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Strategic Industry Positioning — BIM Intent Compiler

The gap between visual editors and Spatial MRP is an opportunity. Competitive landscape, scorecard, and market positioning against Revit, Tekla, and Trimble.

Why the gap between visual design editors and a Spatial MRP compiler is an opportunity, not a deficit.


What Are BIM and IFC?

BIM (Building Information Modelling) is the practice of designing a building as a structured digital model rather than flat drawings. Instead of lines on paper, every wall, door, pipe, and beam is a database object with geometry, material, cost, and relationships to other objects. Architects design in BIM; contractors are expected to build from BIM.

IFC (Industry Foundation Classes, ISO 16739) is the open standard that makes BIM data portable. When an architect finishes a model in Revit or ArchiCAD, they export an IFC file — a vendor-neutral snapshot of the entire building: 51,000+ elements with types, storeys, spatial containment, and properties. Any compliant tool can read it.

BIM dimensions measure what a model can do beyond 3D geometry:

Dimension Covers Example
3D Geometry & visualisation Walk-through renders
4D Construction scheduling "Install steelwork week 12"
5D Cost & quantity takeoff "2,400 m2 of curtain wall @ $X/m2"
6D Sustainability / energy Embodied carbon per element
7D Facility management Maintenance schedules, asset lifecycle

BIM adoption exceeds 70% in developed markets (UK, Germany, Nordics) driven by government mandates. The global BIM market reaches $15.4B by 2030 (CAGR 11.3%). The digital twin market hits $384.8B by 2034 (CAGR 35.4%). All require a deterministic BIM-to-ERP bridge — spatial MRP with verified placement — that is not yet widely available.


The Landscape Today

The construction-tech market has three tiers. Each solves a real problem — none solves the problem this project addresses.

Tier 1 — Incumbents (Geometry Authoring)

Tool Role Approach
Autodesk Revit Full BIM authoring — walls, MEP, structural Proprietary, desktop. Industry standard.
ArchiCAD (Graphisoft) Architectural BIM with strong documentation Proprietary, desktop. Strong in EU/Asia.
Tekla Structures (Trimble) Steel/concrete detailing, LOD 400+ Proprietary, desktop. Fabrication-grade.

These are where buildings get designed. A Revit user drags a door onto a wall and it cuts the opening automatically. What they cannot do: tell you what to procure. Revit models 51,088 elements but cannot produce a bill of materials that maps to a purchase order. The QS opens the model in Navisworks, manually counts elements, and exports to Excel — weeks of work, error at every step.

Tier 2 — Visual Newcomers (Design-to-3D)

Tool What It Does Stage
Snaptrude Browser sketch-to-BIM, real-time 3D $10M+ Series A
TestFit AI generative site planning, instant pro forma $20M Series A
Arkio VR/AR collaborative design Seed
Hypar Cloud parametric building configurator Acquired by Autodesk (2024)
Modelo Web-based 3D viewer + collaboration Series A

Beautiful GUIs, smooth animations, drag-and-drop libraries. What they cannot do: prove the model is correct, trace every element to a catalog product, or verify spatial arrangement against regulations. They help you decide what to build; they say nothing about how to build it.

Tier 3 — Open Source (IFC-Native)

Tool What It Does Approach
Bonsai/BlenderBIM IFC-native BIM authoring inside Blender FOSS, Python/C++
FreeCAD BIM Parametric BIM workbench, IFC export FOSS, merged in v1.0
IfcOpenShell IFC parsing/generation library FOSS, Python/C++
IFC.js / ThatOpenCompany Web IFC viewer/editor components FOSS, TypeScript
xBIM .NET IFC toolkit, geometry engine + viewer FOSS, C#

Bonsai is closest philosophically — it works directly with IFC data. What none of them can do: compile. They author and parse IFC models but cannot decompose 51K elements into a BOM, assign them to storeys and disciplines, compress via formula verbs, and produce a verified construction order. They are editors and libraries, not compilers.


Where the BIM Compiler Sits

The entire industry focuses on design-time — helping architects create models. Nobody focuses on compile-time — taking a finished model and producing construction-grade output that maps to ERP procurement.

