Reference architecture
A repeatable architecture for putting AI into real operations. Your systems stay the source of truth, a governed gateway controls every tool call, controlled AI workflows take structured action, and an operator layer plus end-to-end audit keep the whole system accountable.
The pattern
Most AI projects stall between a convincing demo and a system you can actually run. The gap is rarely the model — it is everything around it: identity, permissions, approvals, redaction, idempotency, recovery, and the audit trail that lets a regulated organization trust an automated action.
We close that gap with a layered pattern. Existing systems stay authoritative. Nervora governs every tool call. Controlled AI workflows orchestrate retrieval, agents, and rules into structured, inspectable actions. Operanto gives operators a place to work alongside the AI. And audit, monitoring, and review wrap the whole system so nothing happens off the record.
Fiscora · Personora · Existing systems
Finance · HR · ERP · CRM · Legacy apps
Nervora
Identity · RBAC · Tools · Approval · Redaction · Idempotency · Audit
Controlled AI workflows
RAG · Agents · Rules · Structured action
Operanto
Inbox · Workflow · Quote · CRM · Human-in-the-loop
Audit · Monitoring · Review
Every action logged, traceable, and reviewable
Layer by layer
Each layer has a single, clear responsibility — together they form one controlled path from your system of record to a safe AI action.
Finance, HR, ERP, CRM, and legacy applications stay authoritative. Fiscora and Personora show how even legacy institutional platforms become API-first, audit-ready systems the AI layer can safely build on.
Nervora is a secure MCP / OpenAPI gateway. Every tool the AI can call passes through authentication, permission checks, approval, redaction, and idempotency — with a full audit record on each call.
Retrieval, agents, and business rules run inside durable workflows — not as a free-roaming agent. State is persisted, steps are inspectable, and the system takes structured actions rather than unconstrained ones.
Operanto turns the controlled workflow into something a team can operate: a multi-channel inbox, quoting, CRM, scheduling, and approvals — the place where humans and AI work the same process together.
Every action — model call, tool call, and human decision — is logged, traceable, and reviewable. Monitoring and observability make behavior visible in real time; review closes the loop on quality, cost, and compliance.
Sovereignty layer
We design AI systems that remain operational when providers, prices, regulations, or geopolitical conditions change. Our architecture combines self-hosted and open-weight models for control and continuity, European model providers and infrastructure for data sovereignty, premium frontier APIs for the most demanding tasks, and deterministic business logic, audit trails, human approvals, and manual fallback paths.
Models are replaceable components — not operational dependencies.
Explore AI resilienceBusiness application
Your product or operational system
Inovativi AI Gateway
One vendor-independent control plane
Policy · routing · data classification · audit · fallback
Every request is governed before a model sees it
Premium APIs · European models · self-hosted open-weight models
Interchangeable model backends
Deterministic services & human approval
Continuity when models are unavailable
Why this pattern
These are the non-negotiables behind every system we put into production.
AI augments your systems; it does not replace or bypass them. The system of record stays authoritative and consistent.
The AI operates inside durable workflows with rules and structured actions — predictable behavior over open-ended autonomy.
Sensitive and irreversible actions pass through explicit human approval, not implicit trust in a model.
Every model call, tool call, and decision is logged and attributable — auditability is built in, not bolted on.
Workflows survive failures, retries are safe, and actions are never silently executed twice.
Permissioning, redaction, and monitoring keep data exposure and model spend within deliberate bounds.
Proven in production
Each project applies the same pattern to a different domain — AI operations, secure tool access, and institutional modernization.
The reference implementation of the governed access layer: authenticated, permission-controlled, auditable tool execution for enterprise AI.
Read case studyAI operationsA multi-tenant operator surface that turns conversations into commercial operations over a controlled workflow engine.
Read case studyInstitutional modernizationA legacy institutional finance platform rebuilt into a secure, API-first, audit-ready system AI can safely extend.
Read case studyInstitutional modernizationA modern HR platform with governed access to sensitive data and a multi-provider AI extension layer.
Read case studyNext step
Tell us about your systems, data, and the workflow you want to put into production. We will respond with an architecture path from a bounded first step to a governed, audited AI workflow.