Imagine a tool that simplifies the creation of an Independent Data Layer, empowers you to deploy advanced controls effortlessly, and seamlessly connects buildings to various partner applications like fault detection or energy optimization - that's exactly what Normal Software does. What sets Normal apart is its simplicity. Unlike many other solutions, Normal is easily deployable as a standalone docker container, enabling smooth integration into existing products and IT infrastructures or directly embedding into your own product.
Founded in 2020, Normal Software was created by industry pioneers to bring building programming into the modern era of software development. The team at Normal specializes in building controls, data management, and applications for IoT (Internet of Things) analytics. They focus on providing open, transparent, and portable solutions for controlling and analyzing IoT devices.
Key features of the Normal Framework (NF) offering include:
- Open & Transparent Approach: NF emphasizes openness and transparency in the design, with support for native BACnet and an API-first approach.
- Powerful APIs and SDK: NF offers powerful APIs and a JavaScript SDK for developers to easily integrate and extend their solutions. This eliminates the need for proprietary languages or complex tools.
- DataOps Features: NF provides tools for DataOps, including data modeling, normalization, quality monitoring, and rapid identification and resolution of outages and quality issues. They also support an "Edge-Only Model" for data processing.
- No 3rd Party SaaS Subscription: NF does not require a third-party subscription for monitoring and securing data, offering a self-contained solution.
Normal offers a comprehensive platform for managing and controlling IoT devices and data, with a focus on openness, flexibility, and ease of integration. They look forward to working with you to create a world where IoT analytics and controls are open, portable, and sharable.
Northern Arizona University faced retiring tradespeople and 6,000+ scattered building documents, so the team used generative AI to extract system relationships and organize them into a searchable knowledge graph. The result: faster onboarding and less reliance on tribal knowledge.
CannonDesign watched a BAS access quote climb from $66K to $100K, then brought in an MSI to review the architecture and cut it to $29K.
Northern Arizona University’s CIO realized that aggregating IoT data wasn’t the hard part; relational context was. After choosing buy over build, the team moved from raw BACnet feeds to ontology-driven HVAC control, achieving 30% energy savings.
At LAX, environmental reporting once meant field visits, clipboards, and emailed meter photos. The airport is now connecting 1.2M+ data points and normalizing what already exists to improve compliance and create new sustainability opportunities.
Lincoln Property Company’s Chris Lelle realized that burdened engineers can’t each manage 300,000 sq ft by diving deep into BAS data—so he used FDD to simplify the troubleshooting his techs need to do.
CannonDesign added smart building scope to their office after bids were in, and Div 23/26 partners didn’t understand what “IDL” meant to their scope. They had to redraw Division 25 boundaries and clarify responsibilities to prevent the job from slipping.
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