Automation is useful when it removes friction from a process people understand. We help you identify repetitive work, connect the relevant tools and introduce AI where interpretation or retrieval adds value.
AI that knows where to help.
A useful first project could be an assistant that answers questions from approved documents, a workflow that organizes new enquiries or an integration that moves information between systems without repeated copying.
- AI chatbots: Guided customer conversations with clear handover to your team.
- RAG knowledge assistants: Answers grounded in your approved business material, with source references and permission requirements considered.
- Lead automation: Capture enquiries, collect qualification details, assign an owner and make follow-up visible.
- n8n workflows: Connect triggers, business rules, APIs and review steps across the tools you already use.
- AI integrations: Add extraction, classification or drafting to an existing application.
Put it in your world.
For a real estate team, start with enquiry capture and agent assignment. For a travel agency, organize customer requirements and follow-up. For a support team, retrieve approved answers and escalate questions that need a person. These are possible workflows, not claims about deployed client projects.
People own the important decisions.
We define what the system can do, where it needs review and how failures are handled. An agent should not silently promise a price, approve a sensitive action or invent a confident answer when the evidence is missing.
A sensible first step.
Bring one recurring workflow, a few representative examples and the systems involved. We map the process, agree how to evaluate the result and scope a focused pilot before expanding.
AI chatbot development and n8n workflow automation
Delphro’s AI automation work connects the conversation to a defined business process. An AI chatbot can collect an enquiry or retrieve an approved answer; an n8n workflow can validate the details, update a supported system and route the next action to a person. LLM integration adds interpretation where a fixed rule is insufficient, with structured outputs checked before use.
When the main requirement is answering questions from company documents, explore RAG and AI knowledge assistant development. For a customer pipeline that needs its own interface, stages and reporting, explore custom CRM development.