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AI is driving incredible demand for data centers, power generation, and manufacturing facilities, but the companies that design, build, and maintain these assets are facing retiring workforces, increasing complexity of regulation, and growing demand for labor. Briq provides digital labor to these industries that allow them to fill much-needed roles in accounting, operations, risk, legal, and human resource functions.
To create this digital labor force, Briq is pursuing a multi-model approach in its technology stack that combines multiple technologies– robotic process automation, generative AI, computer vision, and predictive modeling. These “workers” are software robots that mimic how humans act, think, and communicate. In order to approximate the acting, thinking, and communicating needed to perform these tasks, Briq uses a combination of open source large language models and proprietary technology.
AI Decision-Making Core
The Rules and Recommendation Engine is the robot’s brain, where advanced AI meets real-time decision-making. Built on LAM (Logic Application Model) frameworks, this core processes complex data sets and automates workflows based on pre-programmed rules, predictive analytics, and real-time learning. The core continuously optimizes tasks by offering intelligent recommendations, learning from every interaction to enhance future performance.
Visual AI & Data Recognition
Briq’s Vision Engine brings advanced AI vision to the digital worker. Capable of interpreting screens, documents, and reports, it uses computer vision and AI-driven data analysis to transform visual inputs into actionable insights. Whether it’s scanning invoices, identifying patterns in financial reports, or interpreting construction blueprints, the vision capabilities streamline processes, reducing manual input and human error.
Conversational AI Generator
The Interaction Engine, powered by advanced Large Language Models (LLMs), excels at text-based communication, enabling seamless, human-like conversations in workflow automation. Whether through chat interfaces or embedded systems, the software robot processes written input with precision and understanding, instantly ready to act. While voice interaction is in development, text commands already bring the robot’s intelligence to life.
Briq uses open source large language models like Meta’s Llama to train on industry-specific questions and topics that may arise. Paired with this is a Response Engine, which delivers real-time, context-aware replies that go beyond simple answers to foster meaningful dialogue. Briq’s LLM-driven responses are nuanced, accurate, and tailored to business needs, automating communications in a way that feels both efficient and human.
Emotive AI & Behavioral Insight Processor
Powered by open sourced LLMs, this engine drives the robot’s ability to simulate human-like instincts, including empathy, tone recognition, and behavioral prediction. Whether it’s understanding the emotional context of a client’s message or preempting the needs of a project team, the robot’s emotional intelligence elevates interactions to a whole new level.
RPA & Task Automation
The powerhouse of the robot’s capabilities lies in the Xcelerate Action Engine, the ultimate RPA (Robotic Process Automation) module. Designed with large action model (LAM) technology, Xcelerate doesn’t just respond to commands—it executes them. From triggering workflows, automating routine tasks, and integrating across systems to managing backend processes, Xcelerate turns decisions into action with lightning speed. It orchestrates a seamless flow between decision-making and execution, automating the heavy lifting across your operations, all while getting smarter with every interaction.
Giving Meaning to Data
The Briq Graph serves as the foundation of Briq’s platform, providing an ontology that unifies all objects under one common language. This ontology creates a structured framework where every element—whether it's financial data, project details, or workflow components—is interconnected, enabling seamless communication and automation across the system. By powering everything through this shared language, the Briq Graph ensures consistency, accuracy, and ease of use, allowing digital workers to operate more intelligently and efficiently. This common language facilitates smooth integration between systems and processes, driving better decision-making and enabling comprehensive automation across the construction lifecycle.
The Briq Platform
While marketed as digital workers, Briq’s technology falls into the Business Optimization and Automation Technology (BOAT) category. BOAT represents a transformative shift in how organizations approach automation. Moving beyond simple task automation, Briq's platform combines sophisticated technologies like process mining, large action models, large language models, and machine learning to deliver meaningful business outcomes. Briq is more than just for automating individual tasks, but is used to orchestrate entire business processes across departments and systems.
