Reference scenarios: what gets automated, which systems it connects to and which KPI is tracked from day one. They are illustrative examples of typical projects, not results from specific clients.
Online shop for gourmet products with thousands of orders a month. The decision-tree chatbot is replaced by an agent powered by RAG over the catalogue and real actions against the ERP. The 90-day goal: resolve most enquiries without escalating to a human, measured against the previous bot.
Talk about a case like this →vs. the previous bot's rate
infrastructure and team hours
with and without cross-sell
vs. the human team
Illustrative examples of typical projects in each sector: they do not correspond to specific clients and include no results.
A mid-sized law firm. Contracts, opinions and precedents are indexed with verifiable citations and integrated into the document manager. Every answer carries the exact source citation and, when there is no source, the assistant says so.
A physiotherapy chain. Voice and chatbot to book, modify and remind appointments; automated reminders aim to cut no-shows.
A model with external factors (weather, holidays, local events). Every night the operations team gets per-store restocking recommendations integrated with the WMS. Goal: reduce stockouts and waste at the same time.
IoT signal analysis on CNC machines at a metalworking SMB, to detect degradation hours ahead and plan the stop instead of suffering it.
Semantic CV-vacancy matching with auditable justification and bias mitigation, to shorten time-to-hire on junior and mid-level profiles. Always with human review.
A catalogue of thousands of SKUs: before, copy-pasted from suppliers; now generated in the brand's voice with extracted taxonomy and attributes. Goal: pages indexable in hours instead of days.
Bank–invoice–order matching across the firm's client base, to cut monthly back-office hours and free the team for real consulting.
Calls answered in Spanish, Catalan and English. The voicebot books, modifies and confirms with no human intervention and captures bookings at peak hours, when calls used to be lost.
Every proposal arrives with a baseline, a quantified hypothesis and a measurement plan. If we can't measure the impact, we don't build it.
Every week there is a demo and a KPI in plain sight. If the projected return isn't met, it gets adjusted or switched off.
30 minutes. We review your case and walk away with a concrete map of opportunities.
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