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EPIOSO
Applied Intelligence

AI Engineering & Intelligent Systems

We build production AI systems designed for actual enterprise workflows, not fragile demos. From high-throughput vector retrieval and cognitive agent orchestration to custom model fine-tuning and inference pipelines, we engineer reliable intelligence directly into your core product architecture.

AI Engineering & Intelligent Systems

Building interfaces that people love to use.

Strategic AI Architecture & Integration

AI engineering at EPIOSO is driven by verifiable performance, not speculative experiments. We transform frontier foundation models and custom architectures into resilient production systems: low-latency agent loops, zero-hallucination knowledge retrieval, autonomous document pipelines, and clinical-grade decision support.

Core Deliverables & Capabilities

  • Production RAG & Knowledge Retrieval

    Hybrid search architectures, dynamic reranking, and semantic vector stores engineered for deterministic accuracy and zero hallucination over massive proprietary datasets.

  • Autonomous Cognitive Agents

    Multi-agent orchestration frameworks equipped with state persistence, structured function calling, and strict human-in-the-loop controls for complex operations.

  • Custom Model Alignment & Inference

    Domain-specific fine-tuning (LoRA/QLoRA), specialized embeddings, and optimized inference serving built for predictable throughput and low latency.

AI Engineering Methodology

Domain Framing & Model Selection

/001

We formalize system boundaries, evaluation benchmarks, and latency targets before selecting proprietary models or open weights.

Vector Architecture & Context Design

/002

We structure semantic chunking strategies, dense-sparse embedding pipelines, and deterministic metadata filters for hybrid retrieval.

Agent Orchestration & Deterministic Controls

/003

We implement function calling contracts, state machines, structured JSON outputs, and strict guardrails to prevent hallucinations.

Benchmarking, Evals & Hardening

/004

We stress-test pipelines against synthetic failure datasets, optimize token economics, and establish automated LLM-as-a-judge evals.

AI Engineering Methodology
<1.2s
Optimized End-to-End Inference Latency
Zero
Tolerance for Unvalidated Hallucinations
Production
Autonomous Agents with Deterministic Safeguards

EPIOSO

What's your business called?

Prefer direct?

LinkedIn

Oussama Zaki

GitHub

gloxoss

Based in

Casablanca, Morocco

We reply within 24 hours.