Technology Stack
The platforms we build on.
Darius and the AIDARIUS team do not recommend AI platforms they have not used in production. Every tool below is one we have deployed with real clients — and understand well enough to tell you when not to use it.
Core platforms
Five ecosystems. Deep expertise.
These are the platforms Darius trains clients on, integrates into business workflows, and draws on when designing AI strategy. Each one is evaluated independently — the goal is always fit, not loyalty to a vendor.
Enterprise AI
Microsoft
Microsoft is the dominant AI platform for organisations already running on Microsoft 365. Darius delivers in-depth Copilot training, Copilot Studio deployments, and Azure AI integrations — helping teams move from basic prompting to genuine productivity transformation. With 25+ years in IT, Microsoft's enterprise ecosystem is the environment Darius knows deepest.
Engagements span readiness assessments, end-user training programmes, governance frameworks under the EU AI Act, and custom Copilot agent builds via Copilot Studio. For organisations with a Microsoft licensing agreement already in place, this is typically the highest-ROI first move in an AI adoption programme.
AI Assistant & API
Anthropic — Claude
Claude is Darius's primary AI assistant for strategic work, content development, and complex reasoning tasks. As a Claude power user and trainer, Darius helps organisations adopt Claude for knowledge work, document processing, and internal AI agent builds. Claude's strong safety and reasoning profile makes it well-suited for regulated industries and governance-conscious clients.
Generative AI
OpenAI
OpenAI's GPT-4o and o-series models remain the market standard for generative AI benchmarks and the most widely recognised platform in client organisations. Darius uses OpenAI across training programmes, custom GPT builds, and API-based automations — and teaches teams how to evaluate its output critically rather than accept it uncritically.
AI Ecosystem
Google — Gemini
For organisations running Google Workspace, Gemini represents the most natural AI entry point. Darius trains teams on Gemini for Workspace — Docs, Gmail, Meet, Sheets — and advises on Vertex AI deployments for more advanced use cases. Google's multimodal strength makes it particularly relevant for content-heavy and marketing-led organisations.
AI Infrastructure
Nvidia
Nvidia underpins the compute layer of modern AI — from cloud inference to on-premise deployments. Darius advises clients on AI infrastructure decisions, NIM microservice deployments, and how to evaluate GPU-backed platforms for privacy-sensitive or high-volume workloads. For organisations considering local AI deployments, Nvidia's ecosystem is the starting point for architecture discussions.
Open source
Open-source models & frameworks.
Proprietary APIs are not the only answer. For privacy-sensitive workloads, local deployments, or clients who want full data sovereignty, open-source models and frameworks are first-class options.
Open-Source LLM
Meta Llama
Meta's Llama family (3.1, 3.2, 3.3) provides enterprise-quality open-weight models that can run fully on-premise. Darius advises clients on Llama deployments where data cannot leave the organisation — legal, finance, HR, and regulated industries. Llama 3.3 70B delivers near-frontier performance at a fraction of the inference cost.
European Open LLM
Mistral AI
Mistral's models — including Mistral Small, Mistral Large, and Mixtral MoE — offer strong performance with European data residency options, making them well suited for EU-based organisations with GDPR concerns. Darius recommends Mistral for clients who need capable open models without relying on US infrastructure.
Local Model Runner
Ollama
Ollama makes running open-weight models locally as simple as a single terminal command. For workshops, demos, and proof-of-concept environments, Darius uses Ollama to show clients exactly what on-device AI looks like — no API keys, no cloud costs, no data leaving the machine. A practical introduction to local AI for technical and non-technical audiences alike.
Model Hub & Ecosystem
Hugging Face
Hugging Face is the de facto hub for open-source AI models, datasets, and tools. Darius uses it for model evaluation, fine-tuning workflows, and Spaces demos. For clients evaluating which open-source model fits a specific task — summarisation, classification, embeddings — Hugging Face is the reference point for benchmarks and reproducible comparisons.
Agent Framework
LangChain & LangGraph
LangChain is the most widely used framework for building LLM-powered applications and agents. LangGraph extends it to stateful, multi-step agent workflows with human-in-the-loop control. Darius uses both when designing AI agent architectures for clients — from simple RAG pipelines to complex multi-agent orchestration.
For organisations moving beyond basic prompting into AI-powered automation — document processing pipelines, research assistants, internal knowledge bots — LangChain and LangGraph provide the scaffolding. Combined with open-source models, they enable fully private, fully controlled AI systems with no vendor lock-in.
Our approach
Vendor-neutral. Results-first.
AIDARIUS has no obligation to any AI vendor. Every recommendation starts with your organisation's actual needs, infrastructure, and team capacity — not a preferred product.
Platform-fit assessment
Before recommending any platform, we evaluate your existing tech stack, licensing, data residency requirements, and team skill level. The best AI tool is the one your team will actually use.
Governance from day one
Every deployment includes usage policy, data handling guidelines, and EU AI Act compliance considerations — not as an afterthought, but as part of the initial design.
Measured outcomes
Adoption metrics, time-saved benchmarks, and skill assessments are built into every programme. If we cannot measure it, we have not solved it.
Work with us
Not sure which platform fits your team?
A 90-minute AI Strategy Session maps your organisation's needs to the right tools — with no vendor agenda.