Manage housing projects faster with document intelligence

No that's a hard boundary in how the platform is built. There's no scoring, ranking, or prioritization logic, no automated underwriting calls, and no autonomous recommendations of any kind. The AI's job is limited to reading documents and organizing what it finds; an Admin or Project Manager reviews and confirms every extracted field, with a direct link back to the source page, before it becomes part of your official project record.

The extraction layer is model-agnostic by design, so you're not locked into one vendor. It connects to OpenAI, Google Gemini, Anthropic's Claude, or Vertex AI through a configurable connector, and switching providers is a settings change, not a development project. API credentials are stored securely, with usage tracking and cost controls built into the same layer.

You do. The platform runs inside a cloud environment on AWS or Azure, with every account created and owned under your organisation's name The Dashboard LLC and full credentials handed to you at go-live. Documents, extracted data, and generated reports all live under your cloud account, your access policies, and your backup schedule, not on infrastructure Fullestop retains control of.

PDF, Microsoft Excel (.xlsx), and Microsoft Word (.docx) are all supported from day one, which covers the large majority of term sheets, contracts, financial models, and internal notes that housing teams already work with.

Yes, and that customisation is central to how the platform works rather than an add-on. Both the fields the AI pulls out and the checklist used to flag gaps are fixed schemas your team defines, built around whatever document types matter to you, whether that's term sheets, zoning studies, or underwriting models. An Admin can adjust prompts and schemas directly, with no development work or redeployment required.

Most MVP builds covering document intake, AI-assisted extraction, gap detection, and the dashboard interface reach code complete in six to ten weeks from kickoff, delivered through an agile process with review checkpoints every two weeks. If your schemas or checklists carry unusual complexity, Fullestop flags that during discovery, before any build work begins, so timeline expectations are set upfront.

It takes the documents you've uploaded for a project and checks them against a checklist you've defined, then produces a report listing exactly what's missing or doesn't line up. There's no scoring or ranking involved the goal is simply to put gaps in front of your team early enough to fix them, rather than discovering them during a financing closing or compliance review.

Access is deliberately simple in this build: two roles, both set up manually by an administrator, with no self-service sign-up. Admin and Project Manager accounts can upload documents, run AI extraction, and export reports. Viewer accounts get read-only access to dashboards, extracted data, and gap reports. Additional roles are a later-phase conversation, not part of this build.

Housing development is where The Dashboard started, but the underlying approach fixed schemas plus a readiness checklist works for any long-dated, compliance-driven real estate project, whether you're deep in feasibility, financing, construction, or years into asset operations.

Drive and SharePoint are fine at storing files, but neither one reads the contents of those files, checks them against a checklist, or produces a gap report. The Dashboard sits on top of whatever storage discipline you already have and adds the layer that actually does something with the documents extraction, validation, and reporting.

Every upload, extraction run, human review, and export is written to an audit log automatically, so you have a complete, exportable trail for compliance reviews or internal audits without anyone having to reconstruct history from memory or old emails.

Start with a discovery call with Fullestop. We'll walk through how your team currently handles project intake, lock down your extraction schema and readiness checklist, and put together a fixed-bid plan for an MVP that typically reaches code complete in six to ten weeks.