> ## Documentation Index
> Fetch the complete documentation index at: https://docs.prodexlabs.com/llms.txt
> Use this file to discover all available pages before exploring further.

# What Is ProDex?

> An overview of ProDex, the AI-native platform for manufacturing operations.

## Overview

ProDex is an AI-native platform for manufacturing operations. It brings [discrete event simulation](/product/simulation-overview), [production planning](/product/planning-overview), and [BOMs](/product/bom-overview) into a single environment — and puts an operations-literate AI agent, [**Dexter**](/product/ai-assistant), at the center of it.

You work with Dexter in [**Chat**](/product/dexter/chat-and-tasks). Describe what you need in plain language, and Dexter builds simulation models, profiles and transforms your uploaded data, runs analyses and experiments, generates reports, and captures recurring procedures as reusable workflows — grounded in your actual operation and auditable at every step.

Everything you build lives in a **Factory**: the workspace container that holds your uploaded data, simulation models, BOMs, configuration templates, plans, experiments, insights, run history, and the [knowledge base](/product/dexter/memories) Dexter maintains about your operation. Your whole team works against the same [Factory](/product/factory-management).

The core idea: instead of managing your operations across spreadsheets, point tools, and manual reports, ProDex gives you a **live, shared model of your factory** — data, structure, and operational knowledge — that your team and Dexter build and reason about together.

<Note>
  New to the vocabulary? [Key Concepts](/getting-started/key-concepts) defines the handful of terms — Factory, model, run, artifact, project — that every other page assumes.
</Note>

## Who Is It For?

ProDex is built for the people who run manufacturing operations day-to-day:

* **Operations managers** who need to understand throughput, bottlenecks, capacity, and sensitivity to disruption
* **Production planners** who turn demand into feasible plans that respect capacity, inventory, and BOM structure
* **Schedulers** who assign jobs to machines and workers and sequence them around changeovers
* **Analysts and engineers** who model what-if scenarios: cycle time studies, layout changes, staffing changes
* **Executives** who want decision-ready reports grounded in the model, not in slideware

No programming experience is required. Dexter does the heavy lifting; you direct the work, approve the assumptions, and sign off on the outputs.

## How You Work with Dexter

Dexter is not a chatbot bolted onto a tool. It is an operations partner with direct access to your Factory, your uploaded data, and a persistent memory of your operation:

* [**Chat**](/product/dexter/chat-and-tasks) is the primary interface. Ask Dexter to profile a spreadsheet, build a simulation of a line, run a planning optimization, or draft a report — in plain language.
* **Session-context awareness**: Dexter knows which page you're on and which objects you have selected (a model, a run, a pipeline), and works against those without you having to restate the context.
* **Tasks**: for multi-step work, Dexter maintains a visible [task list](/product/dexter/chat-and-tasks) so you can see exactly what's in flight, what's done, and what's next.
* [**Knowledge Base**](/product/dexter/memories): durable, per-factory memory of how your operation actually runs, what your data means, and what has been built in the platform. It survives across conversations, and you can read and edit it.
* [**Rules & Preferences**](/product/dexter/rules-and-preferences): standing instructions you set for how Dexter should work — conventions, defaults, and guardrails it follows in every conversation.
* [**Workflows**](/product/dexter/custom-workflows): once Dexter has learned to do a recurring task the way your team likes it, you can save that procedure as a workflow and reuse it in later conversations.
* [**Projects**](/product/dexter/projects): for efforts too big for one conversation (a full simulation study, a multi-week model build), Projects give the work a durable home with phases and gated sign-offs, so Dexter can resume exactly where it left off across sessions.

