Generative AI that works for SMEs

We turn AI into measurable value—faster operations, less manual work, and better customer experiences.

Artificial intelligence with a human touch.

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Picture by Deepak Pal

AI, LLM, Workflows and Agents

Generative Artificial Intelligence is opening new horizons for businesses of all sizes.

With Large Language Models (LLMs), companies can automate complex tasks such as document analysis, customer support, and knowledge management.

Intelligent workflows streamline processes across departments, connecting data and actions seamlessly to save time and reduce costs.

AI agents take this further by acting autonomously, handling repetitive operations, and making informed recommendations.

Together, these technologies empower organizations to work smarter, faster, and with greater impact.

Examples of Use Cases

  • Human Resources: CV analysis with job matching, personal training plan, new staff onboarding, and more.
  • Strategy: Competitive intelligence, sector analysis or technical watch.
  • Customer Support: first line contact support with chat or voice bots, FAQ generation from documents and internal resources.
  • Marketing/Communication: multi-channel versus one-channel communication, multi-channel campaign of a new product/service, brand-consistent messaging and beyond.
  • Customer Relationship: incoming email classification triggering workflows, email response preparation and follow-up automation.

What do you need to get started?

  1. Strategic Foundations
    • Clear business goals: Identify why you want to use AI (e.g., automate support, improve efficiency, generate insights, enhance customer experience).
    • Use case selection: Start small with one or two high-value, low-risk use cases: document summarization, chatbot for FAQs, workflow automation among other things.
  2. People & Skills
    • AI champions / leadership buy-in: Someone must sponsor and drive the initiative.
    • Internal skills: Upskill teams in data science, prompt engineering, and workflow design.
    • Partners: Consider external consultants, like IoTec-AI or vendors for faster ramp-up.
  3. Data Readiness
    • Data availability: Collect and organize the relevant documents, structured data, and knowledge bases.
    • Data quality: Ensure clean, reliable, and updated information.
    • Governance & compliance: Handle sensitive data securely (GDPR, local regulations).
  4. Technology Stack
    • LLM platform: OpenAI, Azure OpenAI, Anthropic, etc.
    • Orchestration tools: LangChain, LangGraph, Prompt Flow, or n8n/Make for workflows.
    • Agents frameworks: Tools like AutoGen, LangChain Agents, or custom-built AI agents.
    • Integration layer: APIs to connect with CRM, ERP, internal apps.
    • Infrastructure: Cloud services (Azure, AWS, GCP) or on-premise depending on data sensitivity.
  5. Experimentation & Scaling
    • Pilot projects: Quick prototypes to demonstrate value.
    • KPIs & ROI: Track efficiency gains, cost savings, or customer satisfaction improvements.
    • Scale gradually: Expand to multiple departments or processes once the first use case succeeds.

How IoTec-AI can help?

  • AI Advisory & Intelligent Workflow Design: We assess your processes, identify high-ROI use cases, and shape a pragmatic AI roadmap that fits SME constraints (budget, data, change). Quick wins first, governance built-in.
  • Custom AI Agent Development: Task-oriented agents for support, sales, or back-office that draft answers, summarize, and trigger actions—always with guardrails and human-in-the-loop. Start small, measure impact, then scale up.
  • AI Integration with Existing Business Systems: We connect LLM capabilities to your ERP/CRM/helpdesk and document stores to automate routine tasks (triage, Q&A, extraction) without disrupting operations. Incremental, reversible changes.
  • Training & Change Enablement to Drive AI Adoption: Role-based training and simple guidelines so teams actually use the new tools. We help set policies, prompts, and habits; we coach champions and track adoption.

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