ai.ro logo
AI Research & Engineering Lab

Applied AI Systems

A small research-driven team building knowledge systems, RAG architectures, and agentic workflows.

STATUS: pending MODE: experimental → production-oriented FOCUS: knowledge systems, agents, retrieval SCOPE: demos · architectures · prototypes LOCATION: distributed (Europe)

Explore demos View capabilities

OUR CAPABILITIES

/skills

What we can design and build.

Skill 01

Knowledge Systems

Design graph-based knowledge infrastructures combining documents, structured data, semantic search, and reasoning.

Typical Outputs

  • domain schema / ontology
  • curated knowledge layer
  • queryable knowledge graph
  • graph-aware retrieval surfaces

Used For

research assistants, internal knowledge, technical systems

Stack Cues

entity + relationship modeling document-to-structure extraction provenance + lineage tracking hybrid indexing across sources consistency + drift monitoring

OUR PLAYGROUND

/demos

Two demos we’re building right now. Demo-first, system-level work.

waiting for query input...

Knowledge Graph + RAG

Graph-backed retrieval system combining structured entities, documents, and semantic search to answer complex questions with traceable context.

  • hybrid retrieval (graph + vector)
  • provenance / citations
  • assistant interface on top
executing flow...

Agent Workflow System

Agentic pipeline that plans tasks, calls tools, and produces structured outputs with observability and safety controls.

  • tool use + orchestration
  • task planning
  • logs / run traces

WHAT WE DO

/operating-mode

Early-stage applied AI lab. We research and build knowledge systems, copilots, and automated workflows, partnering with teams shaping ambitious AI infrastructure.

01

Research Collaboration

Joint exploration of new architectures, methods, and system designs.

02

Prototype Sprint

2–6 week focused build of a specific AI system or capability.

03

Advisory

Technical review, system assessment, and architecture guidance.

04

Knowledge System Build

Design and implementation of structured knowledge layers and retrieval surfaces.

05

Internal Copilot Development

Custom assistants for teams, research groups, or technical workflows.

06

Workflow Automation

AI-powered document and knowledge pipelines with traceability and auditability.

WHAT WE BELIEVE IN

/vision

Our long-term direction is practical: build systems that can reason over structured knowledge, execute workflows safely, and remain inspectable under real usage.

Future software will be centered on intelligent knowledge systems and autonomous agents.

We are building toward that future by designing and shipping real systems, incrementally and with clear technical constraints.

01

Grounded by Knowledge

Systems should reason over explicit context, not isolated prompts.

02

Traceable by Default

Decisions, sources, and tool actions should remain inspectable.

03

Shipped Incrementally

Progress comes from real demos, eval loops, and production hardening.

04

Constrained by Design

Autonomy should operate within clear policies, limits, and recovery paths.

OPEN CHANNEL

/contact

If you are exploring knowledge systems, retrieval architecture, or agent workflows, send a short message and we will reply directly by email.

TARGET: contact@ai.ro

MODE: asynchronous

STATUS: listening

0 / 100
0 / 2000