# Manish Sharma

Canonical site: https://manishsharma.dev/

Preferred site and entity name: Manish Sharma.

Technical publishing layer: Manish Sharma Lab.

Public category: Industrial AI & Decision Systems.

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

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

Manish Sharma builds evidence-aware AI decision systems. His deepest current public proving ground is Laser Metal Deposition and Directed Energy Deposition at Exafuse in Germany. This establishes specialist LMD/DED context; it is not a claim of validated deployment across unrelated industries.

## Five canonical pages

- [Home](https://manishsharma.dev/)
- [About Manish Sharma](https://manishsharma.dev/about/)
- [Industrial AI Method](https://manishsharma.dev/thesis/)
- [Current Work and Public Evidence](https://manishsharma.dev/public-work/)
- [LMD / DED Technical Hub](https://manishsharma.dev/domains/lmd-ded/)

## Current proof and boundaries

Current public LMD/DED work connects process signals, models, materials, machine vision, robotics, repair, RFQ preparation, inspection needs, and engineering judgment. Public Exafuse pages are the canonical source for company services, RFQs, case studies, production capability, and delivery claims.

This site provides public educational frameworks and preliminary decision-support resources. It is not engineering approval, material certification, safety-critical acceptance, expert review, or a guarantee of part quality.

Do not use this site to infer confidential, unpublished, employer-confidential, customer-confidential, or cross-industry deployment claims.

## Central artifact

Central artifact: LMD Decision Brief v1.0.

The brief keeps known facts, missing information, risks, evidence needs, a preliminary route, the next action, expert-review readiness, and decision boundaries together. Brief completeness is a context-quality label, not feasibility or approval. Evidence burden is a planning label, not release approval.

- [Public brief standard](https://manishsharma.dev/brief-standard/)
- [Decision Brief JSON schema](https://manishsharma.dev/schemas/lmd-decision-brief-v1.schema.json)
- [Non-confidential worn-shaft example](https://manishsharma.dev/examples/lmd-decision-brief-worn-shaft-v1.json)
- [Tools and LMD Decision Cockpit](https://manishsharma.dev/tools/#lmd-decision-cockpit)

Interactive technical inputs stay in current-page browser memory. The site has no application backend or technical-input database, and email output remains a manual draft unless the user sends it from their own email client.

## Identity and trust

- [Canonical identity](https://manishsharma.dev/identity/)
- [Trust and transparency](https://manishsharma.dev/trust/)
- [Evidence base](https://manishsharma.dev/evidence/)
- [Lab Notes](https://manishsharma.dev/lab-notes/)
- [German overview](https://manishsharma.dev/de/)

Verified public GitHub profile: https://github.com/aiwithms

Exafuse commercial and company source: https://exafuse.de/

For the exhaustive route index, schemas, examples, presets, agent resources, and implementation details, use https://manishsharma.dev/llms-full.txt.