                    DESIGN PHASE              CONSTRUCTION PHASE
                    ────────────              ──────────────────
Tier 1 (Revit)     [████████████]             [                ]
Tier 2 (Snaptrude) [████████]                 [                ]
Tier 3 (Bonsai)    [██████████]               [                ]

BIM Compiler       [██*]                       [████████████████]
                    ↑                          ↑
                    *GUI = LHF (Phase G)        Spatial MRP output

This is the same relationship as CAD vs. CAM in manufacturing: SolidWorks designs the part, the G-code compiler produces machine instructions. Nobody expects SolidWorks to run the CNC machine.

Spatial MRP — A Differentiated Approach

Spatial MRP = Material Requirements Planning extended with spatial intelligence:

Traditional MRP Visual BIM Tools Spatial MRP (BIM Compiler)
Answers What materials, when? What does it look like? What materials, where, how connected?
Input BOM + demand forecast Architect's sketch IFC extraction (51K elements)
Output Purchase orders 3D model + renders C_Order + C_OrderLine + W_Verb_Node
Verification MRP explosion audit Visual review Rosetta Stone gate (G1-G6 proof)
Compression BOM explosion None 51K elements → 700 BOM lines (73x)

Visual tools help architects imagine buildings. The BIM Compiler helps contractors build them.


IFC/BIM Compliance Scorecard

IFC compliance is the prerequisite for serious construction deployment. Each BIM dimension compounds difficulty for tools not built on structured data.

Important context: We already built and shipped the IfcOpenShell Federation addon for Bonsai — a plugin that extracts multi-discipline IFC models into a FederateModel spatial database (SQLite + R-tree spatial index), achieving 93% memory reduction on a 93K-element terminal project. On top of that database, we delivered working PoCs for 4D (construction schedule + Blender animation), 5D (automated BOQ with Excel export and CIDB pricing), 7D (digital twin asset management with maintenance scheduling and IoT sensors), rebar generation, NLP query against building data, and discipline color schema — each built in a single Claude Code session. These are hardcoded Python scripts: they prove the capabilities work. What the BIM Intent Compiler adds is the production foundation — a typed verb compiler, mathematical proof gate, BOM factorisation, and ERP-native tables — that makes these capabilities structural, repeatable, and scalable to any building type.

Capability Revit ArchiCAD Snaptrude TestFit Arkio Bonsai FreeCAD BIM Compiler
IFC native Export Export Export No No Native Export Native (extract)
openBIM (ISO 19650) Partial Yes Partial No No Yes Partial Yes
3D Geometry Full Full Full Site only Full Full Full Via Bonsai/Blender
4D Scheduling Plugin Plugin No No No No No ScheduleDAO: BOM × CIDB sequence → Gantt
5D Cost/QTO Manual Manual No Pro forma No Basic No CostDAO: 3-component (mat+lab+eq) CIDB 2024
6D Sustainability Plugin Plugin No No No No No SustainabilityDAO: carbon rollup from M_Product
7D Facility Mgmt Plugin Plugin No No No No No FacilityMgmtDAO: maintenance schedule + lifecycle
BOM factorisation No No No No No No No 73x compression (51K→700)
ERP-native output No No No No No No No C_Order + iDempiere tables
Spatial proof No No No No No No No G1-G6 Rosetta Stone gate
Infrastructure IFC4X3 No No No No No Partial No Bridge+Road+Rail compiled
Inference engine No No No No No No No Dependency DAG + proof tree
Product browser + fit No No Partial No No No No BOM Chooser + AABB fit check
Wireframe-first UX No No No No No No No WF-BB: bbox=working, solid=settled
Live cost-of-change No No No No No No No costOfChange during drag (stub)
Change Request (R_Request) No No No No No No No Cross-discipline CR + audit trail (spec)

Numeric scoring (0-3): 0=absent, 1=partial/plugin, 2=built-in, 3=native/core

Tool IFC 3D 4D 5D 6D 7D BOM ERP Proof Inference WF-UX CR/Audit Total /36
Revit 2 3 1 1 1 1 0 0 0 0 0 0 9
ArchiCAD 2 3 1 1 1 1 0 0 0 0 0 0 9
Snaptrude 1 3 0 0 0 0 0 0 0 0 0 0 4
TestFit 0 2 0 2 0 0 0 0 0 0 0 0 4
Arkio 0 3 0 0 0 0 0 0 0 0 0 0 3
Bonsai 3 3 0 1 0 0 0 0 0 0 0 0 7
FreeCAD 1 3 0 0 0 0 0 0 0 0 0 0 4
BIM Compiler 3 3 2 3 2 2 3 3 3 3 2 2 31

