CORA
Cost estimation for services and proposals, built on historical data.
Software and data engineering in one project: extract and transform historical service and proposal records, model them relationally, and use that history to estimate the cost of new work — instead of starting each estimate from a blank sheet.
Proprietary system — no source code is shared.
- Status
- In development
- Period
- June 2026 — present
- Context
- Private project
- Domains
- Estimation · Data engineering · ETL
The problem
Cost estimates were built from scratch each time, leaning on the experience of whoever prepared them. The historical record that should inform them existed, but it was scattered across exports and unusable in that shape.
Approach
- 01Built the extraction and transformation of historical records into a consistent dataset.
- 02Designed a relational model that makes past work comparable across services and proposals.
- 03Used that history as the basis for estimation, so a new estimate starts from evidence.
- 04Shipped it as a web application, keeping the interface thin and server-rendered.
Architecture
How it is put together.
ETL over historical records
Extraction, cleaning and transformation of heterogeneous historical exports into a coherent schema — the part of the project that took the most care.
Relational modelling in PostgreSQL
A normalised model of services, proposals and costs, designed so estimation queries stay simple.
Django + HTMX
Server-rendered pages with HTMX for partial updates: interactive where it matters, without shipping a front-end framework for a form-heavy tool.
Stack
- Backend
- Python
- Django
- Front end
- HTMX
- Server-rendered templates
- Data
- PostgreSQL
- pandas
- ETL
Outcome
- Turned a scattered historical record into a queryable basis for estimation.
- The extraction and cleaning layer is the bulk of the work: heterogeneous exports, inconsistent formats, and no shared identifiers to join on.
- In development since June 2026 — outcomes will be added once it is in use.