SandLogic · 0 reviews

SandLogic

Enterprise AI development for edge devices, simplified through low-code/no-code innovation

Data Science and Machine Learning Platforms

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About SandLogic

SandLogic is a full-stack enterprise AI platform that democratizes deep learning application development for edge devices through its Low-Code/No-Code (LCNC) architecture. The platform eliminates barriers to AI adoption by enabling organizations to build, train, deploy, and manage sophisticated machine learning models without requiring extensive coding expertise. SandLogic streamlines the entire AI lifecycle—from data preparation through model optimization to edge device deployment—reducing development time and technical complexity. By leveraging AiDOOS marketplace integration, enterprises can enhance deployment governance, access specialized AI talent for model optimization, ensure seamless integrations with existing infrastructure, and accelerate time-to-market for edge AI solutions. The platform supports full model lifecycle management, provides built-in optimization for resource-constrained edge environments, and delivers robust scalability across distributed device networks, making enterprise-grade AI accessible to organizations of all technical maturity levels.

Challenges It Solves

High complexity and steep learning curve for developing deep learning models
Limited resources and technical expertise for building edge AI applications
Lengthy deployment cycles from model development to production edge devices
Difficulty managing and updating models across distributed edge device networks
Cost barriers associated with specialized AI development teams and infrastructure

Faster AI model development and deployment cycles

Reduced technical barriers for non-expert developers

Improved operational efficiency in edge AI management

Use Cases

Manufacturing Quality Control

Deploy computer vision models to production lines for real-time defect detection without cloud dependency, enabling faster decision-making and reduced waste.

72% Real-time quality defect detection with sub-second latency

Retail & Inventory Management

Build shelf-scanning and inventory tracking applications using LCNC tools, automating stock management across distributed store locations without coding expertise.

58% Automated inventory tracking across multi-location retail networks

IoT Predictive Maintenance

Develop anomaly detection models for industrial equipment monitoring, predicting failures before they occur and reducing downtime across connected device networks.

81% Predictive equipment failure detection with 80% accuracy improvement

Smart City Infrastructure

Rapidly deploy traffic management, environmental monitoring, and public safety AI applications across city-wide edge device networks with minimal technical overhead.

65% Large-scale AI deployment across distributed city infrastructure

Healthcare Point-of-Care Diagnostics

Create portable diagnostic applications for remote and rural healthcare settings, enabling local inference without cloud connectivity while maintaining HIPAA compliance.

74% Offline diagnostic capability with enterprise-grade security

Pricing

Pricing available on request

SandLogic pricing is customized based on your team size, integrations, and requirements. AiDOOS will get you a scoped proposal — for free.

Schedule a Meeting

Key Features

Low-Code/No-Code Model Development

Build AI models without extensive coding expertise

Enable business teams to develop production-ready models independently

Edge Device Optimization

Automatically optimize models for resource-constrained environments

Deploy models to edge devices with reduced memory and compute footprint

Full-Stack Model Lifecycle Management

Manage models from training through deployment and monitoring

Unified platform for complete AI application development and governance

Distributed Model Deployment

Deploy and update models across multiple edge devices seamlessly

Scale AI applications to thousands of edge devices simultaneously

Pre-built AI Components Library

Leverage templates and pre-trained models for rapid development

Reduce development time from months to weeks for common use cases

Real-time Model Monitoring & Analytics

Monitor model performance and health across edge deployments

Identify and address model degradation before impacting operations

Reviews

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Enterprise Readiness

Model Encryption

Role-Based Access Control (RBAC)

Secure Edge Deployment

Audit Logging

Data Privacy Protection

Integrations

8 total apps

Import and optimize TensorFlow models for edge deployment with automated quantization and pruning

Convert and deploy PyTorch models to edge devices with performance optimization

Manage containerized edge deployments and orchestrate model updates across distributed clusters

Connect IoT devices and edge servers for real-time model inference and telemetry collection

Deploy and manage models across AWS edge devices and on-premise infrastructure

Integrate with Microsoft Azure IoT platform for hybrid edge-cloud AI deployments

Package and containerize SandLogic applications for consistent edge deployment

Automate CI/CD pipelines for continuous model training, testing, and edge deployment

AiDOOS Managed Deployment

Deploy SandLogic in

AiDOOS handles setup, CRM integration, SSO config, and user provisioning. Your team goes live — not your IT department.

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Deployments

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Adoption rate

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Post-deploy sat.

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Time to value

Prerequisites

Configuration Options

Virtual Delivery Center · A new delivery category

A Virtual Delivery Center for SandLogic

Pre-vetted experts and AI agents in the loop, assembled as a delivery pod. Pay in Delivery Units — universal pricing across roles, seniority, and tech stacks. No hiring, no contracting, no procurement cycle.

Plans from $2,000 — Starter Pack, 10 Delivery Units, 90 days
Refundable on unused Delivery Units, anytime — no questions asked
Re-delivery guarantee on acceptance miss
Pre-flight delivery sizing — you see the plan before you commit

Get a delivery plan for SandLogic What’s a Virtual Delivery Center?

How a Virtual Delivery Center delivers SandLogic

Outcome-based delivery via AiDOOS’s VDC model. Why VDC vs traditional consulting? →

Outcome-Based

Pay for results, not hours

Milestone-Driven

Clear deliverables at each phase

Expert Network

Access to certified specialists

Implementation Timeline

Discover

Requirements & assessment

Integrate

Setup & data migration

Validate

Testing & security audit

Rollout

Deployment & training

Optimize

Performance tuning

Schedule a Meeting

Frequently Asked Questions

What programming experience do users need to build models with SandLogic?

SandLogic's Low-Code/No-Code platform is designed for business users, domain experts, and citizen developers with minimal to no programming experience. Visual workflows, pre-built components, and guided templates enable anyone to develop AI models.

Can SandLogic models run entirely on edge devices without cloud connectivity?

Yes, SandLogic is specifically optimized for edge inference. Models are compiled and optimized to run locally on edge devices, enabling offline operation. This is critical for latency-sensitive and disconnected environments.

How does SandLogic handle model updates across distributed edge networks?

SandLogic provides centralized model management with intelligent update orchestration. Organizations can schedule updates, manage versioning, and rollback across thousands of edge devices from a unified dashboard.

Does SandLogic support custom model architectures and transfer learning?

Yes, SandLogic supports importing pre-trained models from TensorFlow and PyTorch, enabling transfer learning workflows. Advanced users can extend models with custom layers while maintaining LCNC accessibility for configuration and deployment.

How does AiDOOS marketplace enhance SandLogic deployments?

AiDOOS provides access to specialized AI talent for model optimization, data scientists for complex use cases, and integration experts for connecting SandLogic with enterprise systems. This accelerates time-to-value and reduces implementation risk.

What edge devices and operating systems does SandLogic support?

SandLogic supports ARM and x86 architectures across Linux, Windows IoT, and specialized edge OS platforms. It's compatible with major IoT platforms including AWS IoT Greengrass, Azure IoT Edge, and custom edge infrastructure.