New dimensions: - WF-UX = Wireframe-first interaction (bbox=working, solid=settled, per-object BOUNDS) - CR/Audit = Change request + audit trail (R_Request, AD_ChangeLog, multi-user undo)

All starred items now re-grounded on ERP framework (Tier 1 DONE 2026-03-20). 3D via Bonsai/Blender viewport (Federation addon + WF-BB). 6D: SustainabilityDAO — BOM × carbon_kg_per_unit rollup from M_Product. 7D: FacilityMgmtDAO — maintenance schedule from maintenance_interval_months. CR/Audit: ChangelogDAO — interceptor on save(), MOVE/RESIZE/PLACE/DELETE diff + undo. See TIER1_SRS.md for full spec. 14 witnesses, 231 tests GREEN.


Three Moats

1. IFC compliance is hard to add retroactively. The visual newcomers started with geometry, not IFC. Adding real IFC compliance — native data model alignment, not just export — requires rearchitecting their core. Most tools treat IFC as a file format, not a data model. We treat it as structured input to a database pipeline.

5. Domain-agnostic compilation — one pipeline for any facility type. The same 12-stage pipeline that compiles a single-storey house also compiles a multi-storey airport terminal, a bridge, a road, and a 73-element railway. No code changes per domain — only a ~30-line YAML mapping segments and disciplines. VerbDetector, BOMWalker, tack convention, delta tests, and G1-G6 gates are all domain-agnostic. No competitor validates infrastructure IFC4X3 with the same toolchain that validates buildings. Proven 2026-03-20: BR 10/10, RD 4/4, RL 4/4 Rosetta Stone gates PASS — CLUSTER verb detection active, rail achieves 93% BOM compression (75 lines → 5).

5b. Terrain-following placement — a winding road on real terrain. The Designer's PlacementContext abstraction makes rooms and terrain the same concept. AlignmentContext.fromContour() auto-generates a curved alignment that follows terrain contours — proven on 689 real survey points (river valley, 20m elevation range). Elements snap ON/ABOVE/BELOW terrain; drag updates Z in real-time. Contour-following minimises earthworks by riding the topography instead of cutting through it. Measured: 2.9km winding road with R=17m–1037m curves, heading sweep 63°→-158°→-23°. No commercial BIM tool does contour-following infrastructure design with validation against IFC4X3 rules. See INFRA_DESIGNER_SRS.md §1 + §5 for full spec.

1b. Geometry Forge — formula-driven construction pieces. Domain-specific tools (MiTek for timber, Tekla for steel, NAPA for hulls) have computed geometry from parameters for decades — but each is locked to one material system. The Geometry Forge generalises this: same ForgeEngine interface, any piece type, full BOM traceability, same EYES verification. See GEOMETRY_FORGE_SRS.md §9 for industry precedent matrix.

2. DB/ERP integration is a bigger moat than GUI. Converting IFC to a relational database with ERP semantics (M_Product, M_BOM, C_Order) requires deep manufacturing domain knowledge. A startup can hire UI designers to build a drag-and-drop editor in months. Building a Spatial MRP engine that maps to iDempiere's manufacturing model requires understanding both BIM and ERP — a rare combination. The Java DAO layer, BIM COBOL verb grammar, BOM dimension model, and RosettaStone proof strategy represent years of domain convergence that cannot be replicated by visual-first tools.

3. LLM-assisted development favours our architecture. LLMs excel at SQL, Python, and structured data — the core of our DB-first approach. GPU-based 3D rendering (the visual tools' core) is harder for LLMs to generate. We have concrete proof: our IfcOpenShell Federation addon shipped a FederateModel spatial DB (93% memory reduction on 93K elements), then 4D scheduling, 5D BOQ, 7D asset management, rebar generation, NLP query, and color schema — each built in a single Claude Code session. The entire Federation addon, with all its features, was developed with LLM assistance at a pace that would take a conventional team months. This same velocity now applies to the ERP compiler framework, where each new verb, witness, or BOM dimension is a bounded task that Claude Code completes in one session (see CONCEPTUAL BLUEPRINT for layer architecture, BeyondVerbs for the roadmap beyond the current verb set).

