Enterprise AI Execution Layer
We build the secure backend, MCP/OpenAPI tool gateways, Databricks integrations, audit trails, and approval flows that let AI agents move from pilot to production.
For CTOs, AI platform teams, German/Swiss recruiters, and boutique AI consultancies that need senior nearshore engineers for production AI infrastructure.
Senior technical ownership and direct engineering accountability for enterprise teams across Europe and selectively in the US.
MCP/OpenAPI Gateways · Databricks Workflows · Azure Integration · Tool-Level RBAC · Audit Trails · Human Approval Gates · CET-Aligned Delivery · NDA/DPA/SCC Ready
Portfolio-backed delivery across institutional modernization, AI-assisted document workflows, computer vision intake, procurement intelligence, and technical lab systems.
The production gap
Models can reason. Demos can impress. What they cannot do on their own is act safely inside a real business — with permissions, validation, audit trails, and operational reliability. That is where most AI initiatives stall, and that is where Inovativi works.
How AI reaches production safely
The same five steps run behind every Inovativi system: a real business system is exposed through a secure gateway, AI works only inside that controlled surface, sensitive actions pass a human approval gate, and every step is recorded. Nervora, our internal MCP gateway reference architecture, demonstrates these patterns with tool-level RBAC, PII redaction, async execution, idempotency, and audit logs.
ERP · CRM · database · portal · documents
Secure tools · permissions · validation
RAG · agents · structured actions
Review · approve · escalate
Traceability · monitoring · compliance
Selected Work
Inovativi's work spans institutional modernization, AI-assisted workflows, document intelligence, computer vision, technical lab systems, and commerce operations. Each project demonstrates the same pattern: connect real data, real users, real rules, and real operational constraints.
Nervora demonstrates how enterprise AI agents can safely access business systems through a governed MCP gateway with OIDC authentication, tool-level RBAC, PII redaction, dry-run approvals, async workflow execution, audit logs, idempotency, and OpenTelemetry tracing.
Character-driven AI companion robot concept combining voice agents, 3D-printable bodies, customization flows, simple robotics, and responsible AI framing.
A modernized institutional finance platform covering hierarchical budget planning, allocations, spending, invoices, payments, formula traces, reporting, and audit-ready financial workflows.
A modernized HR and personnel platform covering employee lifecycle, recruitment, employment history, leave balance logic, contracts, timesheets, appraisals, documents, and audited sensitive access.
A photo-based window and door quotation workflow using A4 reference calibration, guided corner selection, homography, review screens, and structured quote preparation.
An eyewear recommendation and preview workflow using face-photo intake, AI-assisted style guidance, visual previews, product linking, and guided shopping flows.
A procurement intelligence workflow for tender ingestion, ranking, summaries, readiness checks, alerts, and operator decision support.
A technical lab initiative for RF measurement, SDR training, spectrum awareness, and AI-ready signal workflows such as classification, anomaly detection, and operator assistance.
Portfolio items include internal products, reference architectures, technical lab initiatives, and concept demonstrations. They are labelled transparently to show the type and maturity of each project — not implying confidential client work.
What we build
Enterprise RAG, document intelligence, deterministic workflows, AI backend engineering, evaluation, computer vision, AI-assisted commerce, technical lab signals, and legacy modernization — delivered as one connected execution layer, not separate service lines.
Retrieval over messy enterprise data — PDFs, contracts, tenders, policies, emails, reports, tables, and internal knowledge bases. Hybrid search (BM25 + vectors), reranking, metadata filters, source citations, and permission-aware results.
Pipelines that convert PDFs, scans, tables, legal judgments, procurement notices, invoices, and forms into reliable structured data — with validation rules, JSON outputs, and human review loops.
Controlled AI workflows with defined states, business rules, approval steps, and audit logs — built with LangGraph-style state machines, conditional routing, tool execution, and human-in-the-loop approvals.
Production APIs, databases, queues, storage, authentication, monitoring, cost controls, and integrations — FastAPI, PostgreSQL, Qdrant/pgvector, Redis, Docker, background jobs, observability, and secure deployment.
