How MyClone Optimizes Its RAG Pipeline for Faster, Smarter Digital Personas

At MyClone, our mission is simple yet bold: to help you create a digital persona that truly thinks, speaks, and advises like you.

Whether you are a consultant, educator, creator, or enterprise leader, your digital persona must reflect your knowledge—accurately, consistently, and instantly.

To make this possible, we rely on a powerful technology called Retrieval-Augmented Generation (RAG). And while RAG is becoming a standard in AI systems, not all RAG pipelines are created equal. In fact, the quality of a digital persona depends heavily on how well its RAG system is designed.

Today, we’re taking you behind the scenes to show how MyClone has engineered a highly optimized RAG pipeline—from how your data enters the system (ingestion) to how it’s retrieved during conversations.

What Is RAG, and Why Does It Matter for Digital Personas?

Traditional AI models generate responses from what they learned during training—but they don’t inherently know your documents, experiences, case studies, research, or expertise.

This is where RAG shines. Think of it like an open-book exam. Instead of forcing the AI to memorize everything, we give it access to a library of your specific documents.

RAG = Retrieval + Generation

Retrieval → Find the most relevant information from your personal knowledge base.
Generation → Use that information to craft a precise, context-aligned response.

For your digital persona, this means:

More accurate answers.
Less hallucination.
Better alignment with your speaking and thinking style.
Automatic use of your uploaded data.

But all this depends on how well your data is stored, chunked, enriched, and retrieved. At MyClone, we’ve spent months refining this pipeline so your clone becomes smarter, faster, and more reliable.

How MyClone Optimizes RAG: From Raw Data to Ready-to-Use Knowledge

We believe that better data input equals better AI output. Below is a breakdown of the major innovations in our ingestion pipeline that set us apart.

1. Smart Chunking: Dividing Large Documents With Overlapping Context

Large documents—PDFs, books, research papers—are too big for AI models to read all at once. So, we split them into chunks (small sections of text).

But if you cut a document in the middle of a sentence or a complex thought, the meaning is lost.

We add overlapping boundaries between chunks.

How it works: If Chunk A ends at sentence 50, Chunk B starts at sentence 45.

Why this matters:

Conversations often refer to content that spans multiple paragraphs.
A rigid cut can break the meaning, causing retrieval issues.
Overlaps ensure that context flows naturally across chunks.

Result: Your digital persona never “loses the plot” mid-answer because the context is preserved across the seams.

2. Context Injection: Summaries & Keywords for Every Chunk

In a standard system, a chunk of text is stored alone. But sometimes, a single paragraph doesn’t make sense without knowing what the whole chapter is about.

This is one of our most important optimizations. For every chunk, we use an LLM to analyze the text and extract:

A micro-summary (1–2 lines explaining the gist of the text).
2–3 high-value keywords (tags that capture the core topic).

We store this metadata inside the chunk.

Why this matters: Retrieval is no longer purely dependent on exact wording. If a user asks a question using different terminology than what is in your document, the system can still find the answer via the summary or keywords.

Example:

Document Content: Discusses “asynchronous team alignment protocols.”
User Question: “How do I keep my remote team on the same page?”
Result: The persona finds the correct chunk thanks to the metadata, even though the words differ.

3. PDF Data Converted Into Clean, Structured Markdown

PDFs are the enemy of AI. They are visual documents, not structured data. If you copy-paste from a PDF, tables often turn into a jumbled mess of numbers, and headers get confused with body text.

MyClone fixes this by parsing all PDF content into well-structured Markdown.

Markdown is a coding language that creates structure. It preserves:

Headings
Lists and bullet points
Tables (in proper markdown format!)

Why this matters: When you ask your MyClone, “What was the Q3 revenue in the table?”, the AI sees a structured grid, not a soup of random numbers. This ensures high precision for financial reports, invoices, and technical specs.