4. Symbolic inference over relational data is unique. The Inference Engine (BIM_Designer_SRS §14) evaluates validation rules in dependency order using Kahn's topological sort, produces proof trees with AD_Val_Rule citations, and SKIPs downstream rules when upstream premises fail. This is Datalog-style deduction over the 4-database schema — not AI, not heuristics, but deterministic symbolic reasoning. No visual BIM tool has a formal proof chain from design decision to regulation citation. The Approve gate requires all-rules-pass before Promote — a governance pattern borrowed from ERP document workflows (iDempiere DocAction) that visual tools cannot replicate without rebuilding their validation from scratch.

The asymmetry: adding a GUI to our DB/ERP foundation takes weeks. Adding DB/ERP depth to their GPU-first foundation takes years. Adding proven capabilities (4D-7D) from our PoC addons to a typed ERP framework takes days.


GUI: Low-Hanging Fruit, Off Critical Path

The PoC must prove the hard parts: BOM factorisation (73x), Spatial MRP, G1-G6 mathematical proof, formula compression (TILE/ROUTE/FRAME). A GUI proves none of these.

When we need a GUI, the ERP BOM framework is itself a generic construction designer for any building type. A GUI on this foundation is a tree editor + form editor + Bonsai 3D viewport — standard UI work that LLMs generate easily.

Phase B (done):  BIM COBOL DSL → classify_te.yaml → compiler → C_Order
Phase G (now):   GUI Editor → BOM Chooser → snap → save → compile → C_Order
                  ↑
                  20 wire protocol actions, 87/87 tests GREEN
                  Works for ANY building type (RE, CO, IN) — generic

The Designer Architecture (Phase G)

The GUI design is fully specified in BIM_Designer.md. Three mechanisms make the Bonsai addon a parametric construction editor, not just a viewer:

1. AttributeSetInstance overrides (§8) — When a user stretches a wall or resizes a room in Bonsai, the change is captured as an M_AttributeSetInstance on the C_OrderLine. The catalog product stays generic; the ASI captures the user's specific dimensions. The compiler blends catalog geometry with ASI overrides into output.db. This is the iDempiere product-variant pattern applied to spatial parameters.

2. Container constraint rules (§9)AD_Val_Rule-pattern validation ensures a child never exceeds its parent container. Stretch a room beyond the floor → the compiler blocks it or offers to extend the floor. The constraint cascades down the BOM tree: building → floor → room → furniture. Same rule at every level — data-driven, no code change per building type.

3. Pattern multiplication (§10) — The user declares "a window every 2.5m" or "a beam every 4m" and the compiler generates the instances. This works across domains: windows along walls (building), piers along deck (bridge), sleepers along track (rail), lights along kerb (road). The spacing rule is metadata in ad_pattern_rule; the compiler multiplies at compile time. Resize the parent → pattern recalculates automatically.

The compound interaction: ASI resize (§8) → container validate (§9) → pattern regenerate (§10) → one recompile → correct output. Three rules, zero manual adjustment. This is what no visual editor offers: the model re-proves itself after every edit.


Construction Technology Stack

┌─────────────────────────────────────────────────────────┐
│              CONSTRUCTION TECHNOLOGY STACK               │
├─────────────────────────────────────────────────────────┤
│                                                         │
│  DESIGN EXPLORATION (upstream)                          │
│  ┌─────────────┐ ┌──────────┐ ┌───────┐ ┌──────────┐  │
│  │  Snaptrude  │ │  TestFit │ │ Arkio │ │  Hypar   │  │
│  │  (sketch→3D)│ │ (AI site)│ │ (VR)  │ │ (gen.des)│  │
│  └─────────────┘ └──────────┘ └───────┘ └──────────┘  │
│                                                         │
│  BIM AUTHORING (midstream)                              │
│  ┌─────────────┐ ┌──────────┐ ┌───────────┐           │
│  │    Revit    │ │ ArchiCAD │ │  Bonsai   │           │
│  │ (parametric)│ │ (arch.)  │ │ (IFC-nat.)│           │
│  └──────┬──────┘ └────┬─────┘ └─────┬─────┘           │
│         └─────────────┴─────────────┘                   │
│                       │                                 │
│                    IFC FILE                              │
│                       │                                 │
│  ┌────────────────────▼──────────────────────────────┐  │
│  │         BIM INTENT COMPILER (downstream)          │  │
│  │                                                    │  │
│  │  IFC → Extract → Classify → BOM → Compile → Prove │  │
│  │  48,428 elements → 700 BOM lines → C_Order        │  │
│  │  77 verbs · 202 witnesses · G1-G6 proven           │  │
│  └────────────────────┬──────────────────────────────┘  │
│                       │                                 │
│                   ERP / PROCUREMENT                     │
│  ┌────────────────────▼──────────────────────────────┐  │
│  │              iDempiere ERP                        │  │
│  │  C_Order → C_OrderLine → Purchase Orders          │  │
│  │  M_Product → M_AttributeSetInstance               │  │
│  │  W_Verb_Node → Manufacturing Instructions       │  │
│  └───────────────────────────────────────────────────┘  │
│                                                         │
└─────────────────────────────────────────────────────────┘

