Founder-led engineering ownership
The founder combines software, business, and advanced data science training, and stays close to every engagement. No account-manager layers, no hand-off chains.
For AI product, platform, and enterprise teams
Production AI Infrastructure for Real Business Workflows
Inovativi builds AI backends, RAG systems, agent workflows, and enterprise integrations that connect data, legacy systems, and human operations — securely, observably, and production-ready.
We build the backend infrastructure that makes AI useful in real operations.
Founder-led, EU-based, CET-aligned engineering team for European, Swiss, UK, and US clients.
Python · FastAPI · MCP · OpenAPI · PostgreSQL · Vector Databases · Docker · Terraform · Cloud/On-Prem Deployment · Observability
Senior nearshore engineers for DACH, Swiss, EU & UK teams
Python, FastAPI, MCP, vector databases & cloud-agnostic integrations
Individual engineers, small pods, or fixed-scope project delivery
From AI prototypes to production-grade infrastructure
What we build
Production AI infrastructure for real business workflows
Six capabilities that cover the work between an AI prototype and a system your operators actually use every day.
AI Backend Engineering
Production Python/FastAPI services, APIs, queues, workers, and execution layers for AI products and platforms.
Enterprise RAG & Document Intelligence
Document ingestion, OCR/parsing, embeddings, vector databases, hybrid search, citation-grounded answers, structured extraction, permission-aware retrieval, and LlamaIndex/LangChain-style RAG pipelines where appropriate.
AI Agents & Workflow Automation
MCP/OpenAPI tool interfaces, LangGraph/LangChain workflows where useful, custom orchestration where needed, human approval flows, retries, logging, task execution, and business workflow automation.
Legacy System AI Modernization
API layers, integration wrappers, shadow systems, reporting layers, and gradual modernization for legacy platforms.
Observability, Evaluation & Governance
Monitoring, logs, audit trails, cost tracking, evaluation loops, permission control, and production-readiness checks.
Custom Enterprise Integrations
CRM, ERP, email, WhatsApp, portals, databases, GIS, Databricks, cloud services, private infrastructure, and internal business systems.
The production gap
Most teams have AI prototypes. Few have them in production.
A working demo is not a working system. To run in production, AI agents need real integrations, APIs, security, monitoring, and execution workflows. That backend layer is exactly what we build.
- AI agents need governed access to real systems, not just prompts and replies.
- Prototypes stall because integrations, APIs, and execution workflows are missing.
- Production agents require permissions, retries, logging, and monitoring to be trusted.
- Databricks and Azure platforms need production-grade services built around them.
How it fits together
A controlled path from AI agents to enterprise systems
AI agents need a controlled path to enterprise systems. Inovativi builds the backend layer that validates requests, exposes reusable tools, triggers workflows, connects data platforms, and records every action for reliability and auditability.
AI Agent / AI Platform
LLM apps, copilots, agent frameworks
MCP / OpenAPI Tool Interface
Reusable tools and typed contracts
Secure Execution Layer
Validation, permissions, audit
Python Backend APIs
FastAPI services and business logic
Queue / Event Bus
Async processing, retries, dead-letter
Cloud / Data Platforms / Enterprise Systems
AWS, Azure, GCP, Databricks, ERP, CRM, GIS
Monitoring / Audit Logs / Error Handling
Observability and reliability
Selected work
Reference architectures and platforms we have built
Some 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.
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 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 studyWhy Kosovo / Why Inovativi
Nearshore efficiency with senior engineering ownership
A European time zone, English-fluent engineers, flexible team setup, and a backend-and-integration mindset — led by a founder with a software and business background and advanced data science training.
Backend & integration depth
We focus on the execution layer — APIs, data platforms, queues, observability, and reliability — not generic dev capacity or chatbot wrappers.
European time-zone alignment
Based in Kosovo, in Central European Time. Stand-ups, reviews, and decisions happen inside your working day, not after it.
English-fluent delivery
Clear English across calls, documentation, code reviews, and written updates. German available on request.
Flexible team setup
Start with one senior engineer and scale into a small pod, or assemble a project team around a defined outcome.
Sustainable EU economics
Senior EU nearshore engineering at rates that work over the full arc of a project, without the markup of a London or Zurich consultancy.
Markets we focus
Nearshore AI Infrastructure for DACH, EU & Selective US Clients
German, Austrian, and Swiss companies are our primary focus. We also serve the wider EU and selective US clients — but our timezone, rates, and delivery model are optimized for DACH.
DACH — Germany, Austria, Switzerland
- CET timezone alignment — same working day
- Nearshore cost advantage vs. local German/Swiss engineers
- EU AI Act & GDPR compliance ready
- German business culture understood (English or German communication)
- Target: Berlin, Munich, Zurich, Vienna
Wider EU — UK, Benelux, Nordics
- 1 hour timezone difference max
- English-first communication
- Lower competition than DACH
- Target: London, Amsterdam, Stockholm
United States
- Remote-first collaboration (asynchronous)
- High-value, selective engagements only
- Inbound or referral
- Target: startups and SaaS (not enterprises)
For DACH and EU clients: we operate on CET, offer standard NDA and GDPR alignment, and are available for occasional onsite meetings in Zurich, Munich, Berlin, and Vienna.
Based in DACH? Let's talk about your AI infrastructure needs.
Discuss a ProjectWhere we're the right partner
We do better work when expectations align upfront
Honest about fit, both ways. Here is how we think about an engagement before either of us commits.
- AI prototypes that need to become real production systems
- Enterprise teams adding RAG, agents, or AI-assisted workflows
- Legacy systems that need API and AI integration layers
- Buyers who value engineering ownership over hourly bodies
- Engagements with a defined outcome — from a 2-week Integration Sprint upward
- Pure chatbot or prompt-engineering-only work
- Hourly staff augmentation with no defined outcome
- Projects requiring more than ~25% on-site presence
- Procurement processes ranked purely on lowest bid
Cloud-agnostic · Deployment-aware · Enterprise-ready
Built for cloud, hybrid, and on-prem
We design AI infrastructure for cloud, hybrid, and on-prem environments. Depending on client requirements, systems can be deployed on AWS, Azure, Google Cloud, private cloud, EU-hosted infrastructure, or self-managed environments.
- Python
- FastAPI
- OpenAPI
- MCP
- PostgreSQL
- Vector Databases
- LangChain
- LangGraph
- LlamaIndex
- AWS
- Azure
- Google Cloud
- Databricks
- PySpark
- Delta Lake
- MLflow
- Docker
- Terraform
- CI/CD
- Observability
Next step
Bring AI into your real business workflows.
Tell us the project or role. We respond with a fixed-scope plan, individual engineers, or a small nearshore pod for Python, AI, RAG, agents, MCP, cloud and data-platform integration, and enterprise systems.
Founder-read inbox. Reply within 1 business day. First call: 30 minutes, scoping only — no pitch.