AIMEC / AI implementation + infrastructure

AI Engineering. Agent Infrastructure. Automation.

AIMEC builds production AI systems for businesses and develops the technical infrastructure, tools and experiments shaping the agentic workforce.

01 / AIMEC SOLUTIONS

AI that has to work inside a real business.

We design and implement agents, automation, retrieval systems, private AI and custom applications around your data, workflows, permissions and commercial objectives.

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02 / AIMEC LABS

The infrastructure behind the agentic workforce.

Our R&D work explores local agents, secure agent networks, world models, evaluation systems and practical tools for the transition from chat interfaces to autonomous execution.

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What we build

From one useful workflow to an operating layer for AI.

AIMEC focuses on the integration layer between powerful models and the messy reality of business systems.

01 / ENGINEERING

Custom AI systems

Production applications, APIs, retrieval, model integration and AI-native backend architecture.

02 / AGENTS

Agentic systems

Tool use, memory, human approval, multi-agent coordination and persistent AI workers.

03 / AUTOMATION

Intelligent workflows

Python, n8n and API-driven systems that remove repetitive work and connect operational data.

04 / PRIVATE AI

Local & controlled AI

Ollama, llama.cpp and private architectures for teams that need tighter control over data and inference.

Built at AIMEC

Proof should look like a system, not a promise.

LOCAL AGENTS

Local Agent Harness

A privacy-first runtime combining local inference, memory, retrieval and controlled tool execution.

AGENT NETWORKS

Private Agent Network

Secure agent discovery and delegation with encrypted boundaries and metadata-minimal administration.

WORLD MODELS

AI SEO Monitoring Infrastructure

Search, analytics and crawl data organized so an agent can reason about change and call the right diagnostic tools.

Technologies we build with

We choose tools by architecture, not affiliation.

These are technologies AIMEC uses, evaluates or writes about. They should not be read as formal partner endorsements.

ModelsQwen, OpenAI models and other fit-for-purpose model layers.
Agent infrastructureMCP, A2A, LangGraph, CrewAI, OpenAI Agents SDK.
Local / private AIOllama, llama.cpp and self-hosted deployment patterns.
Automationn8n, Python, APIs and event-driven workflows.
Data & retrievalVector search, structured memory, analytics and knowledge systems.
Technology references indicate hands-on use, evaluation or editorial coverage unless a formal partnership is explicitly stated.
Technology partnerships

Building something developers or businesses need to understand by using it?

AIMEC works with model providers, infrastructure teams, open-source projects and enterprise technology vendors on integrations, reference implementations, evaluations and technical content.

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