The BIM Intent Compiler occupies a position no other tool — commercial or open source — currently fills. It bridges the design world (IFC models) and the construction world (ERP procurement). The visual editors make buildings easy to imagine. This compiler makes them possible to verify, procure, and build.


The Paradigm Shift: Semantics as Source of Truth (2026-03-18)

A 10 KB semantic file defines a building that would be a 200 MB IFC file. The geometry is never stored in the project — it is compiled on demand from shared catalogs. The project file is just: "use these templates, in this arrangement, with these overrides."

The Industry's Structural Problem

Every BIM tool stores geometry as the source of truth. An IFC file IS the building — geometry, relationships, properties, all in one monolithic file. Lose the IFC, lose the building.

Consequences:

  • Version control is impractical. Binary diffs of 200 MB files are meaningless. Teams use "v3_final_FINAL.ifc", not semantic diffs.
  • Collaboration requires full file exchange. Every stakeholder gets the entire model, even to change one room width.
  • Variants require full duplication. 100 design options = 100 × 200 MB.
  • Regulatory review is opaque. Reviewers receive geometry and must reverse-engineer intent.
  • Storage scales linearly. 1,000 projects × 200 MB = 200 GB, mostly duplicated standard components.

The Inversion

The BIM Intent Compiler inverts this. Semantics are the source of truth. Geometry is a compiled artifact — disposable, regenerable.

TRADITIONAL BIM:
  Geometry (200 MB)  ←  THIS is the building

BIM INTENT COMPILER:
  YAML + Order + ASI (10 KB)  ←  THIS is the building
  References:
    component_library.db (500 MB, shared across ALL projects)
    {PREFIX}_BOM.db (10 MB, curated BOM templates)
  Compiled output:
    output.db (50 MB, always regenerable, disposable)
Layer What it stores Size
YAML Building identity — type, storeys, discipline, jurisdiction ~2 KB
C_Order + C_OrderLine Arrangement — which templates, what configuration ~5 KB
ASI (M_AttributeSetInstance) Per-instance overrides — this room 4500mm, that bed +300mm right ~3 KB
Total project file Complete building definition ~10 KB

The compiled output is disposable. Delete it and recompile. The semantic file + shared library reproduces the building exactly (enforced by spatial digest tamper seals).

The Analogy Map

This model exists in every mature engineering discipline. BIM is the outlier.

Domain Source (versioned) Compiler Output (disposable) Shared Library
Software .java, .py javac, gcc .jar, .exe Maven Central
Publishing .tex pdflatex PDF CTAN packages
Music MIDI Synthesizer .wav Sample libraries
Manufacturing BOM + Work Order Factory/MRP Product Product Master
Chip Design Verilog Synthesis GDSII Standard cells
BIM (traditional) None — geometry IS source None IFC IS output AND source Embedded per project
BIM Intent Compiler YAML + Order + ASI 12-stage pipeline output.db component_library.db

BIM is the only major engineering domain that ships compiled output as source of truth.

Concrete Implications

Version control — semantic diffs:

Traditional:  200 MB binary blob → meaningless diff
BIM Compiler: -  width_mm: 4000
              +  width_mm: 4500  → 3 lines, semantically clear

Collaboration — share semantics, compile locally: Architect shares 10 KB. Each discipline compiles against shared library. No 200 MB transfers.

Variants — fork the order, not the model: 100 variants = 100 × 10 KB = 1 MB. Not 20 GB.

Regulatory submission — machine-verifiable: Submit semantic file + library hash + validation report. Reviewer recompiles and verifies independently. Reproducible compliance.

