Nalune is the technical foundation for teams that build themselves: API-first, multi-tenant, auditable and ready for productive AI in existing products and processes.
Audio
conversations turn into structured data
OCR
documents become readable and searchable
Knowledge
friday. and edith. hold the context
Audit
every processing step is logged
Starting point
From scattered knowledge to an executable process layer: the three stages Nalune closes between existing systems and day-to-day execution.
Relevant content appears in calls, inboxes, forms, tickets and documents. Turning it into a process step costs valuable time.
Nalune connects existing systems, knowledge and AI models into an intelligent layer between information and operational execution.
Tasks, documentation, decisions and actions emerge structured, traceable and embedded in the systems already in daily use.
Ecosystem
Six building blocks that interlock: from the incoming information through processing to the audit trail. Each one is callable on its own, none stands alone.
The platform boundary every request passes through. It ties identities, permissions, tenants, audit trails and operating models into a production-ready foundation.
An information input becomes a structured process with steps, states and audit events. Decisions stay explainable and processes stay controllable.
Spoken content is recognised and analysed automatically. Nalune extracts the information worth acting on.
Documents are recognised and read automatically. Nalune extracts their content and makes it structured and searchable.
The reasoning layer connects rules, knowledge and models into traceable results: tasks, documentation, decisions and next steps.
Full traceability and audit trails. Every processing step is logged for audits and regulatory requirements.
Research
Two systems, one cycle: edith. researches what is missing, friday. retains what holds. Whatever has been settled once does not have to be asked again.
While friday. stores the knowledge, edith. makes sure new knowledge appears. She works like a digital research analyst: when the system detects missing knowledge, edith. starts researching automatically.
Classic databases store data, friday. stores knowledge. Where tables and documents stay isolated, friday. structures information as connected knowledge units with source, time reference and trust level.
Together they form a knowledge flywheel: every request builds new knowledge that is stored for good and makes future decisions better.
Classic AI often guesses. Nalune knows. With edith. as the analyst and friday. as the memory, knowledge emerges that stays structured for good, traceable and citable.
Nalune brings integration, compliance, auditing, knowledge management and process automation together, so AI doesn't end as a demo but works inside real operations.