Practical AI · by AIHUB.WORKS

12 months to make AI part of how your business works.

Your team doesn't need another AI workshop. It needs a structured way to find valuable use cases, build AI assistants, put them into daily work and measure what changed.

Practical AI Adoption is a 12-month partnership with your corporate team. We work on your real business processes, build the solutions together with your people, and stay through adoption.

Book an AI Adoption Assessment →
Svetlana Riabova with a group of workshop participants in a classroom
Hands-on AI workshop with a client team
50–300employees in scope
8–12business processes
1measurable transformation
Q1 · BuildQ2 · EmbedQ3 · ScaleQ4 · Measure
Who runs the program

Practitioners who ship, then teach.

We are an AI automation bureau first. Everything we teach your team comes from systems we built and run for clients in retail, manufacturing, real estate, robotics, finance and healthcare.

Svetlana in front of a screen showing the talk 'AI: How Managers Win Back Time'
“AI: How managers win back time”, management session
8+years automating operations, from robotics to back office
50+AI solutions delivered across enterprise verticals
100+companies advised on LLM strategy and execution
100+pilots managed in one portfolio, hypothesis to proof of concept
YandexX5 Retail GroupKerama MarazziKastellCORE.XPVDS TradeSlise.xyz
Your 12-month roadmap

Four quarters. One corporate team. A growing portfolio of AI solutions.

Q1Weeks 1–13
Focus · Discover & build

Build your first AI assistants

We start with your team's real work: recurring tasks, bottlenecks, and processes where AI makes a measurable difference.

  • Assess AI readiness across up to 300 employees and 4–6 business functions through interviews, a skills survey and process mapping.
  • Identify and prioritize 30+ potential use cases on a value × feasibility × adoption matrix.
  • Select 3–5 pilot projects with an economic model for each: volume, cost per task, expected savings.
  • Train a first cohort of 20–30 employees in a 4-module hands-on course: role-based prompting, research and competitor analysis, knowledge work with NotebookLM and Perplexity, and rapid prototyping with Claude, Gamma and Lovable.
  • Build and test 5 AI assistants on real business tasks, during the sessions, with your data.
CORE.XP · Valuation & property managementBack-office AI
ChallengeProperty listings arrived daily in mixed formats: PDFs, scans, spreadsheets. Analysts copied the data into the CRM by hand, with errors that spread into valuations.
SolutionAn intelligent CRM enrichment assistant that recognizes multi-format documents, extracts the fields and writes clean records into the CRM.
10,000+listings processed daily
95%data accuracy in the CRM
~610employees work on top of the enriched data
Quarterly deliverable5 tested AI assistants, a prioritized implementation roadmap, and a baseline for every pilot process.
Q2Weeks 14–26
Focus · Embed in workflows

Put AI into daily workflows

We take the strongest Q1 solutions and build them into the way the team works every day.

  • Select 2–3 pilot workflows for full implementation.
  • Connect assistants to your CRM, ERP (1C, ERPNext), knowledge base, Slack or Teams.
  • Train 50+ employees in the new workflows with step-by-step video walkthroughs and prompt libraries per role.
  • Set quality checks, human-in-the-loop escalation rules and usage guidelines.
  • Measure adoption and compare every workflow with its Q1 baseline.
Cyprus bank (NDA) · Content & search visibilityAI workflow · 90 days
BeforeThe content team had no scalable way to research the market. Every article meant manual monitoring, writing, design and voice-over.
AfterA 9-step agent workflow: it collects signals from LinkedIn, Reddit and industry media, clusters topics, drafts Q&A articles in the bank's tone of voice, adds branded images and audio, and delivers them to the CMS for editor approval.
12–16 minfrom signal to ready article
+34%organic traffic in 90 days
18financial queries where AI search cites the bank
3–5/wkpublications with the same team
Quarterly deliverable2–3 AI-powered workflows running in real business processes, with documented results and usage guidelines.
Q3Weeks 27–39
Focus · Scale & champions

Scale adoption across the organization

We expand what has proven its value and remove the barriers that stop wider use.

  • Expand successful workflows to 3–5 additional teams or departments.
  • Train 100+ new employees and run weekly office hours for existing users.
  • Establish internal AI champions in every business function, about 1 champion per 15–20 employees.
  • Improve solutions based on employee feedback and usage data.
  • Track weekly active usage, task completion and business impact on a shared dashboard.
BATUMI.WORKS · Tech hub operationsAutomation at scale
Initial pilotOne operations team managing bookings, members and equipment across spreadsheets and messengers.
Scale-upAn integrated CRM and booking platform with automated workflows, rolled out across a 10,000 m² hub and its whole member base.
1,000+active members served
−30%operating costs
55%retention, 25 points above industry average
Quarterly deliverable150+ employees using AI in daily work, with proven workflows adopted across 3–5 departments.
Q4Weeks 40–52
Focus · Measure & hand over

Measure impact and build the next roadmap

We evaluate the year, document what works, and prepare the next stage.

