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HOANG THUYET

Industrial AI Platform

AI that understands engineering and machines.

Hoang Thuyet is building an AI-native Industrial AI platform that transforms engineering information and machine data into actionable intelligence.

From understanding technical drawings to monitoring industrial equipment, grounded AI agents help engineering teams design faster, detect problems earlier and make better operational decisions.

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bearing_housing_drawing.pdfEngineering AI
  1. 2D
  2. AI
  3. Features
  4. 3D
1234ABC12055Ø40±0.02R5SECTION A-AAA4× Ø8 THRUTOP VIEWNOTES1. GENERAL TOL ±0.1 UNLESS NOTED2. FILLETS R5. BREAK SHARP EDGESBEARING HOUSINGDWG BH-120REV ASCALE 1:2UNIT mmSHEET 1/1
Reading drawing…Product Concept / In Development
Motor M-04 · Line 2Machine Intelligence
M-04
Motor M-04 Monitoring
Vibration
4.2 mm/s
Temperature
67 °C
Current
12.8 A
RPM
1480
Decision support · engineers in controlIllustrative data

Platform

One intelligence layer for engineering and industrial operations.

Industrial information is fragmented across drawings, documents, machines, sensors and operational systems.

We are building an AI layer that helps connect these sources and turn them into engineering context that people and AI agents can use.

Engineering data

  • 2D Drawings
  • Technical Documents
  • CAD Metadata

Industrial AI Platform

  1. Context EngineL1
  2. AI ReasoningL2
  3. Engineering AgentsL3
  4. Tools & Industrial SystemsL4

Machine data

  • Vibration
  • Temperature
  • Current
  • Speed
  • Operational Signals

Engineering Intelligence

From engineering drawings to structured 3D understanding.

Engineering teams still spend significant time interpreting drawings, extracting specifications and rebuilding legacy designs.

We are developing AI-assisted workflows that understand technical drawings and convert engineering information into structured, machine-readable representations that can support downstream 3D and CAD workflows.

bearing_housing_drawing.pdfProduct Concept / In Development
1234ABC12055Ø40±0.02R5SECTION A-AAA4× Ø8 THRUTOP VIEWNOTES1. GENERAL TOL ±0.1 UNLESS NOTED2. FILLETS R5. BREAK SHARP EDGESBEARING HOUSINGDWG BH-120REV ASCALE 1:2UNIT mmSHEET 1/1

Drawing Intelligence

Understand more than geometry.

Drawing understanding

Identify dimensions, annotations, views and engineering features.

Specification extraction

Turn unstructured drawing information into structured engineering data.

Document context

Connect drawings with manuals, specifications and related engineering documents.

Engineering assistant

Ask questions about drawings and receive responses grounded in engineering source material.

Ask Engineering AIProduct Concept / In Development
What is the tolerance of the main bore?

The main bore is specified as Ø40 mm with a tolerance of ±0.02 mm.

Source

Bearing Housing Drawing · BH-120 Rev A

Section A-A, bore callout

Ask about a drawing, part or specification…

Machine Intelligence

Turn sensor signals into machine understanding.

Industrial machines continuously generate signals.

We are building AI-assisted monitoring that combines sensor analysis, operating context and engineering knowledge to help teams identify abnormal behavior and investigate potential equipment issues.

MOTOR M-04
Potential anomalyIllustrative sensor data
Vibration4.2mm/s
baseline 3.55 mm/s−24 hnow
Temperature67°C
−24 hnow
Current12.8A
−24 hnow
RPM1480rpm
−24 hnow

Sensor Pipeline

From raw signals to actionable context.

Layer 1 · Signal analytics

Deterministic processing produces measurable features.

  1. Machine

    • Motor
    • Pump
    • Fan
    • Gearbox

  2. Sensors

    • Vibration
    • Temperature
    • Current
    • RPM
    • Acoustic

  3. Signal processing

    • Filtering
    • FFT
    • Feature Extraction
    • Trend Analysis

  4. Anomaly detection

    • Baseline comparison
    • Drift & threshold events

Layer 2 · AI reasoning

Language models reason over features and context, not raw waveforms.

  1. AI context engine

    • Features + events
    • Machine history
    • Manuals
    • Engineering knowledge
    • Maintenance context

  2. Industrial AI agent

    • Grounded explanation
    • Suggested checks
    • Draft tasks

  3. Operator / Engineer

    • Reviews
    • Decides
    • Approves

Signal processing and anomaly detection produce measurable features: RMS levels, spectral peaks, trends and threshold events, computed with established signal methods.

AI reasoning combines those features with machine history, manuals, engineering knowledge and maintenance context to help engineers investigate problems. A language model is never asked to read raw vibration signals on its own.

Industrial AI Agent

An AI agent that understands the machine, not just the conversation.

The agent plans a multi-step investigation, calls controlled tools for sensor features, documents and maintenance records, and answers with sources. Any action it proposes waits for a person to approve it.

Agent session · Motor M-04Interactive demo · no equipment connected
Why is Motor M-04 showing abnormal vibration?

Agent activity

  1. Retrieve vibration historysensor_history(M-04, vibration, 24h)
  2. Analyze extracted signal featuressignal_features(M-04)
  3. Check temperature trendsensor_history(M-04, temperature, 24h)
  4. Retrieve motor manualdocs.search("M-04 manual bearings")
  5. Review maintenance historymaintenance.records(M-04)
  6. Compare operating contextcontext.operating_state(M-04)

The agent does not control machinery. It reads approved data sources and proposes actions for people to approve.

