Oneiros AI

Enterprise AI That Actually Works in Production.

From agentic workflows and retrieval-augmented generation to fine-tuned domain models and AI-native application platforms — Oneiros builds AI that delivers measurable outcomes, not prototypes.

We engineer production-ready AI systems on the world's leading foundation models. Every deployment is observable, governed, and continuously improved — so your AI gets smarter over time.

Explore AI CapabilitiesTalk to an AI Engineer
AI Engineering Depth

AI Is Not a Feature. It's an Engineering Discipline.

Oneiros approaches AI the way great engineering teams approach infrastructure — with rigour, observability, and a relentless focus on reliability in production environments.

200B+
Tokens processed monthly in production
15ms
Median AI inference latency (p50)
40+
Production AI systems delivered
94%
Average RAG retrieval accuracy on enterprise data

AI Readiness Assessment

Before building, we audit your data quality, existing systems, and business processes to identify where AI will drive the highest value — and what's blocking you from getting there.

Architecture Before Code

We design your AI architecture end-to-end: model selection, RAG pipelines, agent topology, embedding strategy, latency targets, and governance framework — all before writing line one.

Build for Production Reliability

No Jupyter notebook demos. Every AI system we build is containerised, instrumented for observability, tested against adversarial inputs, and deployed with a rollback strategy from day one.

Continuous AI Improvement

AI models drift. We monitor output quality, collect feedback signals, and run continuous fine-tuning and prompt improvement cycles — so your AI compounds in value over time.

AI Use Cases

Six AI Capabilities. Real Business Impact.

Each capability is a production-proven AI pattern — engineered at depth using the latest foundation models, frameworks, and infrastructure to deliver reliable, measurable outcomes.

Agentic AI

Agentic AI & Autonomous Workflows

AI that plans, acts, and adapts — without constant human prompting

Deploy multi-agent systems that autonomously break down complex tasks, call tools, query databases, and coordinate sub-agents to completion. Built on LangGraph, CrewAI, and custom orchestration frameworks — fully observable and auditable.

  • Multi-agent task orchestration (LangGraph / CrewAI)
  • Tool-calling agents with real-time API access
  • Human-in-the-loop approval gates
  • Persistent agent memory across sessions
Explore CapabilityAI Pattern
RAG & Knowledge

Retrieval-Augmented Generation (RAG)

Ground your AI in your enterprise knowledge — not hallucinated answers

Enterprise-grade RAG pipelines that combine semantic search, structured retrieval, and hybrid ranking to give your LLMs accurate, contextual, and up-to-date information from your own data sources.

  • Hybrid semantic + keyword retrieval
  • Multi-modal document ingestion (PDF, Word, images)
  • Vector store management (Pinecone, Weaviate, pgvector)
  • Re-ranker models for retrieval precision
Explore CapabilityAI Pattern
AI Copilots

Conversational AI & Business Copilots

Intelligent assistants embedded directly in your workflows and apps

AI copilots that understand your domain, interact naturally, escalate to humans when needed, and improve with every conversation. From customer-facing virtual agents to internal operations assistants — built secure and context-aware.

  • Domain-specific LLM fine-tuning
  • Omnichannel deployment (web, mobile, Teams, Slack)
  • Session context & long-term memory
  • Sentiment detection & escalation routing
Explore CapabilityAI Pattern
Document AI

Computer Vision & Document Intelligence

Extract, classify, and understand any document or image at scale

Transform unstructured documents — invoices, contracts, forms, inspection images, engineering drawings — into structured, actionable data. Combining OCR, vision models, and LLM reasoning for extraction accuracy above 97%.

  • Intelligent OCR with layout understanding
  • Contract clause extraction & comparison
  • Invoice & PO automated processing
  • Visual inspection & defect detection
Explore CapabilityAI Pattern
Predictive ML

Predictive Analytics & Decision Intelligence

ML models that tell you what will happen — before it does

End-to-end ML pipelines for demand forecasting, churn prediction, anomaly detection, and dynamic pricing. Feature engineering, model training, validation, and production deployment with continuous drift monitoring.

  • Demand forecasting & inventory optimisation
  • Customer churn & lifetime value prediction
  • Real-time anomaly detection
  • Dynamic pricing & revenue optimisation
Explore CapabilityAI Pattern
LLM Engineering

LLM Fine-Tuning & AI-Native Applications

Custom models trained on your data, powering your AI applications

Fine-tuned domain models using LoRA, QLoRA, and full fine-tuning on proprietary datasets. Build AI-native applications where LLMs are the core runtime — not a bolt-on feature — with structured outputs, tool use, and JSON-mode APIs.

  • LoRA / QLoRA fine-tuning on domain data
  • Structured output & function-calling APIs
  • Model evaluation & benchmark frameworks
  • Serving infrastructure (vLLM, TGI, Ollama)
Explore CapabilityAI Pattern
Technology Stack

Best-of-Breed Models. Model-Agnostic by Design.

