Today, we’re introducing multi-file ingestion, a new feature in SeekrFlow’s AI-Ready Data Engine that speeds up automated generation of fine-tuning datasets. With this capability, enterprise teams can upload multiple unstructured files at once and automatically transform them into a generative AI-ready format—saving time, resources, and headaches in their data preparation.

Data integration across file types

Nearly 80% of enterprise data exists in unstructured formats such as PDFs, DOCX, Markdown, and JSON. Converting the data from all of these files into an AI-ready format requires multiple tools and manual interventions, leading to delays and increased costs.

The multi-file ingestion feature directly solves this bottleneck in data preparation. Previously, users needed to manually combine all relevant content into a single file before using the AI-Ready Data Engine. Now, users can upload multiple files across formats and the data engine will automatically extract and structure all relevant training data through an agentic workflow.

This eliminates the need for time-consuming prework like formatting or stitching files together. Instead of consolidating documents manually, users can simply upload various guidelines, documentation, and principles in their original format.

Key benefits

Effortless data upload

Many enterprises store critical knowledge such as guidelines and internal documentation in various file formats (e.g. DOCX, PDF). Multi-file ingestion lets teams upload all the enterprise documents needed to train a model—across various formats—to eliminate manual file handling to streamline data ingestion. Simply drag, drop, and let SeekrFlow handle the rest.

Automated conversion

Once uploaded, SeekrFlow automatically converts each file into a structured Markdown format. These files serve as the input that kickstarts the AI-Ready Data Engine process, streamlining the transition from unstructured enterprise data into a structured AI-optimized dataset.

Faster AI data preparation

By eliminating the need for manual formatting and tool-switching, multi-file ingestion enables users to process large volumes of data more efficiently. This reduces bottlenecks and accelerates the deployment of high-performing AI applications.

Breaking down the real cost of manual data preparation

Traditional AI data preparation is slow, costly, and resource-intensive. It often requires teams to manually structure, label, and cleanse data, delaying AI deployments and limiting scalability. Multi-file ingestion in SeekrFlow dramatically reduces this burden by automating the most resource-intensive steps.

To illustrate the difference, we compared three data preparation approaches based on what it takes to process 10,000 pages of documents into training data:

• Manual: Fully human-driven with formatting, labeling, and document merging, no AI.
• Hybrid: A mix of software such as AWS Textract or Google Document AI, and manual processes.
• Automated (SeekrFlow): Fully automated data preparation through SeekrFlow.

Each method was evaluated across four key stages of preparation:

• File conversion: Converting PDFs, DOCX, and other formats into structured outputs like JSON or Markdown.
• OCR processing: Extracting usable text from scanned or image-based documents.
• Data cleaning and structuring: Formatting, deduplication, tokenization, and error correction.
• Alignment and token optimization: Ensuring data is in the right structure and form to support LLM fine-tuning and retrieval.

SeekrFlow allows enterprises to focus on building and deploying AI, not formatting files or troubleshooting conversions. The speed and consistency of automated ingestion unlock a new level of efficiency across your AI initiatives.

Time savings: When teams spend less time prepping data, they can spend more time building and validating models. What once took weeks now takes hours.

Reduced operational costs: Manual data prep doesn’t scale. Whether it’s engineering hours or outsourced labeling, the costs compound quickly. SeekrFlow eliminates this by automating ingestion and structuring from the start.

Consistency at scale: With SeekrFlow, the same ingestion logic applies across every file, every time. That means fewer errors, more predictable outputs, and higher dataset quality, whether you’re ingesting five files or 500 files.

Build trusted models faster with the AI-Ready Data Engine

The Seekr AI-Ready Data Engine automates the entire process of ingesting, structuring, and optimizing content into high-quality AI-ready datasets, enabling enterprises to:

Accelerate AI model development

By automating data preparation, the AI-Ready Data Engine reduces time spent on structuring and labeling datasets, cutting data prep time from weeks to hours. On average, enterprises can build datasets 2.5x faster and 90% more cost-effectively than traditional methods.

Enhance model performance

Raw enterprise data is often cluttered with irrelevant information that can dilute AI performance. The AI-Ready Data Engine filters out noise, extracting the most critical signals to ensure models train on high-quality, domain-specific data, resulting in up to 3x improved accuracy.

Ensure consistency across AI applications

AI models require data tailored to specific use cases, but maintaining consistency across applications can be challenging. SeekrFlow enables businesses to generate structured datasets aligned with their unique system prompts, ensuring data integrity across fine-tuning, retrieval, and real-time decision-making.

Start building with SeekrFlow

Five or 500 files, multi-file ingestion removes the complexity of data preparation. No more manual formatting or juggling tools to convert your data—simply upload your files in their existing formats and SeekrFlow will transform them into a single, structured Markdown document ready to be converted into a generative AI-ready format.

With the Seekr AI-Ready Data Engine, enterprises eliminate manual bottlenecks, streamline data preparation, and accelerate AI deployment all within a single platform.

Sign up for SeekrFlow today through our API, SDK, or intuitive UI to experience seamless data ingestion and automated structuring firsthand, or book a consultation with a product expert to explore how Seekr can optimize your AI workflows.