Iris.ai Tech Stack

AI development platform for production agentic RAG systems

Software Development Norway 11–50 employees Founded 2015 Privately Held

Iris.ai builds infrastructure for enterprises moving agentic RAG systems from prototype to production. The stack—Python, Django, PostgreSQL, Elasticsearch, PyTorch, Transformers, and orchestration via Kubernetes and Terraform—reflects a focus on data preparation, LLM evaluation, and secure deployment across on-premise and cloud environments. Hiring is senior-heavy (4 of 5 roles) and decelerating, while active projects center on agent reasoning, RAG pipelines, and LLM evaluation frameworks. The pain-point stack (scaling expert knowledge, evaluating LLM uncertainty, transitioning sales motion) signals a transition from R&D-led founder sales toward repeatable enterprise processes.

Tech Stack 27 technologies

Core StackPython Django PostgreSQL Elasticsearch Couchbase PyTorch AWS Cursor Kubernetes Docker Terraform TensorFlow Hugging Face OpenAI OpenSearch Chroma Gensim Transformers spaCy AutoGen Windsurf Amazon Q Claude Git Flowise GCP Azure

What Iris.ai Is Building

◆Challenges

Scaling next phase of growth
Transitioning sales motion to scalable processes
Accelerating enterprise adoption
Accelerating value generation
Scaling expert-level domain knowledge
Building trustworthy ai systems
Evaluating llm uncertainty

▲Active Projects

Ai agents
Rag pipelines
Llm evaluation frameworks
Global go-to-market strategy
Sales playbooks development
Partnership model with support demand
Design end-to-end agentic solutions
Rapid prototyping of ai agent proof-of-concepts
Llm evaluation & uncertainty
Agentic reasoning & control

Hiring Activity

Decelerating5 roles · 1 in 30d

Department

Engineering

Research

Sales

Seniority

Senior

Principal

Notable leadership hires: Tech Lead

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About Iris.ai

Iris.ai provides a platform for building and operating agentic RAG systems in regulated enterprise environments. The product includes data transformation tools (Neuralith, Axion) and evaluation frameworks (RSpace) that connect internal and external data sources, orchestrate domain-specific agents, and measure LLM performance across 30+ metrics. Deployment options span on-premise, cloud, and hybrid architectures with ISO27001 certification and privacy-by-design governance. The company serves manufacturing, telecom, public sector, and R&D organizations; customers operate at scale—Iris.ai has processed over 160M documents internally and reports 35%+ LLM cost reductions and up to 80% acceleration in AI deployment timelines for clients.

HeadquartersNorway

Company Size11–50 employees

Founded2015

Hiring MarketsBelgium

Frequently Asked Questions

What tech stack does Iris.ai use?

Iris.ai uses Python, Django, PostgreSQL, Elasticsearch, PyTorch, Transformers, and Kubernetes for orchestration. The platform integrates with AWS, GCP, Azure, and includes LLM integrations with OpenAI and Hugging Face models.

What countries does Iris.ai hire in?

Iris.ai is hiring in Belgium. Current open roles span engineering (3), research (1), and sales (1), with a focus on senior and principal-level positions.

What is Iris.ai working on?

Active projects include agentic AI systems, RAG pipelines, LLM evaluation frameworks, end-to-end agentic solution design, and a global go-to-market strategy with sales playbooks development.