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Vetting & Validation
12 TermsAECO.digital Score AECO.digital
A weighted composite score from 1–100 produced by our Vetting Lab audit process. Calculated across six dimensions: Core Functionality, Interoperability, UX & Adoption, Value vs. Pricing, Support & Documentation, and Vendor Viability. Scores above 75 typically qualify for a Buy verdict.
→ See also: Interoperability Matrix, Vendor Viability Score
Buy / Wait / Avoid AECO.digital
The three-verdict taxonomy used at the conclusion of every Vetting Lab audit. Buy indicates the tool delivers sufficient value relative to risk for qualified use cases. Wait indicates potential but insufficient maturity. Avoid indicates critical failures in testing, interoperability, or vendor stability.
Capability Profile AECO.digital
A verified data sheet outlining what a startup’s technology can actually do today, clearly distinguished from “roadmap features” that are not yet live. Capability Profiles are updated when vendors ship material changes verified by our team.
→ Critical for procurement teams evaluating pre-GA products
Field-Readiness Validation
A test protocol assessing whether a tool performs reliably under real-world conditions: unstable network connectivity, large file sizes, multi-user concurrent access, and hardware constraints typical of a construction site. A tool may pass lab tests and fail field-readiness — we test both.
Interoperability Matrix AECO.digital
Our proprietary scoring system rating how effectively a tool exchanges data with the wider AEC ecosystem, specifically assessing OpenBIM compliance, IFC 4.3 support, API stability, and data portability. Scored on a 0–10 scale within the AECO.digital Score composite.
→ A low Interoperability Matrix score is the most common reason for a Wait verdict
Legacy Risk Risk
A risk rating assigned to software products with high technical debt, deprecated architecture, or outdated data models that may hinder future integration, cloud migration, or data sovereignty compliance. Legacy Risk is assessed during Vetting Lab audits and flagged prominently in audit reports.
Sandbox Testing
The controlled, isolated test environment used by AECO.digital’s Vetting Lab for all tool audits. Sandboxes use real anonymised project data, not vendor-supplied demo datasets. This ensures performance metrics reflect genuine deployment conditions rather than optimised demonstrations.
Technical Validation AECO.digital
A rigorous 30-day assessment of a tool’s codebase stability, API reliability, real-world performance under project load, and security posture — moving beyond traditional marketing claims. Published methodology is available at AECO.digital/our-methodology.
Transfer Tech
Technologies originally developed for high-precision industries — Aviation, Automotive, Aerospace, or Defence — that are being evaluated or adapted for deployment within the AECO environment. Transfer Tech carries both high potential and elevated integration risk due to domain-specific assumptions baked into the original architecture.
Vendor Viability Score Risk
One of the six AECO.digital Score dimensions. Assesses a vendor’s financial stability, funding runway, team depth, customer retention signals, and acquisition risk — because a tool with a score of 85 from a vendor with 6 months of runway is not a safe buy.
→ See also: M&A Risk Score, Legacy Risk
Wall of Shame AECO.digital
An AECO.digital editorial feature documenting tools that failed Vetting Lab audits or produced significant negative outcomes in field deployments. Published with full methodology transparency to help practitioners avoid costly technology mistakes before they happen on live projects.
Weighted Scoring Rubric AECO.digital
The published scoring framework underpinning every AECO.digital audit. Weights are adjusted by tool category — interoperability carries a higher weighting for CDEs than for standalone estimation tools. Full rubric weights are disclosed in every audit report.
BIM, Data Standards & Interoperability
18 TermsBIM (Building Information Modelling) Standard
A process for creating and managing digital representations of the physical and functional characteristics of a built asset across its full lifecycle — from design through construction to operations. BIM is not software; it is a method of working that software enables. Defined under ISO 19650.
BIM Level 2 UK Mandate
The UK Government’s mandated minimum standard for all public-sector projects since 2016. Requires collaborative 3D BIM with shared data environments, federated models, and structured asset information. Many practitioners conflate BIM Level 2 compliance with BIM maturity — they are not equivalent.