Agentic Workflows

Specialist agents, one orchestrated workflow.

Industrial questions cross disciplines. Our architecture routes each step to a specialist agent with its own tools and scoped context, while an orchestrator plans the workflow, checks the results and asks a person to approve anything that changes a system.

Orchestrator

Plan · route · verify · request approval

Drawing Agent

Reads drawings and specifications

  • drawing.parse
  • spec.extract
  • docs.search

Signal Agent

Interprets extracted sensor features

  • signal_features
  • sensor_history
  • baseline.compare

Maintenance Agent

Prepares inspections and work orders

  • maintenance.records
  • task.draft
  • checklist.build

Knowledge Agent

Grounds answers in manuals and history

  • rag.retrieve
  • cite.sources
  • memory.scope

Shared: grounding, scoped memory, evaluation traces, permission-aware tool access.

Architecture in development

AI Architecture

Grounded AI for industrial workflows.

Retrieval and context engineering decide what the model sees. Claude reasons over that context, agents orchestrate tools, and people approve what happens next. Memory, grounding, evaluation and observability run across every layer.

  • Scoped Memory
  • Grounding
  • Evaluations
  • Observability

Inputs

  • Engineering Drawings
  • Machine Manuals
  • Sensor Features
  • Maintenance Records
  • Operational Data

Retrieval + Context Engineering

Select, rank and assemble the right sources

Claude

Reasoning layer

Agent Orchestration

Plan multi-step work across specialist agents

Tool Use

  • Engineering Tools
  • Maintenance Systems
  • Industrial APIs
  • Business Systems

Human Approval

Required before important actions

Action

Executed through existing systems, fully traced

Built with Claude

Building industrial intelligence with Claude.

Claude serves as a reasoning layer within our Industrial AI architecture.

We are exploring how Claude can combine retrieved engineering knowledge, machine context and controlled tool access to support complex industrial workflows.

Context engineering

Build relevant context from machines, drawings, users and workflows.

RAG

Retrieve relevant technical documentation and engineering knowledge.

Grounding

Tie AI responses back to source documents and machine information.

Agentic workflows

Coordinate multi-step engineering and maintenance workflows.

Tool use

Allow agents to interact with controlled engineering and operational tools.

Scoped memory

Maintain appropriate machine and workflow context across interactions.

Evaluation

Test groundedness, citations and tool choices before workflows ship.

Observability

Trace every retrieval, tool call and decision for review.

AI-native from day one

We build the platform itself with AI. Our engineering work runs on Claude Code agents for implementation, review and testing, under written guardrails: one change per pull request, tests that can fail, and a human decision at every open design question.

Evaluation

Industrial AI needs to be measurable.

Before AI-assisted workflows can be trusted in industrial environments, their behavior needs to be evaluated systematically.

Evaluation SuiteNo results published yet
Evaluation dimensions and their status
DimensionStatus
Groundedness Testing
Citation quality Testing
Tool selection Testing
Context retrieval Testing
Task completion Testing

  • Test Cases

    Questions and tasks with expected sources and tools

  • Evaluation Runs

    Repeatable runs against each model and prompt version

  • Agent Traces

    Step-by-step record of planning and decisions

  • Tool Calls

    Every call, its arguments and its result

  • Source References

    Which documents and signals supported each answer

Agent traceIllustrative structure
  1. planInvestigate abnormal vibration on M-04
  2. toolsensor_history(M-04, vibration, 24h)
  3. toolsignal_features(M-04)
  4. tooldocs.search("M-04 manual bearings")
  5. sourceMotor M-04 Manual · §6 Bearings
  6. checkEvery claim cites a source

Use cases

Built for engineering-intensive operations.

UC-01

Engineering digitization

Transform legacy drawings and engineering documentation into structured digital knowledge.

UC-02

Equipment intelligence

Understand machine behavior using sensor signals and operating context.

UC-03

Maintenance assistance

Help maintenance teams investigate anomalies and prepare inspection workflows.

UC-04

Industrial knowledge

Give engineers grounded access to manuals, drawings, specifications and machine history.

Safety & human control

AI assistance with engineers in control.

Grounded outputs

Connect AI responses to engineering sources.

Human approval

Require approval before important actions are executed.

Traceable reasoning

Record retrieval, tool calls and workflow execution.

Permission-aware access

Only provide agents with authorized context and tools.

The platform is designed as engineering decision support. AI-generated analysis should be reviewed by qualified personnel before safety-critical decisions are made.

Company

Building practical AI for industry.

Hoang Thuyet is an early-stage technology company in Singapore focused on Industrial AI.

We are developing systems that combine engineering data, machine signals and AI reasoning to help industrial teams understand complex information and improve engineering workflows.

Stage
Product Development
Location
Singapore
Focus
Industrial AI · Engineering Intelligence · Machine Intelligence

Founder

Hoang Cong Thuyet

Founder

Software engineer and product builder focused on Industrial AI, engineering software and intelligent automation.

Contact

Build the next generation of industrial intelligence.

Interested in Industrial AI, engineering automation, machine intelligence or early product access? Let's talk.

[email protected]

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