We select the right foundation model for each workload — not one vendor for everything. Your AI stack stays portable, cost-optimised, and always running the best model available.

GPT-4o
OpenAI
MultimodalFunction Calling128k Context
Claude 3.7
Anthropic
200k ContextReasoningCode
Gemini 2.0 Flash
Google DeepMind
MultimodalReal-timeFast
Llama 3.3 70B
Meta AI
Open-weightSelf-hostedFine-tunable
Mistral Large 2
Mistral AI
EU-hosted128k ContextMultilingual
o3 / o4-mini
OpenAI Reasoning
Chain-of-ThoughtSTEMComplex Reasoning
Orchestration
  • LangChain
  • LangGraph
  • LlamaIndex
  • CrewAI
  • Haystack 2.0
Vector Stores
  • Pinecone
  • Weaviate
  • Qdrant
  • pgvector
  • Redis VSS
Cloud AI
  • Azure OpenAI
  • AWS Bedrock
  • GCP Vertex AI
  • Cloudflare AI
MLOps
  • MLflow
  • Weights & Biases
  • Seldon Core
  • BentoML
  • Arize AI
Delivery Methodology

From Discovery to Production in Five Steps.

Every Oneiros AI engagement follows a structured, repeatable process — designed to move fast without cutting corners on reliability or governance.

01

Discovery & Data Audit

We start with your data — not your wishlist. A structured audit of data sources, quality, volume, and accessibility determines what AI can realistically achieve and what needs to be fixed first.

AI Readiness Report
02

Solution Architecture Design

We design the complete AI system: model selection, pipeline topology, latency budgets, embedding strategy, RAG architecture, agent design, and the governance and observability framework.

AI Architecture Blueprint
03

Data Engineering & Ingestion

Build the data pipelines that feed your AI: document ingestion, chunking strategies, embedding generation, vector store population, and structured data connectors — all optimised for retrieval quality.

Production Data Pipeline
04

Model Build & Fine-Tuning

Prompt engineering, few-shot design, and fine-tuning on your domain data where needed. Evaluation against task-specific benchmarks, adversarial testing, and hallucination mitigation before any production deployment.

Validated AI Model
05

Production Deployment & MLOps

Containerised AI services, CI/CD for model updates, A/B testing infrastructure, latency monitoring, output quality tracking, and feedback loops wired into your product — ready for scale from day one.

Live AI System + Runbook
Responsible AI

Trustworthy AI. Not Just Powerful AI.

Enterprise AI must be safe, explainable, and governed. We embed responsible AI practices into every system we build — not as compliance theatre, but as engineering discipline.

Responsible AI by Default

Every AI system we build includes bias evaluation, fairness assessments, and output quality testing before deployment. We follow NIST AI RMF and EU AI Act alignment principles as standard practice.

  • Bias & fairness evaluation
  • EU AI Act alignment
  • NIST AI RMF compliance

Explainable & Observable AI

Black-box AI is a risk, not a feature. We instrument every model with output tracing, token-level attribution, confidence scoring, and reasoning chains — so you always know why the AI said what it said.

  • Output tracing & attribution
  • Confidence scoring
  • Audit-ready reasoning chains

Data Privacy & Security

Your data never trains foundation models without explicit consent. We enforce data residency requirements, end-to-end encryption, PII redaction pipelines, and zero-trust access controls on all AI infrastructure.

  • No data used for model training
  • PII redaction pipelines
  • End-to-end encryption & RBAC

Human Oversight & Control

AI augments human decision-making — it doesn't replace governance. Every high-stakes AI workflow includes human-in-the-loop gates, override mechanisms, and clear escalation paths.

  • Human-in-the-loop gates
  • Override & rollback controls
  • Clear accountability chains

Compliance & Certification

AI deployments aligned with industry regulations and certification standards. From healthcare data handling (HIPAA, HL7) to financial services (FCA, GDPR) and public sector AI governance frameworks.

  • GDPR-aligned AI processing
  • HIPAA & financial services ready
  • Regulatory audit trails

Continuous Model Governance

Models degrade, data drifts, and the world changes. Our MLOps framework monitors output quality continuously, triggers automated retraining pipelines, and alerts on distribution shift before it impacts your users.

  • Automated drift detection
  • Continuous retraining pipelines
  • Quality degradation alerting
Start with AI

Your AI Advantage Starts with the Right Partner.

Stop experimenting. Start shipping AI that matters. Tell us your challenge — we'll bring the expertise, the models, and the delivery rigour to make it production-ready.

Start the ConversationExplore Capabilities

AI Proof of Concept

A focused 2–4 week sprint to prove AI value on a real business problem — with working code, benchmark results, and a clear path to production.

Start a PoC

Production AI Build

End-to-end delivery of a production-grade AI system — from architecture and data pipelines through model training, deployment, and MLOps setup.

Brief us on your project

AI Strategy & Advisory

A senior AI architect working alongside your team to define your AI roadmap, evaluate vendor options, and build internal capability — without the overhead of a full programme.

Book an advisory session