tasks

Inside an AI Solution

A private AI environment on your own data

Not another AI tool bought off a shelf. An environment built around the company's own documents, systems and approvals.

  • 01

    Ingest

    PDF, DOCX, XLSX and Confluence content is pulled in, so what is scattered across drives becomes searchable.

  • 02

    Retrieve

    RAG retrieval with a preprocessor returns only what is relevant, instead of paying to push whole documents at a model.

  • 03

    Route

    More than twenty models compared and routed on cost and fit, across the Anthropic, Gemini and OpenAI families.

  • 04

    Specialise

    Sub-agents handle specific jobs, using MCP for controlled access to your own tools and systems.

  • 05

    Guard

    Orchestration, guardrails and a testing agent that keeps checking whether answers are still reliable.

  • 06

    Approve

    A human approves before anything becomes business output, and a web interface is where people actually work.

Three ways to buy it

Four capabilities, three packages. Every package ends where the next one starts.

  • Start

    AI Essentials, as a team session

    The team is using AI properly within a week, with two or three use cases each.

  • Most chosen

    Discover

    AI Essentials and the Opportunity Scan

    A scored set of opportunities, the few worth testing, the fewer worth building, and a now, next and later plan.

  • Transform

    Opportunity Scan, Research Hub and an AI Solution

    A working AI solution inside the business, with guardrails, human approval and measured impact.

Scope and price are set per engagement. The 30-minute conversation is where that gets worked out.

Why Ionita

Three things that are rarely sold together. Trainers cannot build. Developers do not teach. Consultants do neither.

  • Business understandingWe start with the problem and the process, not with whatever technology is on offer.
  • AI-native practiceWe test current models, tools and agent setups every week, and we know what each one costs to run.
  • Software deliveryWhen something works, we can build it and run it in production rather than hand over a slide.

AI does

Code, research, comparison, summaries, prototypes, iteration.

We do

Business judgement, technical validation, domain context, quality control, oversight.

What this looks like when it ships

These projects predate the offering, but they are the same work: research against real material, validated with the client's own experts, then built.

The delivery track record behind this

How you can hold us to it

Four numbers we are happy to be judged on.

  • Share of employees actively using AI at 30, 60 and 90 days
  • Hours saved per mapped workflow
  • Use cases tested versus use cases actually deployed
  • Error and rework rate on AI output

The first conversation is free

Bring one workflow, one problem or one idea, and we will tell you what we would do with it. Thirty minutes, no deck.

Book a 30-minute conversation