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Skema

AI-powered BIM knowledge reuse engine for schematic-to-BIM workflows

AI design assistant that captures design knowledge from previous BIM projects and applies it to new designs, enabling architects to generate coordinated LOD 350 BIM models in minutes instead of weeks. Preserves institutional design intelligence through reusable design catalogs and morphing tools.

Not publicly specified raised 📈 Growth Stage

Founded 2021 • Design firms including TVS (Atlanta-based architectural practice) and pilot programs with major architecture firms; claims "100+ design catalogs" in library

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Why This Tool Exists

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The Problem

Architects manually rebuild schematic designs into BIM models during design development, wasting 6-8 weeks per project. Knowledge from previous similar projects is lost, forcing teams to recreate floor layouts, room configurations, and structural systems from scratch. This repetitive work delays project schedules and increases costs.

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The Solution

AI-powered design reuse engine that ingests previous BIM projects, extracts design knowledge (floor layouts, room types, systems), and applies them to new projects. Architects morph existing designs to fit new site constraints. Exports coordinated LOD 350 BIM models to Revit in minutes, eliminating weeks of manual modeling and preserving institutional design knowledge.

How You Use It

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Delivery Method

SaaS Plugin

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Integrations

Revit SketchUp Rhino

Disciplines

Architecture

Project Phases

Schematic Design, Design Development

Project Types

Commercial, Residential, Healthcare, Education, Hospitality, Mixed-Use

Data Transparency

Exactly what this tool uses and how

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Input

What it needs

Required: Existing BIM project (Revit format), New design concept or schematic sketch

Optional: Site context, Sustainability requirements, Proforma metrics, Previous project performance data

Formats: RVT (Revit), SketchUp, Rhino, Web-based sketching tool

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Output

What you get

Format: Coordinated BIM model (LOD 350 native Revit format)

Fields: Room-level geometry and configurations, MEP systems (pre-coordinated models), Structural elements from design catalog, Parameters and properties from source projects, Quantity schedules, Export-ready Revit file for documentation phase

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Algorithm

How it works

Model: Proprietary design pattern recognition and morphing engine (specific ML approach not publicly disclosed)

Accuracy: Not publicly specified (claims efficient room-level geometry and reduction of manual cleanup time)

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Privacy

How your data is protected

Retention: Project-based retention; design catalogs retained for firm-specific reuse (deletion timeline not specified)

Training: Does not train AI models on customer data; design catalogs are firm-specific and not shared across customers

Compliance: Encryption in transit (TLS) and at rest (AES 256 equivalent), GDPR compliant with Standard Contractual Clauses, Breach notification within 72 hours

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API

Integration

Endpoint: Contact vendor for API access

Method: Not publicly documented

Use Cases

• Generate LOD 350 BIM models in minutes from schematic design concepts
• Preserve and reuse floor plate layouts across multiple projects
• Accelerate healthcare design workflows using surgical suite and nursing station templates
• Multi-family residential design standardization with unit morphing
• Reduce BIM modeling phase from weeks to days for early design development
• Leverage institutional design knowledge across geographically distributed teams
• Pre-coordinate MEP systems during schematic design phase

Pricing

Free

30-day trial of Professional tier

Pro

Professional: $199/month (individual); Team Starter Pack: $750/month (up to 5 seats with firm-specific design catalogs)

Enterprise

Enterprise Pioneer: Custom pricing (12+ seats with in-person onboarding, IP management, and product roadmap input)

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📚 Research Sources & Data Quality Last verified: 2026-02-01

Data Sources (10)

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Verified Data (17)

problem, solution, deliveryMethod, integrations, disciplines, projectPhases, projectTypes, yearFounded, maturityStage, customerBase, input-formats, output-formats, pricing-model, privacy-location, privacy-encryption, control-features, useCases

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Not Found (9)

fundingTotal, detailed-algorithm-model, accuracy-metrics, api-documentation, soc2-compliance, rate-limits, data-retention-timeline, specific-employee-count, annual-revenue

Our Commitment: We only include verified data from official sources. If information isn't publicly available, we mark it as "Not publicly specified" rather than guessing.