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The Database for SMEs, Personal AI Apps, and AI Agents.

Encrypted JSON database with SQL

Schema-free storage. Full ACID transactions. Row-level encryption. Built-in key-value cache. All in a single binary.

01 — Foundation
Built for strict reliability.

Schema-free JSON

Store any JSON structure. Query with SQL. Support for nested objects and arrays.

Full ACID

No compromises on data integrity. Synchronous writes to disk, snapshot isolation, and WAL.

Encrypted by Default

Security isn't an afterthought. Row-level and index-level encryption. Rotatable keys.

Built-in RBAC

Granular table-level access control working out of the box. No plugins required.

02 — Velocity
Speed without the complexity.

Automatic Indexing

Every property is indexed automatically. Stop worrying about query optimization.

Built-in Cache

1 Billion key/value pairs. 10K writes/sec, 10K lookups/sec. No Redis needed.

Zero Dependencies

A single binary that runs anywhere. No runtimes, no DLL hell.

Driverless

Use it from Python, C#, Go, or Node via a simple HTTP REST API.

03 — Seamless Search
Find anything, any way.

Exact Match

Lightning-fast lookups by ID, SKU, or any field. Find order #INV-2024-0847 in microseconds across millions of records.

Fuzzy Search

Typo-tolerant matching. "Micheal" finds "Michael". "Kristopher" finds "Christopher". Perfect for call centers and customer service.

Full-Text Search

Search inside documents, notes, and long text fields. Find contracts mentioning "intellectual property" across 50,000 files in under a second.

Semantic Search (AI)

Understands meaning, not just keywords. Search "fast shipping" and find "expedited delivery". Built-in vector embeddings with HNSW indexing.

04 — File Storage
Store, search, and understand your files.

Encrypted File Storage

Files stored alongside your data with AES-256-GCM encryption. No separate object store needed.

25+ Format Extraction

Auto-extract text from PDF, DOCX, XLSX, images, and more. Built-in OCR for scanned documents.

Semantic File Search

Search files by meaning, not just keywords. Find "quarterly revenue" inside a PDF titled "Q3 Report" using AI embeddings.

Version History

Full revision tracking for every file. View, compare, and restore previous versions with configurable retention.

05 — AI Agent
Your data analyst, built in.

Natural Language Q&A

Ask questions in plain English. "How many patients last month?" or "Show invoices over $10K" — answered in seconds from your actual data.

Multi-Step Analysis

Automated deep-dive reports with charts, tables, and insights. "Analyze hospital demographics by department" produces a complete report.

Quick Data Edits

Update records through natural language. "Change Dr. Smith's department to Cardiology" — with confirmation and audit trail.

Scheduled Reports

Set up recurring analysis tasks. Weekly sales summaries, daily patient counts, monthly compliance audits — all automated.

Integration

Simple to use

import requests

base_url = "http://localhost:8080"

# Authenticate and get JWT token
login = requests.post(f"{base_url}/api/auth/login", json={
    "username": "superadmin", "password": "your-password"
})
headers = {"Authorization": f"Bearer {login.json()['token']}"}

# Insert a document — no schema needed
order = {
    "customer": "Acme Corp",
    "items": [
        {"sku": "WIDGET-A1", "qty": 5, "price": 29.99},
        {"sku": "GADGET-B2", "qty": 2, "price": 49.99}
    ],
    "total": 249.93,
    "status": "pending"
}
res = requests.post(f"{base_url}/db/Sales/Order", json=order, headers=headers)
doc_id = res.json()["id"]

# Retrieve by ID
doc = requests.get(f"{base_url}/db/Sales/Order/{doc_id}", headers=headers)
print(doc.json())

# Query with SQL
result = requests.post(f"{base_url}/sql", json={
    "sql": "SELECT customer, total FROM Sales.Order WHERE status = 'pending' ORDER BY total DESC"
}, headers=headers)
print(result.json())
Pricing
Simple & Transparent.
Indicative pricing — subject to change before general availability

Every tier includes the complete database — all features, all search capabilities, file storage, AI agent, encryption, RBAC, and REST API. No feature gates.

Personal

Self-Hosted Single instance · Your infrastructure · Personal projects & side apps
$18 /mo

Personal license · Email support

Business

Self-Hosted Single instance · Your infrastructure · Commercial use
$99 /mo

Commercial license · Email support

Who It's For

Built for every industry that runs on data.

From clinics to courtrooms, warehouses to classrooms — if you store data, manage files, need search, or want AI-powered insights, InventDB is built for you.

Healthcare & Clinics Law Firms Financial Services Retail & E-Commerce Professional Services Real Estate Education & Nonprofits AI Agent Developers Hospitality & Restaurants Field Service & Maintenance Construction & Logistics Insurance & Compliance HR & Workforce

Any business that stores data, manages files, needs search, or wants AI-powered insights from their own data — without the cost and complexity of enterprise software.

Performance

Performance Benchmarks

PostgreSQL is the gold standard of relational databases — battle-tested over 40 years and trusted worldwide. We benchmark InventDB against PostgreSQL because that is the standard we aspire to. Transparency in performance is how we hold ourselves accountable.

View Full Benchmark Report Deployment Configuration Compare with Other Databases
Early Access

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