Bildeasy

The messy workflow

Construction lending runs on trust that's hard to verify. A bank approves a loan and releases each tranche believing the project is actually at the stage the paperwork claims - across dozens of branches, with no consistent technical check. The blunt version: stop approving loans you can't verify.

Bildeasy puts a verification layer between the project and the lending decision: branch teams submit project files, licensed professionals verify the technical inputs, and the bank gets a consistent, audit-ready record at the two moments that matter - pre-approval and pre-disbursement.

Inputs

• Project files & documentation from branch teams
• Site evidence and observations from licensed professionals
• Standards, templates and project context (reference set)

Output

• Technical verification records - 214+ compliance inputs reviewed
• Pre-approval verification assessments
• Disbursement-readiness confirmation
• Audit-ready documentation with a professional input trail

System flow

The AI layer - and its limits

AI organises submitted evidence into consistent verification records - extraction, classification and structured analysis. It does not verify or approve: a licensed professional confirms the technical inputs and the bank makes the lending call. The AI standardises; humans hold the accountability.

Built on the OpenAI Assistants platform as an agent with a vector store of reference files - standards, templates and project context. That store is retrieved (RAG, via file-search tool calling) before every report generation, so each report is grounded in the relevant source material rather than the model's memory alone.

Guardrails

• Licensed-professional verification is structural - AI never signs off
• Clear separation of roles: branches submit, professionals verify, the bank decides
• Two verification moments - pre-approval and pre-disbursement
• Every record traces to its source evidence and the professional who verified it
• Audit-ready trail by design

Status

Live, built with licensed professionals and lending workflows. As founder I led product strategy, the AI verification logic, prompt architecture and the verification-record design. Private walkthrough available on request.

What I learned

The lesson was about framing. The hard problem wasn't producing better construction reports - it was making evidence verifiable enough that a bank could lend against it. Once I treated the verification record as the unit of value, the decisive design choice followed: keep a licensed human in the loop so the output carries real accountability, not just AI confidence.