PRIVATE BETA — EDGE INTELLIGENCE PLATFORM SUITE

Intelligence
lives at the edge.
not in the cloud.

Three products built for a world where devices think, interfaces learn, and databases heal themselves. ShorelineDB orchestrates IoT. EdgeLiteDB.js adapts your UI. HelioSyncDB synchronizes with data.

Three tools.
One philosophy.

IOT CANVAS IDE · MIDDLEWARE
ShorelineDB
shorelinedb.io ↗

SwiftUI wire-frames meet industrial IoT control. Draw agentic workflows visually on a canvas — drop AI monitors directly inside real devices, wire sensor events to firmware upgrades, and let the system learn your routines and optimize them autonomously.

TYPE
Canvas IDE
PROTOCOL
MQTT + WebSocket
TARGETS
ESP32 · Arduino
AI MODE
Embedded Agent
  • Canvas drag-and-drop: wire IoT device graphs like UI screens
  • AI monitors embedded inside real firmware — learns & upgrades OTA
  • InstructionTable: priority-aware, TTL-windowed command delivery
  • Offline-first: Bloom-filter dedup, time-delayed replay queue
  • Visual IDE: wire screens like SwiftUI but for edge intelligence
shoreline.workspace — canvas.v0.1 ● LIVE
canvas.init — 5 nodes loaded
TempSensor #A3 → AI Monitor routine-5
AI learned: HVAC cycle reduces 18% at 22:00
ADAPTIVE FRONTEND RUNTIME
EdgeLiteDB.js
edgelitedb.io ↗

React, but it learns. An agentic JavaScript runtime that installs itself, adapts to the device context, measures anonymous error logs from real users, scrapes JS templating forums for patterns, and continuously evolves its own component tree to stay current and efficient.

TYPE
JS Runtime
INSTALL
Agentic · Auto
TARGETS
Mobile · Laptop · Edge
TELEMETRY
Anonymous Errors
  • Agentic install: detects device, bandwidth, screen context
  • Anonymous error telemetry feeds adaptive UI improvement loop
  • Forum-scraping knowledge agent keeps templating patterns current
  • Self-optimizing component tree based on real usage patterns
  • Drop-in replacement for React — better on constrained devices
edgelitedb.js — adaptive.runtime ● ADAPTING
RENDER EFF.
94%
ERROR RATE
4%
PATTERN AGE
2d ago
KNOWLEDGE SRC
247
mobile-viewport low-bandwidth touch-optimized dark-mode forum-sync error-batch-61 pattern-upgrade vdom-diff-v3
initializing adaptive context engine...
BSON IN-MEMORY NOSQL · QUERY SYNAPSE
HelioSyncDB
heliosync.io

An in-memory BSON NoSQL database with a biological cognitive mutation: Query Synapse. It doesn't read queries — it perceives them as living neural networks. Equipped with Table Hypothesis, it auto-heals schemas, upgrades firmware, and resolves computational anomalies before they surface.

ENGINE
BSON In-Memory
FALLBACK
Flash Persistence
SKILL
Query Synapse
HYPOTHESIS
Table Auto-Heal
  • Query Synapse: perceives data structures as living neural networks
  • Diagnoses inefficiency as if detecting illness — heals instinctively
  • Table Hypothesis: infers & rebuilds schemas from minimal fragments
  • Cross-paradigm: SQL ↔ NoSQL ↔ BSON translation seamlessly
  • Temple databases: structurally balanced, scalable, self-healing
heliosync — query.synapse.v0.1 ● SYNCHRONIZED
// Query Synapse standing by // Perceiving data structures as living networks... // Paste any broken, partial, or cross-paradigm query above
HELIOSYNCDB — GENETIC SKILL

Query
Synapse

You possess an innate, almost biological ability — a cognitive mutation that allows you to perceive, interpret, and manipulate data structures as if they were living neural networks. Joins become bridges. Indexes pulse like arteries. Schemas form skeletal frameworks.

🧠
Neural Perception
Sees queries as flowing systems, not syntax strings
🩺
Instant Diagnosis
Detects corruption like illness in a body
Real-Time Rewrite
Optimizes by instinct, not memorized syntax
🧬
Temple Databases
Generates self-healing, structurally balanced schemas
// HelioSyncDB Query Synapse — ready // Supported paradigms: SQL · MongoDB · BSON · NoSQL · broken fragments // Output: healed · optimized · translated · temple-ready // // The database doesn't just process your query. // It synchronizes with it.

Self-healing intelligence
at the schema level

Table Hypothesis enables HelioSyncDB to autonomously determine when, where, and how to update hardware, software, or firmware — and resolve computational-scientific anomalies that haven't been seen before.

BIOLOGICAL
Schema Reconstruction
Infers intended schema design from minimal fragments. Rebuilds broken structures like a body healing a fracture — guided by structural memory.
AUTO-HEAL
Cross-Paradigm Translation
Restructures query logic across relational, document, in-memory, and time-series systems without loss of intent or performance profile.
INSTINCT
Firmware Upgrade Timing
Monitors device telemetry and data drift patterns to determine the optimal moment to push hardware or software updates — no manual scheduling.
UNFORESEEN
Anomaly Resolution
Handles unexpected computational-scientific events through inference and pattern matching — resolves what no prior rule was written for.
TEMPLE DB
Self-Healing Schemas
Generates structurally balanced "temple databases" — schemas that are scalable, normalized, and continuously monitor their own integrity.
COGNITIVE
Query With Your Eyes
Absorbs raw data patterns and produces optimized queries without deliberate composition. Pure synchronization between operator and data.
UNIFIED ARCHITECTURE

How the three products
talk to each other

📡
IoT Device
ESP32, sensors, actuators — any hardware node
🎨
ShorelineDB
Canvas IDE — wire, monitor, AI-upgrade devices
MQTT + WS
Hybrid sync, offline replay, Bloom filters
🧬
HelioSyncDB
BSON core — Query Synapse + Table Hypothesis
EdgeLiteDB.js
Adaptive UI runtime for user-facing surfaces
Ready to deploy at the edge?

Private beta — limited access. IoT, industrial, and research teams prioritized.