→ Succeeded by ISO 19650 as the international benchmark
CDE (Common Data Environment) ISO 19650
An agreed source of information for any given project or asset, used to collect, manage, and disseminate each container of information through a managed process. Defined in ISO 19650-1. A CDE is not just a file server — it enforces workflow states (Work In Progress → Shared → Published → Archived) and access controls.
→ Key vendors: Autodesk Construction Cloud, Trimble Connect, Aconex, BIMcollab
COBie (Construction Operations Building Information Exchange) Standard
A data schema for the handover of asset information from construction to operations. COBie is structured as a spreadsheet or IFC file and captures equipment, spaces, systems, and maintenance schedules in a format consumable by Facilities Management (FM) and CAFM systems.
Data Drops
Formally defined, scheduled points in a project lifecycle at which specific, validated information must be available and submitted to the employer. Defined in an Exchange Information Requirement (EIR) or the Asset Information Requirements (AIR). Data Drops gate payments and regulatory approvals on major public infrastructure projects.
Data Sovereignty Risk
The principle that digital assets — models, specifications, cost data, sensor feeds — remain under the legal control of their owner and are governed by the laws of the country in which the data physically resides. Critical for multinational projects where cloud infrastructure may store UK project data in US or EU jurisdictions.
→ Relevant legislation: GDPR (EU), UK GDPR, US CLOUD Act, China PIPL
DfMA (Design for Manufacture and Assembly)
A design philosophy and workflow that optimises building elements for factory production and on-site assembly, reducing waste, cost, and programme risk. DfMA requires tight integration between design authoring tools and manufacturing execution systems (MES) — interoperability is the critical technical challenge.
Digital Twin Market Hype Risk
A real-time or near-real-time virtual representation of a physical asset, connected to live sensor data, updated continuously, and capable of simulation and predictive analysis. In AECO, most “digital twins” are aspirational BIM models without live data connections — AECO.digital distinguishes between Level 1 (static model), Level 2 (connected data), and Level 3 (predictive simulation) when auditing claims.
EIR (Employer’s Information Requirements)
A pre-appointment document issued by the appointing party defining what BIM information is required, when, in what format, and to what level of information need. The EIR drives the BIM Execution Plan (BEP) and all downstream data drop schedules. Poor EIRs are the most common root cause of BIM project failures.
Federation
The process of combining separate, discipline-specific BIM models (architectural, structural, MEP, civils) into a single coordinated model for clash detection, coordination, and client review — without merging the underlying native files. Federation preserves authorship and enables parallel workflows across delivery teams.
IFC (Industry Foundation Classes) ISO 16739
An open, neutral data format and object schema for BIM data exchange, standardised under ISO 16739. IFC enables interoperability between software tools from different vendors by providing a common language for building objects, their properties, and relationships. IFC 4.3 is the current release, adding infrastructure (roads, bridges, rail) to the schema.
→ Maintained by buildingSMART International. Not to be confused with proprietary formats (RVT, NWD).
IFC 4.3 Current Release
The latest major release of the IFC schema, published as ISO 16739-1:2024. IFC 4.3 extends the standard to cover infrastructure assets including roads, bridges, railways, ports, and waterways — critical for National Infrastructure Delivery Programmes (NIDPs). Adoption by authoring tools remains partial as of 2025.
OpenBIM Standard
A universal approach to collaborative design, construction, and operation of buildings and infrastructure based on open standards and workflows. Championed by buildingSMART International. OpenBIM mandates vendor-neutral data exchange via IFC and BCF — contrasted with proprietary BIM ecosystems that create vendor lock-in.
PAS 1192 Series
The suite of UK Publicly Available Specifications that defined BIM Level 2 requirements from 2013–2019. Superseded by the adoption of ISO 19650 into UK practice. PAS 1192-2 (design & construction) and PAS 1192-3 (asset management) remain reference documents for understanding the UK BIM mandate’s original intent.