Storage — 400:1 reduction: 1,000 projects = 10 MB semantic + 500 MB shared library = 510 MB. Not 200 GB.

Three-Tier Persistence (BIM_Designer.md §17.10)

The ERP foundation enables clean data governance:

Action Frequency Writes to Deliberation
Save Frequent .blend file (Blender native) Low — just persist
Recall As needed Nothing (reads previous variant) None — browse
Promote to BOM Rare {PREFIX}_BOM.db (new m_bom) High — governance gate

The BOM catalog stays curated — only proven, validated, owner-signed designs enter. This is the iDempiere Document Process pattern: Draft → In Progress → Complete.

The Flywheel

EXTRACT (Rosetta Stones) → prove compiler works
    ↓
DESIGN (Generative) → new buildings from catalog
    ↓
VALIDATE (PlacementValidator) → machine-verifiable compliance
    ↓
PROMOTE (Governance Gate) → proven designs enter catalog
    ↓
CATALOG GROWS → more templates → more design options → ↑

Each promoted design enriches the catalog. A richer catalog enables more combinations. The marginal cost of each new building approaches zero.

What This Enables

AI-Assisted Design: An AI generates YAML + Order + ASI — text, not geometry. The compiler handles 3D. PlacementValidator ensures compliance.

Mass Customisation: 5 base templates, buyers customise via ASI. Each variant is 10 KB. The factory (compiler) produces unique geometry per buyer.

Digital Building Passport: The semantic file (YAML + Order + ASI + library hash + spatial digest) is the building's machine-readable passport. Survives the full lifecycle: design → construction → operation → demolition.

Federated Compilation: Each discipline maintains their own Order against shared catalogs. Federation compiler merges. Clash resolution is semantic: adjust the Order, not the mesh.

Machine-Provable Compliance: The Inference Engine produces a proof tree for every approve/promote decision. Regulators don't review geometry — they verify the proof chain: "Room BD_01 passes UBBL s33(1) because width 3100mm

= minimum 3000mm (AD_Val_Rule 102, jurisdiction MY)." Audit trail is data, not screenshots.

Prior Art Comparison

System Approach Differs from BIM Intent Compiler
Grasshopper/Dynamo Parametric scripts → geometry Scripts per-project, no shared catalog
BIMserver Delta-based IFC storage Still geometry-centric deltas
Hypar (defunct) Cloud parametric generation No ERP BOM catalog, no compilation
Flux (defunct) Data pipeline between tools Data transform, not compilation
TestFit AI layout optimisation Layout is output, not compilable source
Speckle BIM data platform Transport + versioning, geometry-centric

The BIM Intent Compiler uniquely combines: 1. ERP product catalog (shared, curated BOMs) 2. Order-based instantiation (thin semantic references) 3. Deterministic compilation (geometry generated, not stored) 4. ASI overrides (minimal per-instance data) 5. Governance gate (Promote to BOM, dangles check) 6. Machine-verifiable compliance (PlacementValidator + spatial digest) 7. Symbolic inference engine (dependency DAG + proof tree + citation chain)

No existing BIM tool or standard combines all seven.


Current Progress (2026-03-20)

Milestone Status
7 Rosetta Stones (4 building + 3 infra) SH, FK, DX, TE, BR, RD, RL (counts in PROGRESS.md)
SH 9/10, FK 9/10, BR 10/10, RD 4/4, RL 4/4 DX 7/10, TE 8/10 (pre-existing)
Domain-agnostic pipeline proven Same code compiles houses, terminals, bridges, roads, railways
ERP architecture designed Discipline hierarchy, verb→AttributeSet, Val_Rule
Formula compression TILE, ROUTE, FRAME, CLUSTER — 93% compression on rail
77 BIM COBOL verbs, 166+ witnesses Pipeline: 12 stages, seal v20 (74 files INTACT)
BIM Designer Phase G (G-1..G-7 DONE) Design Mode, BBox renderer, Save/Recall, BOM Chooser, Assembly Builder
Infrastructure UI filtering FacilityType enum, snap() with facility type, 30 infra rules
Terrain-following placement (PoC) PlacementContext, AlignmentContext, TerrainSnap, contour-follow on 689-point survey
204 witnesses GREEN 22 infra filter + 16 terrain context + 7 vocabulary + 3 contour
Infrastructure UI filtering FacilityType enum, snap() with facility type, 30 infra rules
PlacementValidator + Inference Engine 63 rules (33 building + 30 infra), dependency DAG + proof tree
ReportDAO interface 8 report types (4D-7D), 8 record types, thin bridge pattern
33 infra products in component_library.db Bridge piers/decks, road courses, rail sleepers — registered by ExtractionPopulator
Semantic Source of Truth paradigm YAML + Order + ASI = 10 KB building definition
216/216 Designer tests GREEN 26 test classes
WF-BB §26 Wireframe-First 25 reqs, 8 CODE DONE, 4 STUB, 13 SPEC ONLY. Per-object BOUNDS, peek popup, orientation markers.
4 new backend verbs getElementMetadata, getChain, costOfChange, moveChain — all compile clean
Scorecard: 31/36 +4 from Tier 1: 6D=2 (carbon DAO), 7D=2 (FM DAO), CR/Audit=2 (changelog), 3D=3 (Blender native). Nearest competitor: 9/36.

