Automation That Enable Continuous Auditing
Glias executes each business workflow as a “verifiable sequence of single actions” and records the audit trail for every single process step-by-step. This allows you to prove quality, accountability, and compliance in real time, rather than just at the end of the fiscal year.
The Issue of Reliability in Business Workflows
Most business processes deliver only the final result without preserving a verifiable record of how it was produced. Thus, it is difficult to demonstrate quality, accountability, and auditability—especially in real time. As AI becomes more integrated into our society, AI-generated output will flood the world. When that time comes, the question will be: What is reliable, and what can be trustworthy? Glias addresses the challenges of an AI-driven society by starting with filling this trust gap.
How it works
Break down the process into “semagrams” (single-function modules) and streamline them into a single standardized procedure.
Every step performs exactly one defined action and automatically records proof that it ran.
You can audit every step in real time. Exception cases are escalated to the appropriate human for verification, but they are also logged and recursively fed back into the automation process.
Examples: Payment reconciliation, inspection verification, execution verification
Solution 01 · Workflows built with semagrams
Glias breaks each workflow into single-function modules(semagrams) in one standardized sequence. The process becomes a decipherable, traceable chain — not a black box.
semagram A group of single-function process modules defined as verbs that record traces as they are executed.
Solution 02 · Auditable in real time, not just at the end of the reporting period
The audit does not have to wait until the end of the fiscal year, as records are created as each step is completed. Audit reviewers can verify the process, sequence, and output at any time.
Solution 03 · The Accumulation of Human-in-the-Loop Decisions
For cases that cannot be resolved automatically, Glias automatically escalates them to the appropriate handlers. This decision-making process is recorded and structured using the same mechanism as automated tasks, and is automatically recursively fed back into the workflow, ensuring that the same exceptions will be processed automatically in the future.
How it's different
Traditional automation
It executes automation that is dependent on a specific environment and returns only the final result. The process by which that result is reached is opaque, and if an exception occurs, the entire flow halts, requiring investigation to determine where it stopped and making necessary adjustments each time.
Glias
Each step is executed as a verifiable action, and a record of the process is maintained step by step. Exceptions are handled through a human-in-the-loop approach, making the process itself verifiable without interrupting the overall business flow.
Who it's for
Rather than just reports, you can provide clients with verifiable records demonstrating quality and compliance for every single case.
You'll have a truly reliable audit trail throughout the entire outsourcing process.
Stop waiting for year-end reviews. Verify the process continuously, as it runs.
About Glias, Inc.
As AI becomes more prevalent in our society, what will truly be needed is not which AI model is best or the AI models themselves, but rather the infrastructure required to safely and continuously integrate AI into business operations. While AI can process large volumes of data at high speeds, it inherently tends to obscure the basis for decisions, the data used, execution permissions, approvers, and accountability in the event of failure. To ensure this, business processes must be redesigned from the onset to leave a verifiable audit trail, be comprehensible to AI, and clearly manage permissions and scope of execution. Of crucial importance is a system that verifies the provenance of input data and outputs, centrally controls multiple AI agents across the entire organization, and records and reusable exceptions requiring human intervention and approval decisions. This is not simply a story of adopting AI to existing business processes. Similar to how the transition from steam engines to electric power fundamentally changed production methods—including factory layouts and assembly-line production using conveyor belts—mastering AI requires a fundamental redefinition of the values and assumptions underlying business operations, auditing, accountability, and organizational management. Consequently, competitiveness in the AI era is not determined merely by “which AI to use.” Instead, what matters is the extent to which a company can visualize and verify AI operations and establish mechanisms to learn from exceptions and feed those insights back into business improvement. Glias predicts that as AI enables the creation of an unlimited number of deliverables, the value of the deliverables themselves will rapidly decline in relative terms, while the value of an execution platform equipped with audit trails, provenance, approvals, and clear lines of accountability will simultaneously grow. At the same time, Glias aims to provide a platform that makes operational tacit knowledge—which has not been reliably shared until now—as visible as possible and enables it to be handed over to AI.
FAQ
We're in alpha, running proofs of concept with a small number of design partners on real workflows.
A group of single-function process modules that execute a single, clearly defined, and unambiguous function defined by a verb, while recording a trace of that execution as it occurs.
RPA automates a series of tasks and delivers the results. In other words, it speeds up only the task flow. Glias makes the entire automation process verifiable—each step is recorded as it is executed, and exceptions are handled through a “human-in-the-loop” approach. This enables the flow to be nearly fully automated.
The automated workflow defined by semantic characters relates to data in the same way that water flows through a water pipe. Except for the exception handling case, all data is automatically processed according to the rules. While exception handling is the only point at which human intervention occurs, Glias is designed so that customer data is generally not stored internally for extended periods.