Reality Capture
The use of scanning technologies — LiDAR, photogrammetry, structured light — to create accurate as-built digital representations of physical environments. Point clouds and photogrammetric meshes are the primary outputs, consumed by BIM authoring tools, digital twin platforms, and construction quality management systems.
bcf (BIM Collaboration Format) Standard
An open file format for communicating coordination issues, design comments, and clash results between different BIM tools — without requiring access to the native model file. BCF is the standard mechanism for issue management in OpenBIM workflows and is supported by all major CDE platforms.
LOD (Level of Development) BIMForum
A framework specifying the content and reliability of BIM model elements at different project stages — from LOD 100 (conceptual mass) to LOD 500 (as-built, verified). LOD defines what a model element represents, not merely its geometric detail. Critical for setting procurement expectations in BIM appointments.
→ Not to be confused with Level of Information Need (LOIN) in ISO 19650
LOIN (Level of Information Need) ISO 19650
The ISO 19650 successor to LOD, defining not just geometry but all information attributes required for a specific purpose at a specific stage. LOIN covers geometric information, alphanumeric data (properties), and documentation. Specifying LOIN correctly in an EIR is a prerequisite for successful data drop delivery.
Market Intelligence & Startup Terms
12 TermsARR (Annual Recurring Revenue)
The normalised, annualised value of a SaaS vendor’s subscription-based revenue. ARR is the primary metric used by investors to value AEC technology companies. For practitioners, ARR growth rate signals product-market fit — rapid ARR growth in a niche market often precedes an acquisition event.
→ AECO.digital tracks ARR signals for 800+ vendors in the Engine Room
Capability Profile AECO.digital
A verified data sheet published by AECO.digital outlining what a startup’s technology can demonstrably do today — clearly separated from “roadmap features” that are not yet live. Capability Profiles are updated when vendors ship material changes verified by our team.
Enterprise Traction Market Signal
A metric assessing a solution’s successful deployment within Tier-1 global AEC firms, as distinct from small-scale pilot programs. Enterprise Traction is AECO.digital’s primary indicator of product-market fit at scale — a tool with 20 Tier-1 deployments carries fundamentally different risk than one with 200 SME trials.
Feature Stripping Acquisition Risk
The process by which an acquiring platform removes, degrades, or paywalls features from an acquired product post-acquisition. Feature stripping is the most common adverse outcome for practitioners following an M&A event, often resulting in forced migration to the acquirer’s native toolset.
→ See also: M&A Risk Score, Vendor Viability Score
Horizontal Platform Market Structure
A software platform designed to serve multiple industries, with construction as one vertical among many. Horizontal platforms (e.g., Salesforce, Microsoft 365) offer broad integration capability but limited AECO-specific depth. Contrasted with Vertical Platforms built exclusively for construction workflows.
M&A Risk Score Risk
An AECO.digital assessment of the likelihood that a vendor will be acquired within a 24-month horizon, factoring ARR, funding stage, platform giant acquisition history, and strategic fit signals. High M&A Risk Scores indicate procurement caution — any decision to adopt the tool should include a migration pathway.
Market Pulse AECO.digital
AECO.digital’s event-driven intelligence format published in the Engine Room. Market Pulse posts are triggered by significant funding rounds, acquisitions, platform announcements, or regulatory changes — providing immediate context on what the event means for practitioners’ technology stacks.
Platform Giant Market Structure
Large multinational software conglomerates — Autodesk, Trimble, Bentley Systems, Procore, Oracle Construction — whose ecosystem decisions, API strategies, and acquisition activity significantly impact market access for smaller innovators and the technology choices available to practitioners.
→ Tracked continuously in the AECO.digital Giant Tracker
Product-Market Fit (PMF)
The degree to which a product satisfies a strong market demand within its target segment. In AEC technology, PMF is harder to achieve than in horizontal SaaS due to the industry’s fragmented procurement, long sales cycles, and resistance to workflow change. AECO.digital’s Enterprise Traction metric is a proxy for PMF at scale.
