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Reference architecture

Agentic document review for an engineering consultancy

An engineering consultancy compared thousands of specification pages against project standards before every tender, entirely by hand.

Conceptual visualization only

Engagement at a glance

Reference architecture
Discipline: AI / ML
Industry: Engineering and construction
Technology: Agentic AI
Cloud: Microsoft Azure
Region: Illustrative

Specification review effort reduced substantially with human sign-off retained

Objectives

  • Cut review effort on repetitive specification comparison
  • Retain engineer sign-off on every finding before it leaves the firm
  • Keep an audit trail suitable for client and legal review

Data sources

  • Permissioned specification and drawing repositories
  • Internal project standards and clause libraries
  • Historical review comments used as evaluation examples

Architecture and approach

Retrieval over permissioned document stores, tool-using agent with mandatory human approval, full audit trail.

  1. Step 1

    Ingestion

    Documents parsed with layout awareness so clauses and tables stay intact.

  2. Step 2

    Retrieval

    Clause-level retrieval restricted to the projects a reviewer may access.

  3. Step 3

    Comparison

    Agent drafts deviations with citations; no finding is asserted without a source.

  4. Step 4

    Approval

    Engineers accept, edit or reject each finding; rejections feed evaluation.

  5. Step 5

    Reporting

    Approved findings exported as a review pack with references.

Technologies used

  • Retrieval over chunked documents with clause-level citations
  • Tool-using agent with mandatory human approval gates
  • Azure hosting with private networking
  • Structured findings store with reviewer decisions

Security and governance

  • Document-level permissions enforced before retrieval, not after
  • No client content used for model training
  • Every agent action, approval and rejection recorded with user and timestamp

Output

Reported against the objectives set out for this reference architecture.

Review effort

Substantially reduced

Reviewers confirm drafted findings instead of reading everything.

Human sign-off

Required on 100%

No output reaches a client without engineer approval.

Citation coverage

Every finding

Each deviation links to the exact clause.

Lessons learned

  • Rejected drafts were the most valuable evaluation signal in the whole system.
  • Approval gates increased adoption; reviewers trusted a tool they controlled.
Reference architecture illustrating method and architecture only. It is not a verified client project, and no client commissioned it.
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