4. Giving Sight to the Blind: LLM-Generated Descriptions for Images

Modern knowledge often includes visuals. Standard search engines are “blind” to these—if your strategy deck relies on a pie chart, a standard AI will miss it completely.

We don’t leave these behind. Whenever our pipeline detects:

A graph
A chart
A large table
An image

We pass it to a Vision LLM to create a detailed textual description.

Input: An image of a rising stock chart.
MyClone Processing: Generates text: “Line graph showing stock value increasing from $100 in Jan to $150 in March.”

This textual description is stored inside the chunk, ensuring it becomes searchable. Now, your digital persona can “read” your charts and answer questions about visual data.

5. Audio and Video → High-Quality Transcripts

Your expertise doesn’t just live in documents; it lives in Zoom calls, podcasts, and lecture videos.

Your digital persona also learns from:

Podcasts
Webinar recordings
YouTube videos
Course lectures
Client calls (optional, uploaded by you)

We currently extract clean transcripts from your audio and video files. These transcripts are then treated with the same rigorous process as text:

Contextually Chunked
Time-aligned
Summarized, and keyword-tagged.

Why this matters: Your digital twin can quote you from a webinar or a podcast just as easily as it can quote a PDF, creating a truly holistic view of your knowledge.

Additional RAG Enhancements We Use at MyClone

Storing data is only half the battle. The other half is finding the exact right piece of information when a user asks a question. Here is how we optimize the retrieval process.

1. Hybrid Retrieval (The Best of Both Worlds)

We don’t rely on vectors alone. We combine two search methods:

Keyword Search: Perfect for specific product codes, names, or unique terms.
Vector Search: Perfect for concepts and broader questions (searching by meaning).

Why this matters: By combining both scoring methods (Hybrid Scoring), we ensure better precision and recall. We find the data whether the user is being incredibly specific or broadly conceptual.

2. The “Strict Editor”: Multi-Stage Re-Ranking

When you search your database, the system might find 50 possible matches. Some are great; some are just loosely related.

We use a Re-Ranking Model. Think of this as a strict editor. It looks at the top results found by the fast search, analyzes them deeply, and re-orders them so that the absolute best, most relevant answer is at the very top.

Result: Only the highest-quality context is sent to the AI to generate your answer.

3. Context Window Optimization

We carefully optimize how much data the model sees to prevent “information overload.”

We automatically:

Remove duplicates.
Filter out contradicting chunks.
Merge related sections.
Limit unnecessary filler text.

This improves both the speed of the response and the quality of the output.

4. Continuous Learning & Re-Indexing

Your knowledge base isn’t static, and neither is our system.

When you:

Upload new documents
Update your digital persona
Correct an answer

The system triggers conditional re-indexing to keep the RAG store fresh and consistent.

Why All This Matters for You

All these technical optimizations come together to deliver what MyClone promises:

A digital persona that speaks like you
Uses your knowledge with accuracy
Reduces hallucinations
Gives consistent, professional answers
Saves time by automating repetitive interactions

From customer-facing bots to consulting clones to internal knowledge assistants—your digital persona needs to retrieve information the way you would. Our optimized RAG pipeline makes that possible.

The Future of RAG at MyClone

We’re building even more enhancements:

Image-to-text OCR improvements.
Fine-grained topic segmentation.
LLM-based contextual memory.
Real-time document syncing.
Persona-aware retrieval (combining your tone with your knowledge).

The goal remains the same: To give every user a scalable, trustworthy digital version of themselves.

Conclusion

RAG may sound like a technical framework, but at MyClone it’s the backbone of something much more meaningful—a digital persona that unlocks your expertise for thousands of people at once.

By blending intelligent chunking, metadata-rich ingestion, hybrid retrieval, and AI-powered summarization, we ensure your clone is fast, accurate, and deeply aligned with who you are.

If you haven’t already created your digital persona, now is the perfect time. Your knowledge can help far more people—your clone will make sure of it.