## Where to Start

Most new users follow this path:

1. **Bring your data in**: upload spreadsheets, MES exports, ERP reports, PDFs of work instructions, even screenshots or CAD files. Dexter profiles what you provide and turns it into ready-to-use inputs, keeping an auditable record of how each value was derived.
2. **Build a model**: describe your operation to Dexter in Chat. Dexter constructs the model in the [Modeler](/product/simulation-modeling), exposes every assumption for your approval, and records provenance for every parameter.
3. **Run simulations**: see throughput, bottlenecks, utilization, and WIP, with full event traces.
4. **Compare scenarios**: use [Experiments](/product/experiments) to snapshot variants of a model or schedule and lay the KPIs out side by side.
5. **Decide and share**: generate production plans, schedules, and [reports](/product/dexter/reports) (PDF, PowerPoint, Word, Excel) that trace back to their inputs.

<Tip>
  For a guided first session, [Your First Project](/getting-started/your-first-project) walks you from a data upload to your first Dexter-built artifact. If you want to go straight to simulation, see [Your First Simulation](/getting-started/your-first-simulation).
</Tip>

## Key Capabilities

### [Modeler](/product/simulation-modeling)

Discrete event simulation, built as a flow graph — sources, processes, stations, buffers, routers, and sinks — with **entities** (parts, batches, work orders) flowing through. Shared resources (operators, machines, tools) are modeled explicitly, along with combiners, separators, and transformers for assembly, splitting, and conversion. [Schedules](/reference/schedules) anchor the run to real-world timing, and resource availability patterns capture shifts and capacity changes. For statistical confidence, [Monte Carlo](/product/monte-carlo) wraps repeated runs into confidence intervals on your KPIs.

### [Data](/product/data-overview)

How raw operational data becomes platform inputs. Upload an MES export, an ERP report, or a screenshot; Dexter profiles it, transforms it, and produces concrete derivations — cycle time distributions, processing times, demand profiles, yield rates — while keeping an auditable record of how each value was derived from its source. See the [Data overview](/product/data-overview) for the full picture.

### [Experiments](/product/experiments)

Snapshot variants of a model and schedule, run them, and compare results side by side with KPIs and charts. The standard tool for sensitivity analysis and what-if work: different schedules, resource configurations, or demand profiles.

### [Insights](/product/insights)

Factory-scoped analytical artifacts — dashboards, charts, and KPI views — for exploratory analysis of your data or your simulation results. Often produced through the [Exploratory Data Analysis](/product/exploratory-analysis) workflow.

### [Production Planning](/product/planning-overview)

Combine demand orders, current inventory, and your [BOMs](/product/bom-overview); the planning optimizer produces a plan of what to make, when, and in what quantities, balancing demand fulfillment against inventory targets and finite capacity. Custom constraints — production smoothing, minimum lot sizes, campaign structure — are supported.

### [Job Scheduling](/product/scheduling)   <Badge icon="star" color="orange" size="sm" shape="rounded">Beta</Badge>

For production orders that need to be sequenced onto specific resources, accounting for processing times and changeover costs.

### [BOMs](/product/bom-overview) and [Configuration](/product/configuration-templates)

BOMs capture product recipes and their component structure. [Configuration templates](/product/configuration-templates) capture configurable products as option classes and constraints; Dexter walks an order through them step by step to produce concrete [configurations](/product/configurations) that plug into planning and simulation.

### [CAD Analysis](/product/cad/overview)

Upload DWG, DXF, or STEP files. Dexter extracts geometry, dimensions, and structure to inform layout, fixturing, and process planning work.

### [Reports](/product/dexter/reports)

Downloadable, shareable deliverables — PDF, PowerPoint, Word, Excel — generated from your Factory's models, runs, insights, and data.

<Note>
  Some modules are enabled per organization. Depending on your configuration, surfaces like Job Scheduling may not be visible in your instance.
</Note>

## How It Fits Into Your Operations

ProDex sits between your raw operational data and the decisions your team has to make about capacity, staffing, plans, and schedules. The **Factory** contains everything — data, models, plans, schedules, reports, and the accumulated knowledge of how your operation actually runs — and Dexter works alongside your team inside it. One shared workspace, one live model of the operation, one partner that remembers what you've built and why.