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KyroDB
SYSTEM READY // V0.1

VECTOR DATABASEWITH MEMORY

Built for RAG workloads and AI agents. Hybrid semantic cache and episodic memory that learns from failures.

<10ms
Latency
70%
Cache hit rate
Scale
STAR ON GITHUB
VECTOR
CACHE
SEARCH
MEMORY
KyroDB
UNIFIED CORE

Vritti

Agents that don't just execute, but remember. KyroDB enables AI to learn from past failures without retraining and weight updates.

Instant Recall
Self-Reflection
EPISODIC MEMORY MODULE

BUILT FOR
AGENTIC MEMORY

KyroDB provides persistent episodic memory for AI agents. Record mistakes, learn from context, and evolve in real-time.

MULTIMODAL CAPTURE

Store visuals, code, and context in a unified vector space.

ADAPTIVE LEARNING

Agents query past failures to optimize future execution paths.

PERSISTENT STATE

Memory that survives process restarts and scales infinitely.

THE FRAGMENTATION PROBLEM

Modern AI stacks are a mess of vector DBs, caches, and KV stores.
Stop managing infrastructure. Start shipping intelligence.

FRAGMENTED ARCHITECTURE

ERROR: High latency detected. Complexity overload.

VECTOR_DB
REDIS_CACHE
SEARCH_ENGINE
TIME_SERIES
MEMORY_STORE
APP_LOGIC
System Status: CRITICAL

PERFORMANCE UNLEASHED

A single, high-performance kernel handling all your data needs with sub-millisecond latency.

10x
QUERY_THROUGHPUT
vs Traditional Vector DBs
<10ms
LATENCY_P99
Consistent at scale
70%
CACHE_HIT_RATE
AI-driven prefetching

SELF OPTIMIZING ARCHITECTURE

KyroDB analyzes access patterns in real-time to optimize data layout and indexing strategies automatically.

INTELLIGENT CACHE

LAYER_01

Predictive data loading based on access patterns

HOT STORAGE

LAYER_02

In-memory active working set for immediate access

DEEP ARCHIVE

LAYER_03

Cost-efficient persistent storage on object store

DATA FLOW: OPTIMIZED // LATENCY: MINIMAL

ZERO CONFIG

One click integration with your existing stack.

PATTERN RECOGNITION

Predictive caching based on query history.

REALTIME SYNC

Event-driven architecture for instant updates.

COST EFFICIENT

Unified storage tier reduces TCO by 60%.

DEPLOYMENT_SCENARIOS

ENGINEERED FOR
MISSION CRITICAL

From high-frequency trading to autonomous agents, KyroDB handles the most demanding workloads.

// System Architecture Overview

INPUTKYRODBOUTPUT
<10ms LATENCY

AI SEARCH RAG

Power your AI applications with lightning-fast semantic search. Perfect for chatbots and recommendation engines.

LIVE UPDATES

REALTIME RECS

Deliver personalized suggestions instantly. No lag between user actions and recommendations.

ALWAYS FRESH

FEATURE STORE

Serve ML features with minimal latency. Keep your AI models fed with fresh, real-time data.

COST SAVER

SEMANTIC CACHE

Cache LLM responses intelligently. Reduce costs and latency by serving similar queries from cache.

REALTIME SCORING

FRAUD DETECTION

Make split-second decisions with instant access to user patterns and historical data.

ZERO CONFIG

DOC INTELLIGENCE

Search through documents using natural language. Metadata filtering included, no extra setup.

System Capabilities

BUILT FOR THE
NEXT GENERATION

KyroDB collapses the modern AI stack into a single, intelligent layer.

01

UNIFIED CORE

Vector search, caching, and persistent memory in a single high-performance kernel.

02

ADAPTIVE INDEXING

Self-optimizing data structures that learn from your query patterns in real-time.

03

ZERO LATENCY

Instantaneous data propagation. Built for the demands of agentic AI workflows.

04

DEV NATIVE

API & Docs available. Drop-in integration. No complex configuration files.

import kyrodb
await kyrodb.connect()
> Connected (2ms)