We build custom AI systems that help engineering teams manage technical documents, reports, and workflows more efficiently.
Engineering and technical teams across Metro Vancouver spend significant time managing documentation, reports, and internal information workflows that slow down project execution.
These challenges are common across engineering, architecture, and other technical teams, and increase as project complexity and documentation volume grow.
We build custom AI systems that help engineering teams reduce time spent on technical documentation, reporting, and repetitive internal workflows.
Instantly retrieve information across reports, specifications, and internal documentation using natural language queries.
Generate structured drafts of reports, summaries, and project documentation based on your existing materials and templates.
Compare versions of specifications, vendor proposals, and technical submissions to surface differences in requirements, pricing, and scope.
Automate repetitive processes such as document handling, internal coordination, and project-related administrative tasks.
We tailor AI systems for different parts of the engineering and technical industry.
Get in touch to explore how AI could fit into your engineering operations and workflows.
Common questions about how AI fits into engineering and technical work across Vancouver and Metro Vancouver.
Engineers waste a surprising amount of time simply trying to locate the information required to complete a task. AI can assist by ingesting drawings, calculations, specifications, and standards, and allow engineers to ask it to find specific information buried within documentation. It can also produce draft reports based on notes, compare vendor proposals, and much more related to technical documentation.
Yes, AI can search zoning bylaws, building codes, and project precedents to surface relevation requirements during early design. Architecture firms in Vancouver, Burnaby, and across the Lower Mainland are beginning to use AI to speed up feasibility studies and client deliverables.
AI in construction engineering workflows can automate document reviews, RFIs, submittals, scheduling, cost tracking, and progress reporting, reducing administrative overhead and project delays. It can analyze drawings, contracts, and site data to identify risks, detect clashes or inconsistencies, and improve project planning. AI assistants can also help engineers quickly search specifications, standards, and historical project information to support faster decision-making.
Yes, there are AI tools for mechanical and electrical (MEP) consultants that focus on searching drawings, specs, RFIs, submittals, and BIM models using natural language. They help with tasks like code compliance checks, clash detection insights, equipment spec lookup, and retrieving information from past projects.
Yes. AI can extract field data, lab results, borehole logs, and regulatory references then draft technical reports following your firm template. Environmental and geotechnical firms across British Columbia are beginning to implement custom AI tools to cut report preparation time while keeping every output under their review.
AI can speed up RFP and proposal work by extracting requirements from the document, building compliance matrices, and mapping them to your past project experience. It can draft first-pass technical and commercial responses using approved content, then tailor language to the client and project context. It also helps ensure consistency, reduces missed requirements, and can pull supporting evidence from past proposals, case studies, and project databases.
Yes. We can integrate AI tools with project and document platforms via their APIs, enabling search, summarization, and drafting directly within the systems your engineers already use. For CAD tools, we typically work with exported outputs (such as PDF drawings or reports), since this is the most reliable approach. Direct integration into CAD applications is also possible, but it is more complex and depends on the specific software environment.
AI can be accurate enough for technical engineering support tasks like document search, summarization, drafting, and cross-referencing standards, especially when it is grounded in your own project data and validated sources. However, it is not reliable enough to replace judgment by EGBC engineers for calculations, design decisions, or safety-critical work without human review. The best use is as an assistant that accelerates work while engineers remain the final authority.
Focused tools usually go live within a few weeks. Mid-sized rollouts run 1 to 3 months, and full multi-system implementations take 3-12 months or longer.
This depends on the complexity of the project, what hardware would be required, and how many hours it takes to develop. Custom AI tools for real estate that are simple and mostly text based typically cost $10,000 - $50,000, while more complex AI implementations can cost $50,000 - $100,000+.