Simam Digital

Our work focuses particularly on AI that can understand data, reason about physical environments, use tools and assist people inside complex operational workflows.

🧪 What We're Exploring

Agentic Infrastructure

Reusable AI agents and orchestration systems for engineering, construction, infrastructure, public services and enterprise workflows.

Spatial Intelligence

AI systems capable of reasoning across Gaussian Splats, GIS, BIM, maps, Digital Twins, imagery and real-world environments.

Autonomous Workflows

Multi-stage systems combining models, tools, agents, APIs and human approval to produce useful operational outputs.

Local Intelligence

Private and on-premise AI using open models for organisations that need greater control over their data, infrastructure and inference.

Human + AI Interfaces

Exploring how voice, vision, XR, spatial computing and intelligent interfaces change the way people interact with AI.

🤗 AI Model Playground

We use Hugging Face to make emerging AI research easier to explore.

Our Spaces include simple interfaces for experimenting with:

Large Language Models
Vision Language Models
OCR & document intelligence
Image understanding
Object detection & segmentation
Embedding models
Local and open-source LLMs
AI agents
Retrieval and RAG
Generative image & video models
Spatial AI experiments

The goal is simple:

Make powerful AI research accessible without requiring users to understand Python, CUDA, inference servers or model deployment.

🧠 Simam Intelligence Framework

Our applied research follows a simple operating loop:

OBSERVE → UNDERSTAND → REASON → ACT → LEARN → IMPROVE

We combine four practical layers:

01 — Spatial & Data Signals 3DGS · BIM · GIS · imagery · documents · sensors · APIs

02 — Intelligence Vision models · LLMs · multimodal models · agents

03 — Workflows Tools · orchestration · human approval · evaluation

04 — Deployment Cloud · edge · local · on-premise

Models are selected around the problem — not the other way around.

🔬 Current Research

Some of our active research areas include:

AI Construction Assistant Spatial agents navigating Gaussian Splat construction environments for inspection, safety and progress analysis.

Local AI for SMEs Privacy-preserving local language and vision models for organisations working with sensitive information.

XR AI Training Vision, voice and spatial agents operating inside immersive industrial training environments.

Infrastructure Intelligence Combining mapping, Digital Twins, operational data and AI agents to create queryable infrastructure systems.

Agentic Workflows Research into visual, secure and human-supervised agent orchestration for non-technical users.

🧩 Simam Agent Studio

We are developing a visual Applied Intelligence platform for creating AI agents and multi-stage workflows without requiring traditional AI development.

Think:

INPUT → MODEL → REASON → TOOL → APPROVAL → ACTION

Our research explores:

Visual agent orchestration
Model-independent workflows
Bring-your-own-model / bring-your-own-key
MCP and external tools
Human approval gates
Agent evaluation
Local model execution
Multi-agent systems
Industry-specific Agent Blueprints

📊 Models & Benchmarks

Not every AI model is right for every problem.

We experiment with open models and publish practical observations around:

reasoning quality
vision performance
document understanding
latency
hardware requirements
inference cost
privacy
local deployment
agent/tool performance
industry suitability

Where useful, experiments will be released as Spaces, datasets, benchmarks or Research Notes.

🛰 Applied Spatial Intelligence

A major focus of the Lab is exploring what happens when AI begins to understand the physical world, not only text.

We research combinations of:

AI + GIS + 3DGS + BIM + Digital Twins + Computer Vision + XR

Our long-term goal is to create intelligent systems capable of understanding complex physical environments and helping people inspect, navigate, simulate, query and operate them using natural interfaces.

🤝 Research & Collaboration

We are interested in collaborating with:

AI researchers
Open-source developers
Universities
SMEs
Infrastructure organisations
Engineering teams
Public-sector organisations
AI model developers
Research funders
Technology partners

We are particularly interested in applied research where an emerging AI capability can be tested against a real operational problem.

Build With Us

Have a model, dataset, research idea or real-world problem worth exploring?

We're open to:

Research collaborations · Model evaluations · Dataset projects · Industry pilots · Agent experiments · Spatial AI research · Open-source projects

🌐 Simam AI Lab: lab.simamdigital.com 🏢 Simam Digital: simamdigital.com 💻 GitHub: github.com/Simam-Digital-Ltd 📍 Wakefield, United Kingdom

Research → Prototype → Evidence → Product

Simam AI Lab Applied intelligence for the physical world.

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