Risk assessments
Classified, extracted and linked back to source evidence for reviewer control.
RAMS document automation
AI RAMS document automation with human approval
DocBeaver helps contractors prepare, review and control risk assessment and method statement documents from repeatable job data.
The workflow drafts from approved wording, job records, site information and evidence documents, then routes exceptions for competent review before release.
25-45%
Target reduction in repetitive RAMS and site-document preparation
Document inputs
Real documents this workflow is built around
These are the source files DocBeaver expects to map during an audit and prototype. The implementation can start with a narrow subset, then expand as extraction quality and review rules are proven.
Method statements
Classified, extracted and linked back to source evidence for reviewer control.
Permits and inspection sheets
Classified, extracted and linked back to source evidence for reviewer control.
Site details and job packs
Classified, extracted and linked back to source evidence for reviewer control.
Training and competence evidence
Classified, extracted and linked back to source evidence for reviewer control.
Photos, reports and prior approved RAMS
Classified, extracted and linked back to source evidence for reviewer control.
Manual bottlenecks
Why this workflow is a strong automation candidate
Step 1
Teams repeatedly copy approved wording into similar RAMS documents.
Capture job information, site details, templates, prior RAMS and supporting evidence.
Step 2
Job-specific hazards, site details and equipment lists are gathered manually.
Extract task, location, plant, materials, personnel, hazards and required controls.
Step 3
Reviewers need to check whether required evidence and controls are present.
Draft RAMS sections from approved wording and current job context.
Step 4
Version control becomes difficult when RAMS drafts move through email and folders.
Check required training, certificates, permits and evidence attachments.
Extraction and checks
Fields extracted and validation checks performed
The automation should produce reviewable data, not a black-box answer. Every important field or exception needs a source link, confidence signal and review route.
| Extracted fields | Validation checks |
|---|---|
| Project, site, task, date, supervisor and work package | Required sections present |
| Hazards, controls, PPE, plant, materials and access requirements | Template version and approved wording checked |
| Personnel, training, competence and certificate references | Training, certificate and competence evidence present |
| Permit needs, inspection requirements and emergency arrangements | High-risk activities routed for review |
| Reviewer, approval status, version and release date | Site-specific hazards included |
Workflow outputs
What the implementation should produce
DocBeaver normally starts with a controlled workflow output: summaries, exception queues, review files, dashboards or proposed system updates. Direct writes into operating systems should be added only after review rules are proven.
- Draft RAMS document
- Missing evidence list
- Reviewer exception queue
- Version and approval log
- Site document pack
FAQ
Common questions
Can AI approve RAMS documents?
No. DocBeaver designs RAMS automation to prepare drafts and checks, with competent human review and approval retained.
Can this reuse existing RAMS templates?
Yes. Existing approved templates and wording can be used as controlled source material for repeatable document preparation.
Assess this workflow using your real documents
Start with a focused audit of document types, source systems, manual checks, exception rules and review requirements.