About Liquid Chair
A focused consultancy built around technical execution.
We design and build data, AI and software systems, and work alongside client teams to get complex solutions integrated, deployed and operating in practice.
What defines us
Consulting and building belong together.
Good technical work starts by understanding the real problem: the users, workflows, data, systems, constraints and decisions around it. Technology choices follow from that context.
Liquid Chair stays close to that full path. We bring engineering judgment to ambiguous work, communicate tradeoffs clearly, and adapt as contact with users and real systems improves the understanding of what is needed.
Our four disciplines reflect that focus: Data Engineering, Applied AI & Machine Learning, Forward Deployed Engineering, and Software Engineering.
Operating principles
Clarity, proximity, and ownership.
Clarity over theatre
Specific language, explicit tradeoffs, and technical choices that can be explained.
Proximity to reality
Stakeholders, users, systems, and data remain part of the engineering conversation.
Ownership through delivery
The work matters when it reaches production and supports the intended outcome.
Product evidence
Lodgegrid is how we build for ourselves.
Lodgegrid helps travelers narrow hotel options around what matters to a specific trip, compare tradeoffs, and understand recurring guest-review themes. Building and operating it applies the same software, data, AI, and product thinking we bring to consulting work.
Explore Lodgegrid ↗Software engineering
A live decision-support web product with user-facing workflows, comparison flows, and production delivery concerns.
Data engineering
Hotel, location, price, rating, and guest-review information organized into usable decision context.
Applied AI
Review-theme and semantic understanding used to help travelers compare tradeoffs instead of scanning raw listings.
Product engineering
A real system Liquid Chair builds and operates, improved through the realities of product use rather than slideware.
Next step
Bring us the problem that needs to work in practice.
Tell us what you are trying to build, improve, or put into production.