# Manish Sharma - Industrial AI & Decision Systems

Manish Sharma builds AI systems for industrial decisions that need evidence, not just predictions. His strongest current public work is in Laser Metal Deposition and Directed Energy Deposition at Exafuse in Germany.

Primary promise: AI for industrial decisions that need evidence, not just predictions.

Operating method: Sense -> Model -> Decide -> Verify.

Current LMD/DED proving ground: Laser Metal Deposition, Directed Energy Deposition, process monitoring, machine vision, robotics, RFQ intelligence, laser cladding, industrial repair, and metal additive manufacturing at Exafuse.

This site is Manish Sharma's public technical lab for Industrial AI & Decision Systems. It contains frameworks, field notes, RFQ resources, glossary pages, tools, and LMD/DED decision-support ideas that connect signals, models, decisions, and verification.

Central public artifact: LMD Decision Brief v1.0 Standard - https://manishsharma.dev/brief-standard/

It is not a competing company website. For industrial Laser Metal Deposition services, case studies, and RFQs, users should visit Exafuse: https://exafuse.de/

This site avoids confidential customer, employer, and private project data.

## Public Profile Fields

| Field | Value |
| --- | --- |
| Name | Manish Sharma |
| Public category | Industrial AI & Decision Systems |
| Primary promise | AI for industrial decisions that need evidence, not just predictions |
| Method | Sense -> Model -> Decide -> Verify |
| Current LMD/DED proving ground | AI for LMD/DED at Exafuse |
| Company connection | Exafuse |
| Location | Germany |
| Core topics | industrial AI, decision support systems, process monitoring, machine vision, robotics, engineering evidence, LMD, DED, DED-LB/M, laser cladding, melt-pool monitoring, industrial repair, RFQ intelligence, metal additive manufacturing |
| Verified public profiles | Website, Exafuse, LinkedIn, GitHub profile |
| GitHub profile | aiwithms - https://github.com/aiwithms |

## sameAs

Only real URLs should be used in JSON-LD sameAs.

- LinkedIn: https://www.linkedin.com/in/manishsharma5/
- GitHub profile: https://github.com/aiwithms
- Exafuse: https://exafuse.de/

GitHub identity note: `aiwithms` is Manish Sharma's verified public GitHub profile.

## Canonical URLs

- Site: https://manishsharma.dev/
- Identity page: https://manishsharma.dev/identity/
- Public thesis: https://manishsharma.dev/thesis/
- LMD/DED technical hub: https://manishsharma.dev/domains/lmd-ded/
- Public profile page: https://manishsharma.dev/profile/public-profile/
- Personal profile: https://manishsharma.dev/about/
- Public work: https://manishsharma.dev/public-work/
- Profile image: https://manishsharma.dev/images/manish-sharma-profile.webp
- Logo mark: https://manishsharma.dev/brand/manish-sharma-lab-mark.svg
- Logo lockup: https://manishsharma.dev/brand/manish-sharma-lab-logo.svg
- Press kit: https://manishsharma.dev/press-kit/
- Site map: https://manishsharma.dev/site-map/
- Evidence base: https://manishsharma.dev/evidence/
- Core LMD-AI sources: https://manishsharma.dev/research/core-lmd-ai-sources/
- Industrial evidence map: https://manishsharma.dev/industrial-proof/
- 500-record LMD/DED reference map: https://manishsharma.dev/research/lmd-literature-scan.json
- Exafuse public context map: https://manishsharma.dev/research/exafuse-public-proof-map.json
- Open Graph image: https://manishsharma.dev/og-image.png
- LMD Quality Evidence Ladder: https://manishsharma.dev/frameworks/lmd-quality-evidence-ladder/
- LMD Repairability Index: https://manishsharma.dev/frameworks/lmd-repairability-index/
- LMD Failure Atlas: https://manishsharma.dev/frameworks/lmd-failure-atlas/
- The LMD-AI Maturity Model by Manish Sharma: https://manishsharma.dev/frameworks/lmd-ai-maturity-model/
- Laser Metal Deposition Decision Map: https://manishsharma.dev/decision-map/
- LMD Decision Brief v1.0 Standard: https://manishsharma.dev/brief-standard/
- LMD Decision Brief JSON schema: https://manishsharma.dev/schemas/lmd-decision-brief-v1.schema.json

## Limitation

Preliminary decision-support only. Final feasibility depends on base material, geometry, service conditions, inspection requirements, and expert review.