Industrial AI · Private Infrastructure · Development-Stage Platform

Engineering document workflows,
grounded in evidence and built for privacy.

AxiOMSphere helps industrial teams draft and review technical documentation for preservation, shutdown, maintenance and asset-integrity workflows — while keeping sensitive source documents on private infrastructure by default.

Discuss a Pilot View on GitHub
Local processing by default Anonymized external evaluation only Human approval required
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Local-first processing
Sensitive document content stays on private infrastructure by default.
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Source-backed review
Recommendations are prepared against traceable standards and guidance themes.
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Human-governed output
Qualified engineering review remains mandatory before operational use.
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Pilot preparation
Development platform preparing for controlled industrial validation.

The challenge

Industrial documentation is too important for untraceable automation.

  • Source materials are fragmented across disciplines, document versions and review histories
  • Sensitive engineering content cannot be submitted uncontrolled to external AI services
  • Procedure maintenance is slow, labour-intensive and difficult to audit after changes

A controlled workflow, not a black box.

  • Local drafting and document review agents working on private infrastructure
  • Benchmark preparation from standards and guidance references retained in the local registry
  • Every output is traceable and retained for qualified human decision-making

How it works

Five stages. Evidence at every step.

01
Context
Retrieve relevant local document context via OCR registry and vector search.
02
Draft / Review
Prepare or analyse technical documentation locally — no source document leaves the environment.
03
Benchmark
Build source-backed review themes and evidence against standards and guidance references.
04
Evaluate
Use approved external evaluation only — anonymized context, no raw project documents.
05
Approve & Learn
Engineer reviews and approves output. Validated cases inform future improvement.
Documents remain on private infrastructure throughout the default workflow.

Initial workflows

Where the platform is being validated.

Internal test scenarios across the following engineering document workflow categories.

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Asset Preservation
Procedure drafting and review for extended shutdown or storage conditions.
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Shutdown & Restart
De-preservation, recommissioning and readiness documentation workflows.
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Maintenance & Reliability
Technical instruction review and evidence-backed gap identification.
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Document Assurance
Structured comments, review matrices and checklist preparation from source requirements.

Privacy architecture

Designed for controlled industrial information handling.

A clear boundary between what stays private and what is permitted to reach external services — and only with controls.

Stays on private infrastructure Default

  • Source documents and project records
  • OCR results and document registry
  • Retrieved project context and RAG results
  • Evidence artifacts and learning cases

External only when authorised Controlled

  • Anonymized research and benchmarking queries
  • Non-identifying evaluation prompts
  • Anonymized technical context for quality scoring
  • No raw customer documents by default
Privacy statement: Sensitive source documents remain on private infrastructure by default. Approved external services are used only with anonymized context for benchmarking, research or evaluation unless separately authorised.

Development status

Built for validation. Preparing for pilot use.

Current capability status, based on internal development and test scenarios.

Multi-agent orchestration workflow Internally validated
Document drafting and review workflow Implemented — internal scenarios
OCR ingestion and document registry Implemented
Evidence and learning-case collection Implemented
Standards and guidance benchmarking In active development
Controlled industrial pilot Preparing

Capability statements reflect internal development and test scenarios unless explicitly stated otherwise.
Internal results will be shared with pilot partners under appropriate agreements.

Startup credits

Seeking credits for controlled validation at scale.

API and cloud credits will help us benchmark local workflows, evaluate anonymized review cases and prepare an industrial pilot — without moving sensitive documents outside the private environment.

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API credits
External benchmark review and anonymized standards and guidance discovery.
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GPU / cloud compute
Controlled local-model inference and evaluation experiments at scale.
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Storage / retrieval
Document metadata and evidence-search scale testing.
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Security / monitoring
Pilot-readiness controls and operational visibility tooling.

90-Day Validation Plan

  • Run 100–300 anonymized document-review workflows across target workflow categories
  • Benchmark local agent outputs against approved frontier evaluators using anonymized context
  • Measure source relevance, gap-detection quality, human usefulness and cost per workflow
  • Build verified learning cases to support ongoing local-model improvement
  • Prepare a limited industrial pilot proposal based on validation findings
Discuss Support or Pilot Access

Responsible engineering AI

AxiOMSphere supports engineering drafting and review workflows. Generated documents and recommendations require qualified human review before operational use.

No automatic compliance certification claims. Copyrighted standards and guidance documents are referenced as benchmarks, not reproduced. Every recommendation includes traceable evidence from source materials.