Unlock the future of

Asset-Intensive and HSE
(Health, Safety & Environmental)
Industries with AI.

OPEX/CAPEX (Operational Expenditures/Capital Expenditures) impact will be the driver for AI adoptions within HSE (Health, Safety, and Environmental) and Asset Intensive industries.

AI in HSE (Health, Safety, Environmental) Asset Intensive businesses: Driving Real Value

Artificial Intelligence, will have a large impact all many industries, but within the asset intensive oil and gas business, it will largely be accepted once it proves value in OPEX/CAPEX (Operational Expenditures/Capital Expenditures) impact. To put it bluntly, it must provide a large value proposition in bringing down costs and improving margin.

Predictive
(machine learning)

1. Predictive

Generative AI (LLMs that generate text, code, and summaries)

2. Generative-AI

Agentic (acting independent, or one way to think of it is analysis, action, with automation)

3. Agentic

AsInt’s Vision

To provide agentic agents that represent key roles within the APM (Asset Performance Management) and AIP (Asset Investment Planning) work processes.

For example, a Reliability Assistant.ai that has all the knowledge of standards, the customers work processes, and the customers data. The Reliability Assistant.ai would never sleep, always interrogating data, acting as a companion to the reliability engineer making recommendations, taking action to help solve problems, and automating key steps. Ultimately, bringing down the costs of operations to the owner of the process facility.

In the case of the Reliability Engineer.ai, OPEX impact can be achieved by reducing the number of external consultants organizations rely on, using a less senior engineer to perform the activities, and automating key work processes.

The same approach can be applied to a corrosion engineer, inspection engineer, maintenance planner, etc….

AsInt does not currently believe the Agentic AI will completely replace team members, but offers tools to assist and bring down the costs. However, we do recognize the industry wants to move into automating complete work processes to fullest extent possible.

Though AsInt believes Agentic AI will provide the economic tipping point, we will continue to invest in Generative and Predictive capabilities as well and embed them within our product lines.

AsInt’s Journey

We are transforming engineering with smart AI tools that combine deep expertise and automation for the future.

Predictive (machine learning)

Since 2017

Predictive (machine learning)

AsInt founding and core competency has been based “rule-based ”predictive algorithms. For example, traditional end of life calculations or risk transition algorithms. In the past year, we have invested in predictive damage detection using a traditional neural network/LLM approach.

Generative (LLMs)

Starting in 2024

Generative (LLMs)

AsInt is starting to weave in agents in our applications. These are represented as Chatbots that have context around standards such as API-510, but also performing tasks such as P&ID scraping of data, or U-1 data automation.

Agentic AI (automation)

2025 and beyond

Agentic AI (automation)

Just as the idea of fitting 4,000 songs into your pocket once revolutionized music, AsInt is revolutionizing industrial inspections by putting the expertise of 4,000 engineers and consultants into one powerful Agentic AI tool.

Where we are at today

AsInt currently offers AI-powered mobile inspection tools with predictive and generative features, plus an advanced agent for Fitness for Service analysis and automation.

Predictive

IntelliSuite, AsInt’s mobile inspection application

Feature/Function: Image Damage Detection

IntelliSuite, AsInt’s mobile inspection application, features advanced predictive Image Damage Detection technology that accurately identifies and assesses damage in real-time. This capability helps inspectors capture critical data efficiently, improving inspection accuracy and enabling proactive maintenance decisions.

Generative

IntelliSuite, AsInt’s mobile inspection application

Feature/Function: API 510/570 Assistant via chatbot

AsInt curated API 510/570 Inspector in your pocket!
Ask questions of API 510/570 like you have a seasoned inspector working along with you.

Generative

IntelliSuite, AsInt’s mobile inspection application

Feature/Function: U1 data scrape

Whether it’s a U-1 form or any other text-based document, simply snap a photo or upload a PDF/image. The platform instantly extracts the content and presents it in clean, usable text format.

Generative

IntelliSuite, AsInt’s mobile inspection application

Feature/Function: Drawing feature count (CML’s for example)

Upload a picture of a drawing, such as a P&ID or PFD, and AsInt Al will count features such as number of Elbows, Tees, Reducers, and CML points.

Generative and Agentic

AI assistant for FFS (Fitness for Service) analysis

Generative and Agentic AI fitness for service agent to guide the user though a fitness for service process.

Coming soon by AsInt, Inc, AsInt is launching our first API 579 application. The FFS ai agent will guide the user through the process, making recommendations along the way, analyzing data, while providing a QA/QC function.

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    Blogs

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    SAP International Conference for Chemicals

    AsInt, Inc. appreciates your kind invitation to the International Conference for Chemicals, presented by SAP and T|A|C Events – A TAC Insights Brand. Our Team has great interaction at the event, and we look forward to meeting you again soon. On behalf of AsInt, Inc., I would like to express our sincere gratitude for extending […]

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    Risk-Based Work Selection and Benefit-to-Cost Ratio in Prioritizing and Approving OPEX Spend

    Introduction In asset-intensive sectors such as energy, manufacturing, and infrastructure, organizations must continually strike a balance between cost control and operational performance. Managing operational expenditure (OPEX) effectively, without compromising safety, reliability, or regulatory compliance, is a persistent challenge. Two essential methodologies support this decision-making process: Risk-Based Work Selection (RBWS) and the Benefit-to-Cost Ratio (BCR). RBWS […]

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