What's Easy to Nail Next (effort vs scorecard impact)

Ordered by lowest effort → highest impact. Each item is a bounded task.

Tier 1 — DONE (2026-03-20) ✓

Item Before After What was done
6D Sustainability 1* 2 SustainabilityDAO + V010/V010b migration. BOM rollup via carbon_kg_per_unit on M_Product. 5 witnesses GREEN.
7D Facility Mgmt 1* 2 FacilityMgmtDAO — maintenance schedule, lifecycle cost, asset register. 5 witnesses GREEN.
CR/Audit 1* 2 ChangelogDAO + V011 migration + interceptor on save(). MOVE/RESIZE/PLACE/DELETE diff + undo. 6 witnesses GREEN.
3D score 2 3 Native via Blender viewport (Federation addon + WF-BB).

Tier 1 total: +4 points (27→31/36). 14 new witnesses, 231 total Designer tests GREEN.

Tier 2 — Two Sessions Each (existing stubs → wired)

Item Current Target Effort What to do
Cost engine (5D live) 3 (offline) 3 (live) 4 hrs Wire costOfChange stub to M_Product_PO.PriceStd. BOM diff = old positions → new positions → delta lines → sum unit costs. Data already in component_library.db.
Chain highlight Stub Working 3 hrs Wire getChain to elements_meta.system_id. GPU batch per chain in chain colour palette. Federation DB already has system_id from IFC extraction.
Ghost drag Spec Working 6 hrs Modal operator: intercept grab, freeze originals as WIRE, track bbox proxy, commit/cancel. The hardest UX piece — but bounded: one modal operator + the existing bbox GPU code.

Tier 3 — Multi-Session (new infrastructure)

Item Current Target Effort What to do
R_Request flow Spec Working 8 hrs R_Request table DDL. moveChain detects cross-discipline impact. Creates CR with attachments. DocAction lifecycle for approve/reject/void. Notification to Blender.
Multi-user sessions Spec Working 10 hrs AD_User + AD_Session tables. Login flow in connect operator. Sync timer polls for other users' changelog entries. Conflict detection on concurrent edits.

The Compound Effect

After Tier 1 (DONE) + Tier 2 (cost engine only):

Score: 31/36 (Tier 1 DONE) → 31/36 with live cost — nearest competitor: Revit at 9/36
Unique capabilities nobody else has:
  - Live cost-of-change during drag
  - BOM factorisation (73x compression)
  - Spatial proof (G1-G6 Rosetta Stone gate)
  - Wireframe-first interaction (bbox=working mode)
  - ERP-native output (C_Order → procurement)
  - Symbolic inference (dependency DAG + proof tree)
  - Domain-agnostic (houses + terminals + bridges + roads + railways)
  - Audit trail (who changed what, when, undo-able)

The gap between this project and any competitor is not 10% — it is categorical. They solve design. This solves construction.


Cross-references: BIM_Designer.md — GUI architecture (§17 Design Mode, §18 UX Strategy) BIM_Designer_SRS.md — UX requirements, user journeys, Inference Engine (§14), WF-BB Protocol (§26) TerminalAnalysis.md — forensics + ERP architecture InfrastructureAnalysis.md — bridge/road/rail domain mapping MANIFESTO.md — ERP world view bim_designer_erd.html — interactive ERD (4 tabs) BIM_Designer_UserGuide.md — setup + usage guide (v0.4)