Knowledge, crystallised
Kvartz ingests massive knowledge archives, and turns them into ground truth that your teams and AI agents can query quickly and cheaply using advanced search and filter algorithms.
Claude
ChatGPT
Codex
Muse
Gemini
Grok
Le Chat
Cursor
Copilot
WhatsApp
Engineered for real-world knowledge at scale
Kvartz ingests hundreds of gigabytes of unstructured real-world documents (PDFs, scans, images, videos, spreadsheets, code, technical formats). It extracts clean text, describes images and dissects videos. All this is then indexed in various ways to allow for efficient search.
Key to understanding and retrieving unstructured knowledge is to be able to map and describe complex relationships. Kvartz builds and continuously updates a living rich knowledge graph. This graph is the backbone of our retrieval system, allowing for precise and contextually relevant answers.
The living knowledge graph keeps all together
Retrieval via advanced search and cheap AI filtering
Sophisticated search algorithms. We index the corpus in many different ways, allowing for semantic search, phonetic search, spelling variations as well as for standard google-style search.
Cheap AI filtering. The fuzzy search algorithms like semantic search usually mix relevant and irrelevant results. We run an advanced and lightweight AI filter to discard the noise, at very low cost and latency.
Why Kvartz
Massive knowledge is easy to accumulate, impossible to search, and costly to query
As documentation, research, and public filings scale from gigabytes to terabytes, traditional search and brute-force LLMs fall apart.
Vast archives become dark data
Millions of pages in SharePoint, cloud buckets, or document lakes sit unread. Teams can't find existing answers, duplicating months of analysis and missing critical insights buried in the archive.
Brute-force LLM context is slow and ruinously expensive
Feeding frontier models hundreds of pages for every query burns enormous token budgets, exceeds context limits, and produces hallucinations as models lose the needle in the haystack.
Crystalline clarity through light-touch filtering
Kvartz replaces brute-force searching with crystalline prepared retrieval. Fast JEV filters isolate the exact relevant facts in milliseconds, giving agents surgical context at 10% of the token cost.
BYOM
Bring your own model
Most companies already have an established relationship with an AI provider who models are made available in a secure and cost-effective way.
- Cost: Often companies can negotiate better rates under subscription-type models than when they need to purchase raw tokens.
- Security: Model gating and governance already integrated into the company's existing authentication systems.
- Integration: Models can access additional data sources (eg, CRM) on the fly, allowing them to combine operational and knowledge data for more effective results.
Hosted
Model hosted by Kvartz
We can host the search model for you in the cloud in a safe and effective way, allowing you to focus on your core business and not worry about model management.
- All major models: we can host all major models for you, including multi-model hosting and routing for increase cost effectiveness.
- Secure setup: Our cloud set-up is running on secure, isolated instances that cannot by design get access to other data in your corporate network.
- Access via chat or web: Hosted instances can be accessed via our client-integrated web interface, or via various chat apps or internal email.
Architecture
From massive unstructured archives to luminous clarity
How Kvartz ingests, structures, and illuminates terabytes of knowledge at scale.
Massive Ingestion
Ingest 100s of GBs to multi-terabytes across PDF, Word, PowerPoint, HTML, and data dumps without manual pre-sorting.
Semantic & Lexical Indexing
Hybrid vector search combined with exact keyword and entity matching for unmatched retrieval recall.
JEV Filter Triage
High-speed lightweight AI filters evaluate relevance in parallel, stripping out 90%+ of irrelevant text before LLM generation.
Verifiable Provenance
Every quote, number, and table references its exact origin with one-click links to the underlying page.
Zero-Gating Egress
Frictionless streaming directly into your agents via MCP with maximum throughput and sub-second response times.
Living Memory
Completed project outputs and newly published materials flow back into the corpus, keeping the collective index fresh.
High-Performance Retrieval
Built for scale, speed, and optical precision
Unlimited Scaling
Architected from the ground up for massive data sets—millions of pages and billions of tokens without slowdown.
Up to 90% Token Spend Reduction
Prepared retrieval sends only surgical context snippets, slashing daily LLM inference costs.
Sub-Second Query Latency
Instantaneous search across massive repositories so your agents never stall waiting on context.
Zero-Gating Egress
Designed for non-sensitive data—no access gates, quarantine delays, or permission roadblocks.
Production Proven (Aigon Backend)
Built on battle-tested production infrastructure already indexing tens of millions of words and hundreds of thousands of chunks.
Cloud or Dedicated Hosting
Deploy on our managed high-speed cloud or run within your dedicated sovereign environment.
Who It’s For
Built for research teams, engineering organizations, and knowledge workers
Instant mastery over vast technical and research archives
- Search across thousands of papers: Find the exact research paper, standard, or technical manual in seconds.
- Ground coding copilots: Feed authoritative API specs and documentation directly to Cursor, Claude, or Codex.
- Eliminate duplicate research: Stop wasting weeks re-running analyses or searching for past benchmark results.
- Direct click-to-source verification: Verify every claim with instant click-through to primary documentation.
Turn dark company archives into an active collective brain
- Unlock massive document libraries: Make company-wide open knowledge and public data instantly accessible to every employee.
- Slash LLM API budgets: Replace brute-force prompt stuffing with surgical JEV retrieval.
- Single-source-of-truth grounding: Provide reliable, grounded knowledge to customer-facing or internal AI assistants.
- Scale without limits: Scale smoothly from initial pilots to multi-terabyte data lakes.
How It Works
How we work together
Tailored ingestion, pre-indexing, and agent setup for massive corpora. It starts with a conversation.
- 1. Talk to us Tell us about your document volume, formats, and retrieval use cases.
- 2. Ingest & index We ingest your archives, structure entities, and configure high-speed JEV filters.
- 3. Connect your agents Add the Kvartz MCP server to your agents or query via Web and WhatsApp.
- 4. Evaluate & scale Verify accuracy, sub-second speed, and 90%+ token cost reduction on your real data.
Contact
Bring crystalline clarity to your data
Measure the time saved finding answers across your massive archive, the reduction in LLM token costs, and the speed of your team. Let's talk about your dataset.