  • Measure every implemented solution against its original baseline.
  • Evaluate adoption, efficiency, quality and employee experience.
  • Identify the next wave of automation and AI integration.
  • Hand over ownership: governance, an internal AI portfolio owner and a continuous improvement routine.
  • Develop the next 12-month AI adoption roadmap with your leadership team.
Innopolis University · Science & business clusterPortfolio management
Initial baseline8 research labs with strong R&D in robotics, computer vision and AI, but no shared path from idea to a deployable solution.
End resultOne managed pipeline: opportunity identification, team assembly, proof of concept, stakeholder presentation. Each pilot judged on feasibility, demand and strategic value.
100+concurrent pilots in one portfolio
8labs on one prioritization model
Quarterly deliverableA documented impact report, an operational AI portfolio with owners, and a prioritized roadmap for the next 12 months.
The business cases we work on

Your processes, not hypothetical AI exercises.

For each use case we set a baseline, build and test a solution, and measure the result after rollout.

Business functionAI applicationWhat we measureFrom our projects
SalesLead research, meeting preparation, CRM updates, product mapping for proposalsTime per lead, preparation time, time to proposalVDS Trade: 40,000+ SKUs mapped and priced automatically into ERP-ready proposals
Customer supportKnowledge retrieval, response drafting, ticket classification, omnichannel inboxResolution time, response qualityClinic network: AI assistant and knowledge base across WhatsApp, Instagram and CRM
MarketingResearch, content production, campaign analysis, A/B testingProduction time, output volume, cost per channelAd platform: analytics engine across 4 channels with AI recommendations
OperationsDocument processing, reporting, performance monitoring, workflow automationProcessing time, error rateKastell: robot performance monitoring and reporting across EU sites
FinanceInvoice preparation, bank statement reconciliation, expense collectionManual share of invoices, close timeFintech: automation plan for invoices, statements and expense bots
How we measure success

We don't count workshops. We count what changed.

We measure whether employees use the solutions, whether processes improve, and whether those improvements create value you can put in a budget.

Adoption

60%+
of target employees use AI solutions every week
150+
employees trained and able to work with AI on their own

Efficiency

1,000+
hours saved per month across implemented workflows
30–50%
less processing time in selected workflows

Business impact

95%
data accuracy target for automated data entry
€500k+
estimated annual value from implemented solutions
How we estimate value: 200 employees × 5 hours saved per month × €45 loaded hourly cost × 12 months = €540,000 per year

Figures above are typical program targets for a 200–300 person team. Your targets are agreed after the initial assessment and baseline measurement.

How we teach

Five principles to take you from theory to application.

Fast and sustainable. Your team learns by doing, on its own tasks, and leaves every session with something that works.

Trainers running a live demo from a laptop in front of a projected screen
Hands-on: building live, on screen
Large group photo of a tech community event
Community: 100+ people at one meetup
Svetlana and a guest expert speaking with microphones
Experts: guest practitioners on stage
Practical RAG Automations webinar: workflow diagram and video of the trainer
Materials: Practical RAG Automations video unit
  1. 01

    Hands-on first

    Instead of just listening to theory, your team works with us in practice from the very first session. Through our challenges, people apply AI to their own tasks right away and gain real experience.

  2. 02

    Community

    No one learns alone. In our learning environment, colleagues meet people with similar goals, share what works and learn from each other. Internal AI champions keep that exchange going.

  3. 03

    Experts

    Our trainers are practitioners who build AI systems for clients. They guide your team step by step, give feedback on real work and are always there for questions.

  4. 04

    Materials

    Easy-to-follow videos combined with concrete methods, clear checklists, role-based prompt libraries and proven frameworks from real projects.

  5. 05

    Flexibility

    On the go or between tasks. Short units and our practical learning app let employees fit the program into a normal working day.

Built around your team

Who works with you

Portrait of Svetlana Riabova speaking with a microphone
Svetlana RiabovaFounder, AIHUB.WORKS · Program lead
Program leadFounder of AIHUB.WORKS. Led AI transformation for enterprise clients and managed cross-functional teams of 50+.
AI & automation engineersBuild assistants, agents and integrations with your CRM, ERP and data.
Learning methodologistDesigns the course modules, exercises and role-based prompt libraries.
Change & project managerRuns the cadence, tracks adoption and supports your AI champions.
Start with your first use case

Tell us which process you want to improve.

We'll assess its fit for AI and define what a successful pilot looks like: scope, baseline, target and cost.

Book an AI Adoption Assessment →
  1. 30-minute call about your team and processes
  2. Readiness snapshot and 3 candidate use cases
  3. Pilot proposal with an economic model