VERIFIABLE AI MEMORY
Verifiable AI Memory

Connect your data.
Use different AI models.
Get verified answers.

PraqtorDB is a Verifiable AI Memory that integrates your data sources, works with different AI models, and verifies answers against your own data.

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DATA SOURCES

Connect where your data lives

PraqtorDB integrates directly with the cloud platforms your organization already uses. Files are synced, indexed, and organized into a Knowledge Graph automatically.

ACTIVE

Google Drive

Sync files from Google Drive and Workspace. Docs, Sheets, and Slides are exported and indexed alongside PDFs, Word, Excel, and more.

ACTIVE

Microsoft OneDrive

Connect OneDrive for Business or personal accounts. Full folder browsing with selective file sync into your knowledge base.

ACTIVE

Dropbox

Browse and sync files from Dropbox. Read-only access with cursor-based pagination for large folder structures.

COMING SOON

Box

Enterprise-grade Box integration for organizations that rely on Box for secure file storage and collaboration.

COMING SOON

GitHub

Index repositories, documentation, and code files. READMEs, notebooks, and source code become searchable knowledge.

COMING SOON

Adobe Document Cloud

Connect Adobe Document Cloud for PDF-heavy workflows. Sync and index documents stored in Adobe's ecosystem.

MCP CONNECTIONS

Use from anywhere your AI lives

PraqtorDB connects to your AI tools through the Model Context Protocol, so your memory and knowledge follow you across every assistant you use. One memory layer, every model.

VERIFIED

Claude

Native MCP integration across Desktop and Web. Ask Claude about anything in your knowledge base and it retrieves with sources.

VERIFIED

ChatGPT

Connect via MCP. Your context, your sources, accessed from ChatGPT with full source attribution.

COMING SOON

Cursor

For developers. Bring your project context, documentation, and team knowledge into your code editor.

COMING SOON

Windsurf

Memory-aware AI coding. PraqtorDB grounds Windsurf in your real codebase and documentation.

COMING SOON

Gemini

Google's Gemini ecosystem via MCP support. Your knowledge layer, Gemini's reasoning.

COMING SOON

Custom Agents

Any MCP-compatible agent or framework. LangGraph, AutoGen, OpenAI Agents SDK, your own builds.

Your memory, everywhere you think.

Write a note once. Ask about it from Claude tomorrow, from ChatGPT next week. PraqtorDB is the layer underneath. Switch AI tools without losing context. Your data, your continuity.

MCP-NATIVE CROSS-PLATFORM MODEL-AGNOSTIC PERSISTENT MEMORY
WORKS LIKE THIS

Your memory. Any AI.

Different AIs. One memory. Watch a story written inside Claude become retrievable, with sources, from inside ChatGPT, routed entirely through PraqtorDB.

Claude generates the Marigold story
Claude confirms save to PraqtorDB with note + doc IDs
PraqtorDB Notes UI showing the saved notes
PraqtorDB Docs UI showing the structured saved document
ChatGPT answers Marigold and cites note #133 and doc #34

One memory. See it in action.

01
Create content in your LLM
Ask Claude to write a short story about a butterfly named Marigold.
02
Save to PraqtorDB as portable memory
One MCP tool call. Claude writes the story to PraqtorDB and returns the note + doc IDs.
03
Stored in PraqtorDB
Saved as Notes, scoped to your workspace. Persistent, isolated, yours.
04
Indexed and structured
Same content as a Doc with entities, themes, and character profile extracted into the knowledge graph.
05
Retrieve from any LLM, with sources
Switch to ChatGPT (or any MCP-aware AI). Ask about the story. Get the answer back with the source IDs cited.

Wrote a story in Claude. Saved it to PraqtorDB. Asked ChatGPT about it.
Different AIs, one memory.

Your Data, Organized Automatically.

When files are synced, PraqtorDB extracts entities, relationships, and key concepts into a Knowledge Graph. The AI understands context, not just keywords.

No manual tagging. No folder hierarchies to maintain. Your documents become structured, searchable intelligence the moment they sync.

