What we do

Most real estate, hospitality and construction firms have already tried AI. A tool was bought, a pilot was run, and six months later it sits unused while the next conference-room conversation starts the cycle again. Very few get what they expected from it, and the reason is rarely the technology. It is that AI was dropped on top of workflows, documents and data that were never organised to support it.

We help firms in the built environment put AI to work in the parts of the business where it actually pays: business development and proposals, document and contract review, project reporting including carbon and ESG reporting, feasibility and market analysis, and making decades of institutional knowledge, the project files, the specs, the lessons learned, usable by the people who need them. We start with the firm’s knowledge, not with a tool.

The difference is that we are operators in these industries. We build panel systems, deliver projects and develop hotels. We use these tools every day in our own work, and we know which tasks in a developer’s, operator’s or AEC firm’s week are worth automating, which are worth augmenting, and which should be left to people.

Who it’s for

Real estate developers and owners with knowledge scattered across drives, inboxes and people’s heads
Hotel operators, management companies and hospitality investors looking at AI for development, asset management and operations
Architecture, engineering and construction firms under pressure to produce more proposals, faster designs and tighter reporting without adding headcount
Building product manufacturers who want AI in sales, specifications and technical support

How we work

Assessment: workflows, documents, data, tools already in use, and where time and money actually go
Knowledge architecture: organising the firm’s own documents, project history and expertise so AI tools can draw on it reliably
Roadmap: automate, augment or leave alone, prioritised by payoff and risk, with a human in the loop on anything touching contracts, specifications, safety or money
Pilot: one workflow, one team, measured before and after on the firm’s own data
Roll-out and training: extend what worked, teach the team, set the governance
Ongoing advisory as the tools and the firm’s needs change

What you get

An AI roadmap with priorities, costs and a clear view of what not to do
A working pilot on a real workflow, with results measured
A knowledge base the firm owns and its tools can use
Vendor and partner selection from people who have no tool to sell you
A team that knows how to use what was built

Partners and tools

We build on Anthropic’s Claude as our primary AI platform and partner with RUH.ai for specialist knowledge tools. We recommend and integrate other tools where they fit. We do not resell any of them.

Example engagements

AI strategy for an integrated AEC firm. Omicron AEC, a Vancouver integrated architecture, engineering and construction firm, wanted an AI strategy. We designed a knowledge architecture built on the firm’s own project history, with RUH.ai as one component, so that proposals, reviews and reporting could draw on decades of work.

Our own firm. Landca runs its business development, research, proposal writing and this website on the same approach we recommend to clients: Claude as the platform, our own knowledge organised so the tools can use it, and people making the decisions.

AI Strategy & Implementation