AI
Consulting

AI consulting means analysing a business's existing workflows and identifying where automation, chatbots, or agent deployments can deliver measurable value, then putting those solutions into production. It is relevant for businesses of any size that face high manual workloads, repetitive tasks, slow customer communication, or scaling bottlenecks. Sector is secondary — whether manufacturing, services, healthcare, or e-commerce, the benefit comes from how the process is structured.

ADWEBX AI consulting covers five areas: (1) AI strategy and roadmap — process analysis and a prioritised implementation plan; (2) process automation — automating repetitive workflows with n8n, Make, and custom integrations; (3) AI agent deployment — auditable autonomous assistants connected to CRM and internal systems; (4) LLM chatbot development — RAG-based support bots for websites, WhatsApp, and Instagram; (5) corporate AI training — hands-on prompt engineering and safe-use workshops for teams.

Quoting a fixed price without knowing scope would be misleading. The logic is straightforward: the human-hours spent on each repetitive task are compared with the automation cost, and that difference forms the ROI. During the free AI readiness assessment, ADWEBX prioritises the processes most likely to deliver measurable savings in the shortest time, anchoring the price estimate to a concrete scope so the investment decision is based on real deliverables rather than abstract promises.

Data security and KVKK compliance are core design criteria for every AI project — they are built in from the start, not added as an afterthought. Which data is processed where is defined clearly before any customer data reaches third-party model providers; on-premise or private cloud architecture is set up when required. All AI decisions are designed to be auditable: human approval is mandatory at critical steps, and a guardrail architecture draws boundaries where the system can act autonomously.

A straightforward automation workflow typically takes a few weeks; projects involving CRM, ERP, or multi-step agent architectures take longer. The process follows these stages: during the free assessment, existing systems and API access are reviewed; the priority use case is defined; once the pilot scope is clear, development and testing begin; after go-live, a monitoring and fine-tuning period follows. Payment for the pilot can be structured around actual results.

ADWEBX applies AI consulting in its own operations, not just in theory, which means it brings both technical and business-outcome perspectives to every project. Measurement is based on concrete metrics: adoption rate, reduced manual hours, lead response time, and process error rate. Success criteria are agreed at the start of each project and results are shared through regular reports. We commit to measurable, iterative improvement rather than guaranteed outcomes.