What is Blockify?

Key impacts and proof points:

• Measurable accuracy gains: Up to 78x (7,800%) accuracy improvement, ~3x cost and infrastructure optimization, and reduction in AI errors from about 1-in-5 queries (20%) to about 1-in-1,000 (0.1%).
• Broad industry validation: Deployed across pharmaceuticals, U.S. federal government and military agencies, government contractors, IT integrators, healthcare, retail, education, and more.
• Third-party validation: A Big Four consulting firm’s two-month technical audit found a 68.4x accuracy improvement on a 17-document dataset, with significant token-efficiency gains.
• Easy to adopt: Integrates via API without changing your embeddings or vector DB. Outputs smaller, higher-quality blocks for your current pipeline or Iternal’s AirgapAI.

The Why: Why Blockify Matters Now

Based on over 550 conversations with enterprise customers in 2024, three consistent blockers for broad AI adoption emerged:

1. High Cost, Unclear ROI: AI deployment at scale is expensive and often disappointing in returns.
2. Need for Data Control and Governance: Teams demand rigorous data security to avoid leaks and third-party risk.
3. AI Hallucinations: Legacy stacks make 1-in-5 errors, posing unacceptable risk for employee-facing use.

Blockify directly addresses all three:

• Transforms human-centric documents into AI-ready data, multiplying accuracy, supporting governance, and reducing compute needs.

Blockify in a Nutshell

• Definition: Blockify is a patented data ingestion and distillation engine that:
  • Converts long-form, unstructured documents into compact, structured “IdeaBlocks” that are highly optimized for LLMs.
  • Removes duplication and redundancy via intelligent distillation, shrinking datasets to ~2.5% of original size.
  • Enables rapid, human-in-the-loop governance so you can trust AI answers in real-world production.
  • Plugs in seamlessly as a text-processing step into any RAG pipeline—your embeddings and vector DB stay unchanged.

Why Legacy Pipelines Hallucinate—and How Blockify Fixes It

The Hallucination Problem

• Human-centric files = text written for people, not LLMs.
• Naive Chunking = splitting text arbitrarily, mixing relevant and extraneous content. Queries easily miss details, forcing LLMs to improvise and guess.

Blockify’s Solution

• Structured, LLM-optimized blocks: Blockify converts text into tight, context-aware IdeaBlocks, removing irrelevant details and redundancy.
• Deduplication: Collapses repeated concepts down; for example, 1,000 versions of a mission statement become one authoritative block.
• Reviewable and Governable: Typical project yields just 2,000–3,000 blocks (paragraph-sized)—enough for same-day human review, with edit propagation across all systems.
• Error rate improvement: Reduces legacy hallucination rates from 20% to just 0.1%; up to 78x overall accuracy improvement and large compute savings.

Example: Big Four Consulting Evaluation

• Question: “Why is it necessary to have a roadmap for verticalized solutions?”
• Naive approach: Returns text mentioning “vertical use cases,” with no reference to roadmapping—model must guess.
• Blockify approach: Delivers concise, on-point block explicitly addressing the roadmap requirement.

Result: Trustworthy, precise responses—and order-of-magnitude reductions in error and compute.

What Blockify Processes

• Sales proposals, SOWs, FAQs, and knowledge base articles
• Marketing materials, slide decks, diagrams
• Transcripts of meetings, emails, contracts, and more

From Unstructured Text to “IdeaBlocks”

1. Ingestion: Converts documents into compact, context-rich IdeaBlocks.
2. Intelligent Distillation: Merges redundant content; output is ~2.5% of original corpus.
3. Human-in-the-loop Review: Teams rapidly review, approve, or revise a manageable set of blocks.
4. Governed Propagation: Edits apply everywhere instantly; consistent answers throughout every system.

Where Blockify Fits in Your AI Pipeline

• Legacy pipeline:
  • Chunk text → embed → vector DB → retrieve → generate response.
• Blockify pipeline:
  • Chunk text → Blockify API (IdeaBlocks) → embed → vector DB → retrieve → generate.

You keep your embeddings, vector DB, and overall stack. Blockify just replaces naive chunking with an advanced, LLM-optimized step.

AirgapAI & Third-Party Compatibility

• With AirgapAI: Use Blockify for on-device, offline, 100% secure chat with Iternal’s AirgapAI. Blockify is included in the AirgapAI license at no additional cost.
• Any AI System: Export finalized blocks to your own vector DB for use with any assistant, chat agent, or generative AI workflow.

Blockify Step-by-Step: Raw Content to Production-Ready Knowledge

1. Curate Your Source Corpus

• Ex: Top 1,000 high-value proposals, slide decks, articles, contracts, etc.

2. Ingest with Blockify

• Upload all documents (including images or graphics).
• Blockify generates tentatively structured IdeaBlocks.

3. Intelligent Distillation

• The distillation model deduplicates and merges overlapping blocks.
• Corpus shrinkage: often from millions of words to 2,000–3,000 blocks total.

4. Human-in-the-Loop Review

• Rapid review/edit/approval of all blocks.
• All downstream answers and systems instantly update with changes.

5. Export and Integrate

• Download for AirgapAI offline/local chat.
• Export IdeaBlocks for your vector DB to power any AI pipeline.

Demonstration Highlights

• Free demo: blockify.ai/demo — Paste public content, see generated IdeaBlocks. (Note: Intelligent distillation not available in demo; included in full-service product.)
• Full application: Upload docs, track job progress, review blocks, run Auto Distill, edit/clean blocks, and export refined datasets.
• During distillation: Flag, merge, or remove redundant and non-relevant blocks; single edit updates everywhere.

