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

# The Mach-1 pipeline

> Move from audio to transcripts, classifications, extracted findings, evaluations, evidence, and forecasts.

Mach-1 turns recordings and existing transcripts into structured results, and forecasts future values from numerical history. Start with the input you already have and choose the processing you need.

## 1. Transcribe

Send a recording for transcription. Inspect the returned text, available timing, and speaker labels. Use [the quickstart](https://docs.aioncx.com/quickstart.md) for your first recording and [transcription](https://docs.aioncx.com/mach1/transcription.md) for input and output details.

## 2. Attribute speakers

Where speaker attribution is available, turns identify different speakers. A speaker label describes the source attribution; use additional identity evidence to associate it with a person. Supplied text preserves the labels and timing you provide.

## 3. Classify and extract

Select published analysis Definitions to identify scenarios, reasons for contact, entities, actions, and commitments. The Definition determines the output and service being requested. See [classification, extraction, and evaluation](https://docs.aioncx.com/mach1/analysis.md).

## 4. Summarize and evaluate

Request a published Definition that produces the summary or evaluation you need. An evaluation applies its own configured criteria and version. Requesting transcription alone does not select analysis.

## 5. Use structured results and evidence

Retrieve the transcript, findings, evaluations, and their source references. Check the input revision and processing state, then follow evidence back to the relevant passage. Read [results and evidence](https://docs.aioncx.com/mach1/results.md).

## 6. Forecast

Supply numerical history or select an authorized registered metric, choose the interval and horizon, and retrieve the saved forecast. Supported drivers can add information available at forecast time.

Extracted findings can contribute to a measured time series. Define its metric, interval, filters, and history before using that series for a forecast. The [forecasting guide](https://docs.aioncx.com/mach1/forecasting.md) starts directly from numerical input.

## Choose an entry point

| Your input | Start with |
| - | - |
| Recording | [Transcription](https://docs.aioncx.com/mach1/transcription.md) |
| Existing transcript | [Analysis](https://docs.aioncx.com/mach1/analysis.md) |
| Existing admitted conversation | [Results and evidence](https://docs.aioncx.com/mach1/results.md) |
| Numerical history or a registered metric | [Forecasting](https://docs.aioncx.com/mach1/forecasting.md) |

Use Build for the available browser workflows and credential management, REST for applications, and MCP for authorized agents. Check [usage and pricing](https://docs.aioncx.com/mach1/usage.md) before submitting paid work.


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