01
Generative & Computational Design
Parametric workflows can compare structural and spatial options against defined cost, performance, and sustainability inputs before a project team selects a direction.
The Spetia Lab
Research &
Development.
We research AI, automation, and reality-capture workflows around defined engineering problems. Any client use is governed by the project inputs, validation method, data rules, human review, and acceptance criteria.
AI-Driven WorkflowsIn-House ProductsDigital Twins
Talk to the Lab→Research Focus
Where we push the edge.
Applied engineering R&D, focused on the problems that slow real projects down and the technology that removes them.
02
AI Scan-to-BIM
Computer-vision experiments assist point-cloud and image classification for reality-capture workflows; model scope, LOD, tolerance, and human validation remain project-specific.
03
Automated Clash Detection
Rules and machine-learning experiments can assist the classification and prioritisation of coordination issues before an engineer reviews the proposed workflow.
04
Workflow Automation & Revit Plugins
In-house plugins and scripts support repetitive modelling, sheet setup, QA, and documentation tasks when they are validated for the project workflow.
05
Digital Twin Intelligence
Digital-twin pilots can connect approved sensor or IoT streams to asset models for operational review, subject to the client platform, data, and security requirements.
06
Predictive Engineering Analytics
Data-model experiments support early review of project risk, quantities, and cost drivers while assumptions and engineering judgement remain visible.
Product Portfolio
Software we built.
Beyond services, we develop purpose-built software from concept and engineering through deployment, with product status and scope confirmed during evaluation.
IMSSpetia Product
Interiors Mapping System
An application developed to structure interiors mapping and measurement workflows for real-estate teams from approved project inputs.
AutomationMobile / WebReal Estate
DTSSpetia Product
Digital Twins Software
A NeRF-based R&D engine for evaluating how approved drone footage can support 3D-mesh and digital-twin workflows.
Computer VisionNeRF3D Mesh
SigmaPSpetia Product
Large-Scale Mapping Platform
A full-stack platform developed to coordinate large-scale mapping inputs, workflow stages, review, and output preparation.
Full-StackCloudMapping
Intelligence, engineered in.
A useful experiment becomes a controlled workflow only after its inputs, limitations, validation method, reviewer, and measurable outcome are defined.
How We WorkInnovation with
Innovation with
discipline.
Our lab pairs current AI with documented engineering controls: approved data handling, visible assumptions, named review, and human-led acceptance.
01
Applied, Not Academic
Experiments start with a defined delivery problem and are tested against an agreed workflow before client use is considered.
02
Project Data Rules
Approved tools, access, transfer, retention, confidentiality, and any restrictions on external model processing are documented for the engagement.
03
Human-Led
Automation supports named specialists; engineering judgement, review responsibility, and acceptance remain assigned to people.