Knowledge Builder
Turns past know-how
into design intelligence.

What used to be buried in folders is now instantly searchable. Knowledge Builder connects past decisions and insights to current challenges fuelling smarter design and fewer repeated mistakes.

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Unstructured past project data

Drawings Photos Written Reports Handwritten Markups Meeting Minutes
Tektome

Knowledge Builder

Learning from past projects

Knowledge
Builder

Data structuring and integrated management

Structured & searchable knowledge

Experienced Know-how Frequently Used Standard Designs Common Quality Mistakes

Data extraction using natural language

With simple natural language instructions, you can structure data from a wide range of files — such as construction drawings, proposals, photos, meeting minutes, and reports. This allows even non-engineers to configure and extract information themselves.

1Input Prompt
openai-gpt-4-omni
String
Extract the drawing type. Information is usually in the drawing title.
2Extract
Construction drawing — Maple Road 5 first floor plan
3Structure

File Attributes

Drawing Title
First Floor Plan
Drawing No.
A202
First Issue Date
13.06.25
Purpose of Drawing
For coordination
Last Revision Number and Date
Revision: 1, Date: 13.06.25
Level
Level 1
Drawing Type
Floor Plan

Compatible with different formats
using same instructions

Urban Planning Division — Internal Memorandum

Date: 15 March 2023

Prepared by: John Atkinson, Senior Planner

Subject: Preliminary Site Analysis for Proposed Development

Site Overview

  • Project Site: London, Westminster
  • Site Area: 32,878.21 m2
  • Type of Construction: Main building work
  • Road Access:
    • Length: 215.36m
    • Width: 17m

Environmental impact assessments and heritage constraints for the surrounding boroughs are currently under review. This document is intended to summarize the essential spatial and infrastructure information available at this stage.

TENOR INFRASTRUCTURE GROUP
Construction Feasibility Report

Report ID: TKG-NLC-ISL/2024-08

Issued: August 2024

Prepared for: London Borough of Islington

Construction Overview

  • Project name: Tektome High School – New Library Construction
  • Location: Islington, London
  • Site area: 82,142.95 m2
  • Type of construction: New construction

The purpose of this report is to provide an outline of the land allocation, buildable footprint, and initial scope for the library facility adjacent to the main school building.

LocationSite Area (sqm)Construction Type
Westminster, London32,878.81Main building work
Islington, London82,142.95New construction
Richmond, London276,118.84New construction

Formats and attributes can be fully customised depending on your preferences.

When a new document is uploaded, KnowledgeBuilder automatically performs extraction according to your pre-set rules.

Data structuring method

Compared to conventional systems, Tektome KnowledgeBuilder offers higher flexibility and features that better match real-world needs.

Database
Construction
Method

User
Extraction Items
Execution
Conventional System

Requires support from the system department and responses can take time

Only items predefined during the initial database design can be used

Time consuming to run on a frequent basis

RAG System

Provides no structuring capability, only usable as a database

Knowledge Builder

Users canconfigure the database

New Items can be added as neededdepending on the situation and project

Allows data extraction anytimeby simply uploading a document

Integrated knowledge search

Knowledge search is our AI-powered tool allowing architects to quickly find past project insights, drawings, or markups — improving design efficiency, reducing reliance on individual memory, enabling informed decisions with just a natural language query.

Use natural language
search queries

Optimise search with
advanced filtering

Get AI recommendations
from past projects

Search attributes within
images and photos

KnowledgeBuilder in action

KnowledgeBuilder product walkthrough

Success story

Company

Leading Japanese construction company

Problem

Difficulty accessing past drawings, weak knowledge transfer and efficiency

Task

Develop a structured database by extracting a vast amount of custom attributes from drawings, meeting notes, images and other project files to enable advanced search capabilities.

Solution

Past Projects

300 projects over the past 5 years. 600,000 drawings, handwritten markups and images.

Auto Structuring

Set Attributes

Set any attribute for architectural, structural, MEP, etc., drawings. All attributes are customisable by user.

Search

Use natural language queries to search within the vast amount of available data.

Drawings
Stack of construction drawings

Reference designs and how the drawings were made

Project NameBuilding UsageComplete Date
Albion QuartersResidential2022-04
IsarTech HubR&D Center2021-12
Pacific Vista CenterConvention Hall, Hotel2023-10
Horizon TowerOffice, Hotel2010-05
Miradouro ResidenceResidential2018-07
Fulton Labs WestScience Lab2015-11
Rhone RiversideCommerce2025-01
St.Edrick's AcademySecondary School2023-10
Search for schools completed after 2020
Show detailed floor plans of convention halls with conference rooms

Result

Thanks to Tektome KnowledgeBuilder, the construction company efficiently retrieved critical drawings, ensuring seamless knowledge transfer and significantly enhancing operational efficiency.

Start today

Schedule a demo.

See Tektome Knowledge Builder on your own project archive. Tell us a little about your team and we'll set up a personalised walkthrough.

  • Turn past projects into searchable knowledge
  • Grounded in your own drawings and reports
  • No commitment, no setup required

Schedule a demo

We use your data solely to respond to your inquiry and will never share it with third parties without your explicit permission.