Evaluation pipelines, regression tests, guardrails, audit logs, and quality dashboards. Faithfulness, context recall, answer relevance, hallucination checks, prompt injection controls, and sensitive data protection.
Add AI capabilities around existing systems without a risky big-bang replacement — API layers, shadow systems, comparison engines, read-only adapters, data synchronization, and gradual migration support. Includes full domain-driven rebuilds of institutional finance and HR systems from legacy ASP.NET into API-first platforms.
Start with a productized first engagement
2–4 weeks · fixed scope
Our fixed-scope AI integration sprint
Expose one internal system safely to AI agents. We map a selected workflow or legacy system, design secure AI-callable tools, implement an MCP / OpenAPI / FastAPI gateway, and add authentication, permissions, validation, logging, and audit trails so AI can interact with real business systems under control.
Governance, safety & cost control
Production AI systems need more than model access. They need controlled execution. We design AI workflows with permission-aware retrieval, tool-level RBAC, prompt-injection safeguards, PII handling, audit trails, approval gates, and deterministic validation before sensitive actions reach production systems.
We build AI workflows with cost visibility from the start: token budgets, loop limits, model routing, semantic caching, usage monitoring, and circuit breakers that prevent uncontrolled agent execution.
Data, documents & retrieval
We connect AI workflows to enterprise data platforms, warehouses, databases, APIs, document stores, and legacy systems — including PostgreSQL, Oracle, SQL Server, Databricks / Delta Lake, SharePoint, CRMs, ERPs, and internal portals.
For complex document environments, we combine vector search, keyword search, metadata filters, reranking, structured extraction, and — where useful — graph-based relationships. We treat GraphRAG as one advanced pattern in the toolbox, not a default.
Institutional modernization
We modernize legacy public-sector and institutional software into secure, API-first, audit-ready platforms. Fiscora and Personora demonstrate how complex finance and HR workflows can be rebuilt from legacy ASP.NET systems into modern platforms with preserved business logic, automated tests, audit logs, and AI-ready extension points.
Institutional Budget & Financial Workflow Modernization
A modernized budget and finance platform covering hierarchical budget planning, execution tracking, allocations, invoices, payments, payroll-related calculations, formula traces, reporting, and audit-ready financial workflows.
Institutional HR & Workforce Modernization
A modernized HR and personnel platform covering employee lifecycle, recruitment, employment history, leave balance, contracts, timesheets, appraisals, documents, reports, and audited sensitive access.
The modernization pattern
How we work
A bounded, evaluation-driven path from a first conversation to a system your operators rely on every day.
We map data sources, workflows, users, risks, and integration points.
We design a bounded architecture and validate it with real documents, real queries, and measurable evaluation criteria.
We implement APIs, retrieval pipelines, workflow logic, databases, and integrations with existing systems.
We test retrieval quality, hallucination risk, permissions, latency, cost, and operational reliability.
We support deployment, monitoring, iteration, and controlled expansion into additional workflows.
Technology
We choose tools based on reliability, integration needs, security, and maintainability — not hype. Our preferred stack supports enterprise RAG, document intelligence, workflow orchestration, and backend integrations.
Why Inovativi
What buyers consistently get: senior technical ownership, hands-on engineering leadership, and no hand-off between sales and implementation.
We build AI that runs every day inside real operations — with monitoring, retries, audit trails, and the boring engineering work that demos skip.
We understand enterprise documents and legacy systems as they actually exist — PDFs without structure, tables in scans, applications without APIs.
We combine backend engineering with AI workflow design, so the same team owns retrieval, orchestration, integrations, and the APIs underneath.
We design for evaluation, approval flows, and clear audit logs. AI proposes, humans confirm where it matters, and every step is recorded.
A bounded first engagement validates the architecture on real data and real queries, with measurable evaluation criteria before scope expands.
Hands-on technical leadership stays close to architecture and implementation throughout the engagement — no hand-offs to a sales layer.
Built for operational environments where reliability, traceability, and human control matter.
Next step
Whether you need enterprise RAG, document extraction, workflow automation, computer vision intake, or legacy system AI integration, Inovativi can help design and build a production-ready backend.
