I’m Cleber, an estimator with a background in architecture and design management. I connect drawings, commercial decisions and the systems people use to get work done.
Explore my workCustom estimating skills, calculated construction programmes and software shaped around real business rules.
Explore the systemsConstruction problems rarely sit in one discipline. My strength is following the connections between design, cost, people and delivery, then making them easier to manage.
Start with the information. Make the gaps visible.
My architectural background helps me see how a building comes together, not just what appears on a quantity sheet. I look for the interfaces, missing information and construction constraints that can become commercial problems later.
That means questioning the scope early, aligning trade packages and making assumptions visible before they become part of a tender price.
A lower price is only useful when the scope still works. I compare trade offers, test material and design alternatives, and bring the cost implications back to the people making the decision.
I use the same approach with technology: define the problem, model the time and cost involved, and establish what would need to improve for the investment to make sense.
A tender board, a production schedule and a delivery team can each look organised while still working from different information. I focus on the points where information changes hands.
Clear ownership, shared data and sensible checkpoints help people see what is ready, what is missing and who needs to act next. The process needs to fit the team’s actual capacity.
Automation works best after the process is understood. I look for repeated manual work, inconsistent naming and avoidable re-entry, then standardise the information before connecting the tools.
Adoption matters as much as configuration. A practical pilot, clear instructions and feedback from the people using the system help make an improvement last beyond handover.
Three examples across business cases, pre-construction operations and manufacturing data. Each starts with a practical problem and connects the technical work to its commercial purpose.
Meeting minutes, action registers and follow-up instructions consumed time across project teams. The opportunity was clear, but choosing an AI tool required more than a convincing demonstration.
My contributionI developed a comparative business case for AI meeting intelligence, assessing Fireflies, Otter.ai, Jamie, Read.ai and Plaud. The evaluation considered capture quality, construction-site conditions, Microsoft Teams and Procore integration requirements, data handling and licensing at scale.
I translated the potential time savings into a financial model so the proposal could be discussed with IT and delivery leadership on a commercial basis.
The assessment brought together operational requirements and the economics of adoption: how meetings were recorded, how actions reached the right person, how the tool would fit the existing software environment and what a rollout would cost.
The financial case used a 300-seat scenario and a three-year horizon. The figures shown are projected business-case outputs, rather than a claim of realised savings.
Opportunities, estimating and factory planning were spread across different teams. Information had to be requested again at handover, and tender commitments were difficult to reconcile with production capacity.
My contributionI designed a connected pre-construction workflow in Monday.com, with six stages, defined responsibilities and automated board and task creation. The structure linked tender development with resourcing, review, submission and the transition into production.
A mid-bid review made scope and pricing risks visible while there was still time to act. Capacity views brought factory availability into the tender conversation earlier.
Task generation reflected the tender’s scope and value. Rather than asking each estimator to recreate a process from scratch, the workflow provided a consistent starting point and clear review gates.
The important connection was between the promised delivery date and the production resources needed to meet it. Shared views helped teams work from the same information through handover.
Part codes had become long and inconsistent. The same component could be difficult to recognise across the design model, procurement records and factory labels, creating friction between drafting and production.
My contributionI reworked the classification and naming structure around shorter, consistent parametric tags. The aim was to make component data understandable and reusable across Revit families, Excel master data, NetSuite and Tillit MES.
This was a design-management problem as much as a data problem: the system needed to describe what was being built in a way that both designers and production teams could use.
The work started with the information itself: what identified a component, which attributes needed to be retained and how the naming structure could stay consistent as the product library grew.
That common structure supported the connection from the Revit library through Excel and Celigo into NetSuite and Tillit, reducing the need to reinterpret the same component at each stage.
Architecture taught me to understand the whole. Design management taught me to coordinate it. Estimating brings the commercial consequences into focus.
Managing commercial tenders end to end, from enquiry and cost planning to tender deliverables, post-tender negotiation and award. Bringing design understanding and systems thinking into the estimating process.
Coordinating commercial and modular bids, subcontractor market testing and mid-bid reviews, alongside business cases and workflow improvements.
Coordinating modular projects, leading Revit adoption and improving project-management processes. Leading the ISO 9001 certification initiative and connecting design information with production requirements.
Producing detailed electrical drawings across concurrent commercial projects. Standardising drawing templates and building an internal database to reduce repeated design errors.
For conversations about estimating, pre-construction, or making construction processes work better.