Series A / B / C Funding
Successive rounds of institutional venture capital investment following seed funding. Series A ($2–15M typical in AEC tech) funds initial scaling; Series B ($15–50M) funds enterprise go-to-market; Series C+ ($50M+) signals preparation for IPO or strategic acquisition. AECO.digital tracks all rounds above $1M in the Investment Tracker.
Vertical Platform Market Structure
A software platform built exclusively for construction and infrastructure workflows, with deep domain-specific functionality. Vertical platforms carry higher vendor concentration risk but deliver superior workflow integration. Examples: Procore (project management), ALICE Technologies (scheduling optimisation), Buildots (site progress monitoring).
Zombie Vendor Risk
A vendor that has ceased meaningful product development but continues to generate support revenue from existing customers. Zombie Vendors present high Legacy Risk — they will not develop IFC 4.3 or cloud-native capabilities — but are difficult to identify without access to internal roadmap and recruitment signals that AECO.digital monitors.
AI, Automation & Emerging Technology
14 TermsAgentic AI Emerging
AI systems capable of autonomous multi-step task execution — planning, taking actions, and self-correcting — without continuous human prompting. In AECO contexts, agentic AI is beginning to appear in automated clash resolution, design iteration, and procurement workflows. Carries higher risk than assistive AI due to reduced human oversight.
AI Hallucination Risk Risk
The tendency of Large Language Models (LLMs) to generate plausible-sounding but factually incorrect outputs — a critical risk when AI tools are used for specification writing, compliance checking, or cost estimation in AEC contexts. AECO.digital’s Vetting Lab tests hallucination rates explicitly for AI tools with compliance or contractual output functions.
Computer Vision (CV)
A field of AI enabling computers to interpret and analyse visual information from images or video. In construction, CV is applied to site progress monitoring (comparing reality capture against programme), safety compliance checking, and quality defect detection — typically from drone footage, fixed cameras, or 360° site cameras.
Copilot / AI Assistant Market Hype Risk
An AI feature embedded within existing software that provides contextual suggestions, generates content, or automates repetitive tasks based on user intent. In AEC, copilots are appearing in design tools (Revit, ArchiCAD), project management platforms, and specification writing systems. Quality varies enormously — AECO.digital audits copilot accuracy and hallucination rates separately from the host product.
Generative Design
An AI-driven design exploration process in which algorithms generate multiple design options optimised against specified constraints — structural performance, cost, programme, sustainability. Practitioners should distinguish between true generative design (constraint-optimised output) and parametric design (rule-based variation) — they are frequently conflated in vendor marketing.
LLM (Large Language Model)
A deep learning model trained on large text corpora, capable of generating, summarising, translating, and reasoning about text. In AEC applications, LLMs are being deployed for specification generation, RFI response automation, contract review, and knowledge retrieval from project documentation. Data privacy and accuracy are the primary enterprise adoption barriers.
ML (Machine Learning)
A subset of AI in which systems learn patterns from data without being explicitly programmed. Supervised ML is used in AEC for cost estimation refinement, schedule risk prediction, and defect classification. Unsupervised ML underpins anomaly detection in IoT sensor streams from smart buildings and infrastructure assets.
Model Training Data Risk Risk
The risk that proprietary project data — drawings, models, cost data, specifications — submitted to a vendor’s AI tool is retained, used to train the vendor’s foundational model, or exposed to other customers. Critical for practitioners on security-classified or commercially sensitive projects. AECO.digital’s Vetting Lab examines vendor data use agreements as part of every AI tool audit.
Predictive Analytics
The use of statistical algorithms and machine learning to forecast future outcomes from historical data. In AEC, predictive analytics applications include schedule delay prediction, cost overrun forecasting, equipment failure prediction (IoT-driven), and safety incident probability modelling. Accuracy degrades significantly when trained on limited or unrepresentative project datasets.
RAG (Retrieval-Augmented Generation)
An AI architecture combining a retrieval system (searching a specific document corpus) with a generative model to produce answers grounded in specific, trusted sources. RAG is the preferred architecture for AEC AI applications involving specifications, regulations, or project documentation — it substantially reduces hallucination risk compared to pure LLM generation.