KNOWLEDGE GRAPH ENTITY EXTRACTION RELATIONSHIP MAPPING AUTO-INDEXING
KNOWLEDGE GRAPH
ENTITY
Acme Corporation
Type: Organization · Revenue: $847.3M · Q4 2025
RELATIONSHIP
Jennifer Wu → Sales Department
Role: Top Performer · 136% of Target · Source: Sales Report Q4
ENTITY
Project Falcon
Type: Project · Accuracy: 94.7% · Budget: $5.2M allocated

Choose Your Model.
Keep Your Data.

PraqtorDB supports GPT-4.1, Claude, Gemini, Llama, Grok, and others through a unified AI router. Your team picks the model that works best for the task. The knowledge layer underneath stays the same.

Switch models without losing context. Your data, your choice.

GPT-4.1 CLAUDE GEMINI LLAMA GROK UNIFIED ROUTER
AI ROUTER · MODEL SELECTION
GPT-4.1
OpenAI
Claude
Anthropic
Gemini
Google
Llama
Meta / Groq
QUERY RESULT
Acme's gross margin in Q4 2025 was 72.3%.
divergence 0% · 2 tool calls · 3.8s

Verified Answers.
Not Hallucinations.

A built-in verification layer cross-checks responses across independent retrieval paths. When both paths agree, you get a verified answer grounded in your data.

When they disagree, the system flags the divergence. Transparency over confidence.

DUAL-PATH VERIFICATION DIVERGENCE DETECTION SOURCE GROUNDING PATENT PENDING
VERIFICATION ENGINE
PATH A
search_kb
PATH B
ask_assistant
RESULT
VERIFIED
Q: What is the tuition for Atlas Academy?
A: $18,500. Scholarships cover up to 60%.
✓ DIVERGENCE 0% 2 tool calls 4.3s

Connect via MCP.
Use From Anywhere.

PraqtorDB supports the Model Context Protocol (MCP), allowing AI platforms like Claude, Cursor, and Windsurf to access your memory and knowledge directly.

Your data stays in one place. Your AI tools connect to it wherever you work.

MODEL CONTEXT PROTOCOL CLAUDE CURSOR WINDSURF CHATGPT
MCP INTEGRATION
CONNECTED TOOLS
search_conversations
search_entities
get_deep_memory
create_note
mcp.praqtordb.com/sse
HOW IT WORKS

From documents to verified answers

Connect. Index. Ask. Verify.

STEP 01

Connect Your Sources

Link Google Drive, OneDrive, Dropbox, or other cloud storage. One-time OAuth setup, read-only access.

STEP 02

Index Your Data

Files are synced, extracted, chunked, and embedded. Entities and relationships flow into the Knowledge Graph.

STEP 03

Ask Questions

Use the AI router to query your data with the model of your choice. Or connect via MCP from Claude, Cursor, or Windsurf.

STEP 04

Get Verified Answers

Responses are cross-checked across independent retrieval paths. Answers are grounded in your data, not hallucinated.

WHY PRAQTORDB

Your data deserves a better AI layer

PraqtorDB does not replace your tools. It makes the AI you already use more valuable by grounding it in your own data.

Without PraqtorDB
✕ Data scattered across drives and platforms
✕ AI answers not grounded in your files
✕ Locked into one AI provider
✕ No verification of AI responses
✕ Knowledge lost between sessions
With PraqtorDB
✓ Data connected from Google, OneDrive, Dropbox
✓ Answers grounded in your own documents
✓ Switch between AI models freely
✓ Dual-path verification on responses
✓ Persistent memory via Knowledge Graph
GET STARTED

Add an intelligence layer to your platform

PraqtorDB can complement your existing platform by adding a verified, model-agnostic intelligence layer on top of your customers' data.

hello@praqtordb.com
Claude generates the Marigold story
Claude confirms save to PraqtorDB
PraqtorDB Notes UI
PraqtorDB Docs UI
ChatGPT cites the sources

One memory. See it in action.

01
Create content in your LLM
Ask Claude to write a short story about a butterfly named Marigold.
02
Save to PraqtorDB as portable memory
One MCP tool call. Claude writes the story to PraqtorDB and returns the note + doc IDs.
03
Stored in PraqtorDB
Saved as Notes, scoped to your workspace. Persistent, isolated, yours.
04
Indexed and structured
Same content as a Doc with entities, themes, and character profile extracted into the knowledge graph.
05
Retrieve from any LLM, with sources
Switch to ChatGPT (or any MCP-aware AI). Ask about the story. Get the answer back with the source IDs cited.