#AIServices

AI tools enhance how organizations interact with users, process information, and make decisions. By leveraging technologies such as natural language processing, machine learning, and conversational AI, we enable systems to understand intent and analyze data across digital channels.

The service focuses on identifying high‑value AI use cases, designing and implementing intelligent assistants, and integrating cognitive capabilities into business systems and workflows. We support scenarios such as customer self‑service, internal support automation, sentiment analysis, document understanding, and knowledge retrieval, while ensuring scalability, security, and continuous improvement through monitoring and model refinement.

AI and Cognitive services, chatbots and virtual assistants

  • AI chatbot development

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  • Virtual assistants for support, HR, sales
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  • AI-powered automations
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  • Machine learning solutions
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  • Knowledge mining and search systems
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  • Integrations with M365 and external systems
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BUSINESS NEEDS

Self‑service

Customers and employees need instant answers without waiting for an agent, especially for common questions and routine requests.
Support load
High volumes of repetitive tickets and requests reduce service capacity and increase handling costs across support teams.
Knowledge access
Information is often spread across documents, portals, and systems, making it difficult to find accurate answers quickly and consistently.
Personalization
Users expect context-aware interactions across channels, requiring responses tailored to intent, profile, and history.
PROJECT STAGES

Discovery

Identify priority use cases, target audiences, channels, and success metrics, while defining conversation

goals and expected outcomes.

Assessment

Review knowledge sources, data quality, integration requirements, security constraints, and compliance needs to ensure feasibility and readiness.

Design

Create conversation flows, intents, escalation rules,

tone of voice, and AI capabilities such as search, summarization, and document understanding.

Building and testing

Develop and integrate the assistant, configure analytics and monitoring, and test accuracy, edge cases, handover scenarios, and performance.

Launch and improvement

Roll out to users with controlled release, track usage and resolution rates, and continuously refine content, models, and workflows based on insights.

KEY RESULTS
1
Intelligent self‑service

AI chatbots and virtual assistants provide accurate, context‑aware responses across Teams, web, and other channels, reducing dependency on human support for routine queries.
2
Smarter process automation

AI‑powered automations handle complex, data‑driven processes to interpret information, make decisions, and act across systems beyond rule‑based workflows.
3
Faster knowledge access

Knowledge mining and AI search surface relevant information from documents, SharePoint, and enterprise systems in seconds through natural language queries.
4
5
Seamless AI integration

AI capabilities are embedded directly into existing tools such as Microsoft Teams, Dynamics 365, Power Apps, Outlook, and external systems, without disrupting daily work.
Data‑driven decisions

Machine learning models and AI insights uncover patterns, predictions, and trends that support better forecasting, prioritization, and decision‑making.
NEXT STEPS
Kick-off meeting
Discover project, business goals and expectations.
Project estimate and plan
Present project plan and budget (to be discussed).

OPTIONAL *Pilot project
Pilot design project that will allow to evaluate business result.
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