Robotics & Autonomous Systems (RAS)
Hardware and software systems capable of performing physical construction tasks with varying degrees of autonomy — bricklaying robots, autonomous earthmoving equipment, inspection drones, exoskeletons. RAS adoption in AEC remains limited by site conditions, regulatory frameworks, and integration with existing programme management workflows.
Shadow AI Risk
The use of AI tools by employees outside IT governance and procurement processes — typically consumer LLMs used for specification writing, contract review, or design generation. Shadow AI creates data sovereignty, IP, and liability risks that are particularly acute in AECO contexts involving classified infrastructure or commercially sensitive project data.
Synthetic Data
Artificially generated data that mimics the statistical properties of real project data, used to train AI models without exposing sensitive or proprietary information. Increasingly used in AEC AI development to overcome the scarcity of labelled training data — particularly for computer vision models requiring annotated construction site imagery.
Workflow Automation
The use of software to execute, coordinate, and monitor sequences of tasks that would otherwise require manual intervention — RFI routing, drawing issue workflows, approval chains, procurement triggers. Distinct from AI automation in that workflow automation typically follows deterministic rules rather than probabilistic inference. Dynamo and visual programming environments enable workflow automation within BIM authoring tools.
Strategic Intelligence & Decision-Making
10 TermsDe-risking Framework AECO.digital
A structured set of criteria used by AECO.digital and recommended to practitioners for identifying and mitigating financial, technical, legal, and operational risks inherent in adopting new AEC technology — covering vendor stability, data portability, integration dependencies, and migration pathways.
Digital Maturity Assessment
A structured evaluation of an organisation’s current digital capabilities against a defined maturity framework. AECO.digital uses a five-tier model: Level 1 (Digital Beginner) through Level 5 (Global Digital Leader). Maturity assessments are prerequisites for technology roadmap development — tools appropriate for Level 2 organisations may be inappropriate for Level 4.
Implementation Playbook AECO.digital
A step-by-step technical blueprint providing exact deployment stages, resource requirements, integration dependencies, timeline estimates, and ROI calculations for a specific validated solution. AECO.digital publishes Implementation Playbooks in the Intelligence pillar following Vetting Lab audits with Buy verdicts.
Innovation Tax
The hidden cost — in time, money, and operational disruption — incurred when an organisation deploys unvalidated technology on live projects. The Innovation Tax is AECO.digital’s foundational concept: the Vetting Lab exists to eliminate it. Typical Innovation Tax events include failed integrations, data loss, contractor disputes, and programme delays caused by immature technology.
Maturity Tier AECO.digital
AECO.digital’s five-level benchmark for digital capability: Level 1 (Digital Beginner), Level 2 (Process Digitiser), Level 3 (Integrated Practitioner), Level 4 (Data-Driven Leader), Level 5 (Global Digital Leader). Maturity Tier benchmarks appear in Vetting Lab audit reports to contextualise which organisations each tool is appropriate for.
New Stack Alert AECO.digital
A fast-track AECO.digital assessment of a newly released or recently updated tool, published within 30 days of a significant product launch. New Stack Alerts provide an early AECO.digital Score, a Quick Verdict, and a category comparison — enabling practitioners to track the market before committing to a full evaluation cycle.
Pilot Trap Risk
The organisational failure mode in which technology pilots are repeatedly initiated but never scaled — consuming innovation budget without delivering enterprise value. The Pilot Trap typically occurs when pilots lack success criteria, executive sponsorship, or integration with procurement decision-making processes.
ROI Framework
A structured methodology for calculating the financial return from AEC technology investment. AECO.digital’s ROI Framework captures five value dimensions: direct labour savings, error/rework reduction, programme acceleration, risk mitigation value, and strategic positioning benefit — recognising that not all technology ROI is immediately quantifiable.
Tech Stack
The full combination of software tools, platforms, integrations, and data infrastructure deployed by an AEC organisation to deliver its projects and operate its assets. Tech stack decisions are interdependent — a CDE choice constrains design tool options; a scheduling platform choice impacts cost management integrations. AECO.digital’s Ecosystem pillar maps tech stack compatibility across major platforms.
