Skip to content
All projects
Dubai MunicipalityGovernmentUAE2026

AI feasibility analysis, extraction and document generation for Dubai Municipality

An end-to-end feasibility pipeline — extract, populate, calculate, benchmark — replacing weeks of manual document handling.

The challenge

Feasibility assessment inside a municipal authority means working through large volumes of dense technical and regulatory documentation, where the material that determines a decision is buried across hundreds of pages — and arrives in whatever format the submitting consultancy chose to use.

The work does not stop at reading. Every assessment produces downstream artefacts: financial sheets, standardised forms, calculation tables. These were being filled by hand, transcribing figures out of one document and into another, which is slow and exactly the kind of task where transcription errors quietly enter the record.

Benchmarking was harder still. Judging a proposal against ISO, WHO and other international standards requires knowing which clauses apply and finding the corresponding evidence in the submission — expert work that varied depending on who performed it.

Our approach
01

Extract from any source

The platform ingests both third-party feasibility studies submitted by external consultancies and the authority's own internal documents, parsing inconsistent structures into a common representation rather than requiring a fixed template.

02

Populate the downstream artefacts

Extracted values flow directly into the forms and sheets each feasibility requires. Financial sheets are filled and their formulas applied, so the calculation chain is derived from the source document rather than retyped from it.

03

Benchmark against world standards

The analysis layer assesses each feasibility against international frameworks — ISO, WHO and other recognised standards — identifying which requirements are met, which are unevidenced, and where the submission falls short.

04

Generate the study

The system produces the standardised feasibility report, structured for review rather than blind acceptance. The value is a reviewer starting from a complete, benchmarked draft instead of a blank page.

Source · third-party feasibility
Flagship · Dubai Municipality

It reads the study.
Then does the work after it.

Feasibilities read, forms and financial sheets filled and calculated from the source, then benchmarked against ISO and WHO standards.

Financial sheet · auto-populated
  • B4Capital cost48,200,000
  • B5Operating cost3,100,000
  • B6Discount rate6.0%
  • B7NPV =NPV(B6,B4:B5)38,940,220
Benchmarked against world standards
  • ISO 31000
  • WHO air quality
  • ISO 14001
What we built

The system, in specifics.

AI extraction from third-party feasibility studies and internal feasibility documents, handling varied formats and structures.

Automated population of the forms and sheets each feasibility requires, driven by the extracted data.

Financial sheet completion with formulas applied, so calculations derive from the source rather than manual transcription.

Feasibility analysis benchmarked against international standards including ISO, WHO and other recognised frameworks.

Automated summarisation of critical sections within large regulatory and technical filings.

Standardised feasibility study generation, removing structural variance between assessments.

Outcome

What changed.

Extraction from both external consultancy submissions and internal documents

Forms and financial sheets populated and calculated automatically from source

Transcription errors removed from the calculation chain

Feasibilities benchmarked consistently against ISO, WHO and other world standards

Standardised reporting structure across all submissions

Delivered for a government authority

Next

Related work.

AI Takeoff Estimator — Construction takeoff and bidding from architectural PDFs, in minutes
Flagship

AI Takeoff Estimator

Multi-client programmeConstructionGlobal

Construction takeoff and bidding from architectural PDFs, in minutes

Reads architectural PDFs, detects the scale on its own, measures only the trade you work in, and returns quantities, labour hours and a bid — then pushes the work into your CRM.

Computer VisionDocument AIDeep Learning
Read case study
Flagship

Moving Estimator

Umzugsauktion GmbH & Co. KGLogisticsGermany

A walkthrough video in, a removals quote in seconds

The customer films their own home. Computer vision identifies and counts every object, estimates dismantling, handling and transport time, and returns a priced quote.

Computer VisionObject DetectionDeep Learning
Read case study
Flagship

Outcall Review Agent

Multi-client programmeEnterpriseGlobal

Automated outbound voice agent for customer feedback and reviews

An AI agent that calls customers after service, holds a natural feedback conversation, and routes happy customers to a public review.

Voice AILLMsSpeech Recognition
Read case study