Our architecture
Architectural differentiation
It is a quick model to deploy, but it introduces structural limitations that are difficult to resolve in production: high latency in multi-step tasks, no shared process memory across channels, limited behavioral control and insufficient audit trails for regulated environments.
Our technology stack is designed to overcome these limitations at their root.
Vertical fine-tuning
We use base models fine-tuned for specific domains, optimized for the latency/accuracy trade-off in real-time environments. The voice-to-voice system operates with target end-to-end latency below 500ms.
Shared process knowledge layer
A centralized knowledge architecture that powers all active agents, regardless of the channel: email, chat, VoIP telephony and APIs. A single point of update, with immediate propagation across all touchpoints.
Multi-agent orchestration
Coordinated agent pipelines with explicit state management, fallback mechanisms, configurable human escalation and structured logging for a complete audit trail.
API-first integration
Native connectivity to ERP, CRM, CMS, BI and custom systems through REST, GraphQL and webhooks, without proprietary middleware to manage.
Geographic and regulatory positioning
We are a 100% European solution. Our infrastructure, models and data governance comply with the AI Act and GDPR regulatory frameworks and are designed for environments requiring European data residency — a critical, non-negotiable requirement in regulated sectors such as finance, healthcare and public administration.
Continuous R&D: seeing technologies before the market
We invest significantly in research, both internally and
through active partnerships with universities and applied
research projects. This gives us a distinctive position:
we gain access to emerging AI technologies before they
reach industrialization, with the time needed to analyze
their real-world limitations, identify the areas of
greatest benefit and bring them to market in a mature
form, before they become commodities.
The practical result is twofold: our clients adopt
technologies that have already been internally validated,
not beta versions; and our automation system can extend
across active projects, where applicable, generating
shared efficiencies and reducing overall development costs.