Vendor Lock-in Risk
The state in which an organisation becomes dependent on a specific vendor’s proprietary formats, APIs, or workflows — making migration to alternative platforms prohibitively costly in time, money, or data loss. Vendor lock-in risk is highest with proprietary BIM formats (RVT, DGN) and closed API ecosystems. Mitigated by contractual data portability clauses and IFC-first data strategies.
Ecosystem, Compliance & Global Standards
10 TermsAPI (Application Programming Interface)
A defined interface enabling two software systems to communicate, exchange data, and trigger actions. In AEC technology procurement, API stability, versioning policy, and deprecation notice periods are critical procurement criteria — poorly managed APIs are a primary cause of integration failure after platform updates or acquisitions.
→ AECO.digital assesses API quality in every Vetting Lab audit
EU AI Act Regulation
The European Union’s comprehensive AI regulatory framework, in force from 2024. Classifies AI systems by risk level, with construction applications including AI-assisted structural analysis and safety monitoring likely categorised as High Risk — requiring conformity assessments, human oversight mechanisms, and technical documentation. Affects any AEC organisation using AI tools on EU-based projects.
GDPR (General Data Protection Regulation) Regulation
EU and UK data protection regulation governing the collection, processing, storage, and transfer of personal data. In AECO contexts, GDPR applies to biometric site access data, worker location tracking, occupancy monitoring systems, and any cloud platform storing personal data of EU/UK residents — regardless of where the data processor is headquartered.
Giants Signal AECO.digital
AECO.digital’s event-driven intelligence format covering significant strategic moves by Platform Giants — acquisitions, API changes, pricing model shifts, roadmap announcements, and partnership formations. Giants Signal posts contextualise what each move means for practitioners’ existing technology investments and future procurement decisions.
Global Gatekeeper AECO.digital
AECO.digital’s framework for assessing whether a technology meets international trade, safety, and federal compliance standards relevant to AECO deployments — including GDPR, ISO 19650, US Export Administration Regulations (EAR), ITAR (International Traffic in Arms Regulations) for defence-related infrastructure, and China PIPL.
ISO 19650 International Standard
The international standard for managing information over the whole life cycle of a built asset using BIM. Comprises five parts: concepts and principles (Part 1), delivery phase (Part 2), operational phase (Part 3), information exchange (Part 4), and security-minded approach (Part 5). Mandated or referenced in procurement requirements across UK, EU, and major GCC infrastructure programmes.
ISO 55000 (Asset Management) International Standard
The international standard for asset management systems, providing the framework within which digital tools — CAFM, CMMS, digital twin platforms — must operate to deliver compliant asset information to operators and infrastructure owners. ISO 55000 alignment is an increasingly common procurement requirement for operational technology on public infrastructure assets.
Minimum Viable BIM (MVBIM)
A procurement philosophy specifying only the BIM deliverables that generate demonstrable value for the specific project use case — avoiding the over-specification of information requirements that inflates delivery cost without improving outcomes. Contrasted with aspirational BIM requirements that specify LOD 500 across all model elements regardless of operational necessity.
Net Zero Carbon (NZC) Compliance
The requirement that buildings and infrastructure assets achieve zero net carbon emissions across their full lifecycle — construction, operation, and end of life. NZC compliance is increasingly embedded in planning consent conditions and public procurement requirements, driving demand for embodied carbon calculation tools, whole-life carbon modelling platforms, and operational energy monitoring systems.
SaaS (Software as a Service)
A software delivery model in which applications are hosted by the vendor and accessed via web browser or API, typically on a subscription basis. The shift from perpetual licence to SaaS in AEC technology has fundamentally changed vendor relationships — moving from capital expenditure to operational expenditure, with implications for procurement, IT governance, and data sovereignty.
The AECO Weekly Briefing applies this vocabulary to live signals — funding rounds, tool launches, standards updates — so you understand not just the terminology but the context it operates in.
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