Engineering Answers, With the Source Attached
A GenAI-powered assistant that lets authorised users retrieve information from project documents through natural-language queries, with context-aware answers supported by references to the original documents.
Specs, BOQs and vendor documents, scattered across files and repositories
A real estate and construction firm managed large volumes of documentation: engineering specifications, Bills of Quantities (BOQs), contracts, vendor documents, inspection reports and revised technical documents. Teams frequently needed to locate specific requirements, verify approved document versions, compare revisions and prepare technical summaries. Searching manually across files and repositories took valuable time.
Want Source-Referenced Answers From Your Own Project Documents?
We'll scope a pilot around your exact specs, BOQs and contracts — natural-language search with source references — with clear success metrics before any production commitment.
Key capabilities
Intelligent document search
Searches specifications, BOQs, contracts, inspection reports and project documents without opening multiple files; filters by project, document type and metadata.
Technical question answering
Answers engineering and project questions using approved documents, gives source references including document names and pages, and identifies missing, conflicting or insufficient information.
Document revision comparison
Compares versions of specifications, BOQs and contracts, and highlights changes in requirements, values and clauses.
Automated summaries and checklists
Summarises lengthy technical documents and extracts requirements into structured checklists.
Illustrative use case
An engineer on a commercial building project needs to verify HVAC insulation requirements and understand the latest specification changes. Instead of searching several documents, the engineer queries the assistant, which retrieves the relevant sections, identifies the referenced document versions, summarises the changes and provides source references. The engineer validates the requirements and decides whether related BOQ items need review.
Business value
- Faster retrieval of engineering and project information
- Less manual effort in search and summarisation
- Better visibility of changes across revisions
- Better traceability through source-referenced answers
- More efficient checklists and handover documentation
Secure knowledge access
Access restrictions based on user permissions, plus security controls and audit logging. A Retrieval-Augmented Generation (RAG) architecture retrieves relevant information from approved documents before generating responses — built on Amazon Bedrock, Amazon S3, Amazon OpenSearch and Amazon Textract, with appropriate identity, encryption and monitoring controls.
An engineering team that ships grounded RAG systems, not slide decks
AWS Advanced Tier Partner
Certified cloud and AI delivery, so your knowledge assistant runs on infrastructure built to AWS Well-Architected standards from day one.
Pilot-first engagement
We scope, build and validate against your real specs, BOQs and contracts before you commit to a production rollout.
Source-referenced, RAG-grounded answers
A Retrieval-Augmented Generation architecture retrieves relevant information from approved documents before generating a response, with document and page references attached.
Access controls and audit logging
Access restrictions based on user permissions, plus security controls and audit logging, built on Amazon Bedrock, S3, OpenSearch and Textract.
Trusted by forward-thinking teams
AWS-Certified Experts Delivering Cloud Excellence.
More Real Estate AI Solutions
Want Faster Answers From
Your Project Documents?
Tell us what your teams search for most — specs, BOQs, contracts — we'll help you scope a RAG assistant with source-referenced, access-controlled answers.