AI Engineering
We integrate AI as a working feature, not a demo. From RAG pipelines and conversational agents to ML inference and LLM orchestration, built to run in production.
Concevoir des interfaces que les utilisateurs adorent.
Project Overview
AI engineering at Epioso is about outcomes, not experiments. We take proven LLM capabilities and wire them into real business flows: support agents, document processing, automated content, clinical decision support.
What We Deliver
- Production AI Systems
RAG pipelines, agentic workflows, and LLM integrations built to run reliably at scale.
- Custom Model Pipelines
Fine-tuning, embedding generation, and ML inference pipelines.
- Automation Workflows
n8n and Python-based automation connecting AI outputs to real business actions.
How We Build AI Systems
Use Case Definition
/001Define the exact business problem and success metrics before selecting any model.
Data & Context Design
/002Design the knowledge base, embedding strategy, and retrieval logic.
Build & Orchestrate
/003Implement the full pipeline: model calls, tool use, memory, guardrails, and fallback logic.
Evaluate & Harden
/004Test with real inputs, measure accuracy and cost, harden against edge cases.
Autres Services
Branding & Digital Identity
Logos, brand guidelines, and digital presence. We make businesses look like they mean it.
Healthcare Technology
Clinical-grade systems, patient platforms, and AI tools with medical domain knowledge.
Systems & Backend Engineering
APIs, databases, architecture, and data pipelines. We think in systems, not features.
Business Automation
Replace manual processes with n8n, Python, and RPA. 60%+ time savings.
// EPIOSO
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GitHub
gloxossBasé à
Casablanca, Morocco
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