Production systems, not demos
We build AI that runs every day inside real operations — with monitoring, retries, audit trails, and the boring engineering work that demos skip.
AI Backend & Integration Engineering
Production AI Backends for Enterprise Documents, Workflows, and Integrations
Inovativi builds AI systems that connect private documents, databases, legacy applications, and human approval workflows. We specialize in enterprise RAG, structured document extraction, deterministic AI agents, evaluation pipelines, and secure backend integrations.
Production AI infrastructure for real business workflows.
Senior-led, engineering-driven delivery for enterprise teams across Europe and selectively in the US.
Python · FastAPI · PostgreSQL · pgvector · Qdrant · LangGraph · MCP · Docker · Evaluation Pipelines
Production AI backends for enterprise documents, workflows, and integrations
Enterprise RAG, document intelligence, and evaluation pipelines
Deterministic AI workflows with audit trails and human approval
Secure cloud, hybrid, or on-prem deployment
What we build
Six capabilities for production AI systems
Enterprise RAG, document intelligence, deterministic workflows, backend engineering, evaluation, and legacy modernization — delivered as one connected execution layer, not separate service lines.
Enterprise RAG & Hybrid Search
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.
Document Intelligence & Structured Extraction
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.
Deterministic AI Workflow Orchestration
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.
AI Backend Engineering
Production APIs, databases, queues, storage, authentication, monitoring, cost controls, and integrations — FastAPI, PostgreSQL, Qdrant/pgvector, Redis, Docker, background jobs, observability, and secure deployment.
Evaluation, Guardrails & Auditability
Evaluation pipelines, regression tests, guardrails, audit logs, and quality dashboards. Faithfulness, context recall, answer relevance, hallucination checks, prompt injection controls, and sensitive data protection.
Legacy System AI Modernization
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.
Selected work
Selected AI Systems and Modernization Labs
Our work focuses on practical AI infrastructure: document intelligence, workflow automation, legacy modernization, and operator-grade internal tools.
Internal Platform / Proof-of-Confidence Lab
TenderScope — AI-Assisted Procurement Intelligence
Ingests public procurement opportunities, ranks them deterministically, and uses AI for summaries, readiness checks, deadline intelligence, alerts, and operator workflows.
Read case studyInternal Platform / Reference ArchitectureJuristi — Legal RAG & Structured Legal Extraction
A legal document intelligence system for retrieval, structured extraction, and citation-grounded answers from Albanian/Kosovo legal material.
Read case studyModernization Lab / Proof-of-Confidence EnvironmentSIGTAS Modernization Lab — Legacy Tax-System Modernization
A proof-of-confidence lab for exploring phased modernization of legacy tax administration systems. Demonstrates shadow architecture, Oracle-to-modern-core integration patterns, comparison layers, audit logs, and low-risk modernization methods. This is a modernization lab, not a claim of full production SIGTAS compatibility.
Read case studyInternal Platform / Product ArchitectureOperanto — AI Operations & Agent Workflow Platform
A chat-first operations platform for AI-assisted workflows, task routing, SOPs, inbox management, approvals, and execution tracking.
Read case studyLive Production System / Proof-of-Confidence LabNagelista — AI-Assisted Personalized E-Commerce Workflow
Uses customer photos and AI-assisted analysis to support product personalization, order flow, customer communication, and operational automation.
Read case studySome case studies are internal platforms, reference architectures, or proof-of-confidence labs. They demonstrate engineering capability, domain understanding, and implementation approach without implying confidential client work.
How we work
From Prototype to Production
A bounded, evaluation-driven path from a first conversation to a system your operators rely on every day.
- 01
Discovery & System Mapping
We map data sources, workflows, users, risks, and integration points.
- 02
Architecture & Proof of Confidence
We design a bounded architecture and validate it with real documents, real queries, and measurable evaluation criteria.
- 03
Build & Integrate
We implement APIs, retrieval pipelines, workflow logic, databases, and integrations with existing systems.
- 04
Evaluate & Harden
We test retrieval quality, hallucination risk, permissions, latency, cost, and operational reliability.
- 05
Deploy & Improve
We support deployment, monitoring, iteration, and controlled expansion into additional workflows.
Technology
Production-Oriented AI Stack
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.
- Python
- FastAPI
- PostgreSQL
- pgvector
- Qdrant
- Redis
- Docker
- Next.js
- TypeScript
- LangGraph
- OpenAI / Anthropic / local LLMs
- Docling / LlamaParse
- RAGAS / TruLens
- MCP
- REST APIs
- Webhook integrations
- Observability tools
Why Inovativi
Why Teams Work With Inovativi
What buyers consistently get from working with a small, senior-led team that ships production AI systems.
Messy data, messy systems
We understand enterprise documents and legacy systems as they actually exist — PDFs without structure, tables in scans, applications without APIs.
Backend + AI in one team
We combine backend engineering with AI workflow design, so the same team owns retrieval, orchestration, integrations, and the APIs underneath.
Auditability and human control
We design for evaluation, approval flows, and clear audit logs. AI proposes, humans confirm where it matters, and every step is recorded.
Start with a proof of confidence
A bounded first engagement validates the architecture on real data and real queries, with measurable evaluation criteria before scope expands.
Technically accountable delivery
Hands-on technical leadership stays close to architecture and implementation throughout the engagement — no hand-offs to a sales layer.
Next step
Build a Reliable AI System Around Your Documents, Data, or Workflow
Whether you need enterprise RAG, document extraction, workflow automation, or legacy system AI integration, Inovativi can help design and build a production-ready backend.