coreAI has taken the step from AI chat to agentic platform: the assistant doesn't just answer questions, it acts – it searches, pulls fresh real-time data straight from the business systems, and runs complex tasks via the Model Context Protocol (MCP) on the user's behalf. coreAI started as an AI chat that gave precise answers from your own content, and the shift moves the solution from a pure answer tool to an integrated work platform that drives real value.
#AI search is only the beginning
AI search is often the first thing customers put in place: a conversation-based entry point to everything the company knows. It gives precise answers from your own content and is the simplest starting point for most partners. See the AI search solution.
#Agentic mode turns chat into action
When the answer needs real-time data or an action, coreAI enters agentic mode. The assistant plans across multiple steps, runs a coverage check and searches again if the answer is thin, and calls external tools via the Model Context Protocol (MCP). The MCP server decides what a given user is actually allowed to do – it's the business system's existing RBAC that applies, not a new authorisation in the AI layer. More in the articles on agentic mode and MCP.
#The use cases that move the workflow
Three use cases drive the most value today, all on the same platform core:
- Customer service: the assistant answers enquiries, looks up orders, escalates cases and updates status without pushing the customer into a queue. See the customer-service solution.
- Shopping list and product discovery: the user describes the need, coreAI finds the products and adds them to the shopping list. See the shopping list in action.
- Knowledge base and search: hybrid search across sources with answers that cite your own content. See the knowledge base.
The next two examples show what this looks like in practice.
#Example: Profixio solves the sports puzzle in real time
Profixio looks up fresh sports data in real time via MCP instead of pre-syncing information that changes constantly. Profixio is an IT company delivering the digital backbone for sports – a system handling everything from tournament and cup registrations to federation administration, licence transfers, and demanding match scheduling where free pitches, travel distance and preferences all have to add up.
It's an enormous puzzle of rules, data and people. When players, parents or coaches use coreAI to find match schedules or results, the assistant looks straight into the database and gives an up-to-date answer in real time. The customer never sees stale information, and Profixio avoids building expensive, bespoke integrations.
#Example: A car workshop automates 90% of the customer journey
A car workshop can use coreAI to resolve a full 90% of all customer enquiries independently, around the clock. Agentic AI reaches all the way out to the consumer through a customer journey integrated into chat, letting the assistant handle everything from simple to advanced tasks across three phases:
- Phase 1 – booking and hybrid support: customers complete appointment bookings directly in the chat, and the system ensures a seamless handover to human customer service if a problem arises.
- Phase 2 – intelligent pricing: when a customer asks the price of a service, the assistant runs a lookup to identify exactly which parts and how much labour the specific car model requires, and gives an exact standard price on the spot.
- Phase 3 – complex repairs: the assistant calculates prices for advanced faults and automatically picks the cheapest parts options to secure an optimal margin for the workshop.
This is agentic AI in practice: the assistant understands the problem, looks up the car's data and the workshop's pricing system via MCP, works out a quote, and books the appointment.
#How to get started
Start with one use case where the data already exists – for example an AI search on your own knowledge base. You don't need to start with the whole customer journey on day one. Once the first flow is in place, connect a business system via MCP and let the assistant act, not just answer. Browse the full solution catalogue to find the simplest starting point.