Life-and-Death Use Case: Healthcare Example

• Scenario: Building a medical FAQ on diabetic ketoacidosis (DKA).
• Naive results: Legacy approaches led to models suggesting dangerous treatment.
• Blockify: Surfaced authoritative, correct treatment protocols—demonstrating impact for any regulated or safety-critical field.

Architecture and Deployment Options

Flexible Models:

• Managed cloud: Iternal hosts the full stack (subscription/licensing).
• Hybrid: Iternal’s cloud UI, but you run your own LLMs.
• Fully on-prem: You license and run Blockify’s models entirely within your environment (no Iternal infrastructure required).

Technical Flow

1. Document parsing (ex: unstructured.io)
2. Chunking (1,000–2,000 chars)
3. Blockify ingest model processes chunks to IdeaBlocks
4. (Optional) Blockify distillation model merges duplicates
5. Embedding (your usual approach)
6. Store in vector DB
7. Integrate to any RAG pipeline

Supported Model Sizes:

• Fine-tuned Llama-based models: 1B, 3B, 8B, 70B parameters.
• Available as plug-in for ML Ops, with max quality in enterprise deployments.

Pricing and Licensing

• AirgapAI: No extra cost; Blockify is bundled with your AirgapAI chat license.
• Managed cloud: Base annual enterprise fee ($15,000), plus $6/page; discounts for volume.
• Private/hybrid/on-prem: $135/user perpetual license (humans or agents), +20% annual maintenance. No infrastructure fee for fully on-prem (you supply compute).

Third-Party Validation: Big Four Consulting Analysis

• Two-month audit: Big Four firm evaluated Blockify on a realistic, albeit small, 17-document dataset.
• Findings: 68.4x accuracy improvement versus naive chunking (lower than 78x due to less redundancy in dataset); substantial reductions in token count per query/query cost.
• Compatibility: Validated with major cloud providers (Google, AWS, Azure), and open-source/on-prem workflows.

How Blockify Supercharges Data Governance

• Practical human validation: Only 2-3,000 blocks per large enterprise project—making human review practical, instead of overwhelming.
• Controlled editing/versioning: Single authoritative blocks push updates everywhere.
• Cleaning, not just deduplicating: Surfaces out-of-scope/legal/irrelevant info; lets teams efficiently trim for full compliance.

End-to-End Example of Value at Scale

• Input: Thousands of proposals with overlapping and duplicative content.
• Workflow: Curate corpus → Blockify ingest → Auto Distill → human review of all merged blocks → export.
• Result: Manageable, reviewed, highly accurate, trusted dataset, ready for your generative AI stack—slashing compute and error rates.

Who Uses Blockify?

Industries and verticals include:

• Pharma/biotech
• Federal agencies, Defense, Government contractors
• IT systems, healthcare, food/retail
• K-12/higher ed, state/local government, and more

Frequently Asked Questions

What is Blockify, in one sentence?

Blockify is a patented system that transforms unstructured documents into LLM-ready IdeaBlocks, cutting hallucinations and boosting AI accuracy up to 78x.

How does it differ from naive chunking?

Instead of arbitrary splits, Blockify builds compact, query-focused blocks, merging duplicates for vastly improved vector search and answer accuracy.

Does Blockify replace my vector DB or embeddings?

No. It’s a text-processing intermediate; your embedding strategy and database remain unchanged.

How much does Blockify shrink my dataset?

Typically down to 2.5% of original size after distillation.

How many blocks do I review?

Generally 2,000-3,000 (about a paragraph each), enabling efficient same-day review.

Does it work with AirgapAI?

Yes, seamlessly—and at no extra charge if using AirgapAI.

Is there a free trial?

Yes: blockify.ai/demo lets you generate blocks from samples. (Intelligent distillation is full product only.)

Deployment options?

Managed cloud, hybrid with your private LLM, or fully on-prem (you run Blockify’s models).

Big Four findings, summarized?

68.4x accuracy improvement on a hard test set, plus strong token-efficiency gains. Commonly up to 78x with larger/redundant corpora.

Licensing for on-prem/private?

$135/user perpetual, 20% annual maintenance. No infra fee for true on-prem.

How to handle regulated content?

Blockify’s distillation and review system ensures only validated, compliant info is surfaced by LLMs.

Getting Started: Your Next Steps

• Experiment now: Paste text at blockify.ai/demo and see IdeaBlocks in action.
• Start with AirgapAI: Blockify included, free to test.
• Go enterprise: Managed cloud, hybrid, or fully on-prem options—curate, ingest, distill, review, export.

Suggested Meta Description

What is Blockify? Discover how Blockify, Iternal Technologies’ patented ingestion and distillation engine, cuts AI hallucinations and boosts LLM accuracy up to 78x while shrinking datasets to 2.5% of original size—plus deployment, pricing, demos, and Big Four validation.

Key Phrases You’ll Understand after Reading this Artcle

• What is Blockify
• Blockify IdeaBlocks
• Blockify intelligent distillation
• Blockify vs naive chunking
• Reduce AI hallucinations
• Improve RAG accuracy
• Vector database readiness
• AirgapAI local chat assistant
• LLM-ready data ingestion
• Enterprise AI data governance

Conclusion: The Enterprise-Ready AI Data Refinery

Blockify is the critical missing link—transforming unstructured data into precise, LLM-optimized blocks. It nearly eliminates hallucinations, enforces data governance, and makes enterprise AI both powerful and trustworthy, at a fraction of previous cost and risk.

Ready to see Blockify in action?
Visit blockify.ai/demo or contact Iternal Technologies for a tailored walkthrough and fast proof-of-value engagement.