AI-Ready Data Overview

The AI-Ready Data tab in SeekrFlow transforms your documents into clean, structured datasets that are ready for model fine-tuning and retrieval workflows. Whether you’re aligning a general-purpose LLM or grounding an assistant in domain-specific knowledge, this is where it all starts.

This page explains what AI-Ready Data Jobs are, how ingestion works, and how to create a job using the SeekrFlow UI.

🧠 What is AI-Ready Data?

AI-Ready Data refers to high-quality, structured training content generated from your documents — such as question-answer (Q&A) pairs — that can be used to fine-tune large language models (LLMs) or support enhanced retrieval pipelines.

These jobs take your uploaded files, run them through SeekrFlow’s ingestion pipeline, and generate Parquet datasets — all traceable, inspectable, and usable across the SeekrFlow platform.

🧩 Job Types

SeekrFlow currently supports two types of AI-Ready Data jobs:

Standard Instruction

(Live – formerly Principle Alignment)

Generates Q&A datasets aligned to a single, high-level instruction. This type processes your uploaded documents through ingestion, then creates training data based on your defined goal.

Ingests PDFs and DOCX into Markdown
Aligns questions to your provided instruction
Output: A structured Parquet file saved within SeekrFlow

Best for:

General-purpose model fine-tuning
Domain-specific task alignment

Context Grounded

(Coming soon – RAFT-based)

Builds Q&A datasets grounded in semantically retrieved content from a VectorDB you create. This ensures generated pairs are based only on content the model would have access to at inference time.

Requires creation of a Vector Store first
Retrieves context and generates Q&A grounded in that context
Output: Parquet file saved for downstream use

Best for:

Retrieval-augmented generation (RAG)
Fine-tuning in factual, high-trust environments
Reducing hallucination risk in vertical-specific use cases

🧭 Job Creation Flow (UI Walkthrough)

Creating a job in the SeekrFlow UI is intuitive and follows these steps:

1. Navigate to the AI-Ready Data Tab

In the Data Engine, open the AI-Ready Data tab. You’ll see a list of existing jobs with their statuses.

Click “Create Job” to begin.

2. Define Your Fine-Tuning Goal

You’ll be prompted to describe your fine-tuning goal in plain language. This is translated into the instruction prompt that guides the Q&A generation process.

Examples:

“Help users troubleshoot hardware issues”
“Answer HR policy questions clearly and concisely”

3. Upload + Ingest Files

Drag and drop your files into the upload area. SeekrFlow supports four file types:

File Type	Ingestion Behavior
`.pdf`	✅ Full ingestion (converted to Markdown)
`.docx`	✅ Full ingestion (converted to Markdown)
`.json`	❌ Skips ingestion (already structured)
`.md`	❌ Skips ingestion (already structured)

Files requiring ingestion are automatically processed after upload, preparing them for alignment.

4. Confirm Setup

You’ll be shown:

A list of uploaded + ingested files
Your fine-tuning goal (instruction)

Click “Start Job” to begin generating the dataset.

5. Job Processing

Your job will now move through the following states:

Queued → Waiting for compute
Running → Files are being parsed, instructions applied, Q&A pairs generated
Completed → Your output is saved to SeekrFlow

6. Output Location + Usage

Once complete:

Your Q&A Parquet file will be automatically saved to:
- The AI-Ready Data page
- The Files section under Storage

You do not need to download anything. When you move to the next stage — Fine-Tuning — you’ll be able to select the Parquet file directly from your saved datasets in SeekrFlow.

This keeps your workflow streamlined, traceable, and ready to deploy.

📊 Job Status Reference

Status	Description
Queued	Job is waiting for available compute resources
Running	Job is actively processing your content and generating data
Completed	Job is done — your structured dataset is now available in-platform
Failed	Something went wrong — review file status and retry as needed

🔁 Platform Integration

The full lifecycle of your AI-Ready dataset flows seamlessly across SeekrFlow:

Upload Files → via the Storage tab
Ingestion (if applicable) → PDFs and DOCX are converted to Markdown
Create AI-Ready Job → via this tab
Output Saved Automatically → Parquet file available in AI-Ready + Storage
Fine-Tune a Model → Select output directly in the fine-tuning UI

Each dataset is fully reusable and traceable — ensuring transparent training workflows every step of the way.