Blog

Energy Strategy First, Sustainability as a Result

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Energy volatility is making emissions and energy reduction a core business imperative, as energy can account for 50% of OPEX. To succeed, leaders must move beyond the noise and focus on capital-efficient, high-impact solutions with verifiable results. Real transformation comes from proactive, closed-loop systems that make thousands of micro-optimizations daily, delivering the real-time energy and cost savings necessary for industrial competitiveness and survival.

Reflecting on Verdantix’s 2025 Green Quadrant for Industrial AI Analytics

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Imubit CEO Gilad Cohen reflects on the 2025 Verdantix Green Quadrant, highlighting the need for scalable, expert-driven AI. While the report benchmarks the industry, Imubit differentiates itself by moving beyond analytics to Closed Loop AI. Our Deep Learning Process Control Platform automates setpoint adjustments 24/7, turning predictions into guaranteed outcomes. With 100+ deployments, Imubit delivers sustained margin and efficiency gains across the process industry.

Conversion Without Transformation: The Hidden Risk in AI Adoption

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The biggest risk in AI adoption is "conversion without transformation": simply automating old processes instead of fundamentally changing how teams work. Real transformation requires a mindset shift and the integration of deep domain expertise. Imubit’s Closed Loop AI Optimization (AIO) enables this by uniting operations, engineering, and commercial teams through real-time, smart, and collaborative economic optimization grounded in real-world process knowledge.

Oxbow

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Oxbow, a global leader in petroleum coke calcination, implemented Imubit’s Closed Loop Industrial AI to optimize its Rotary Kiln operations. By anticipating system volatilities and adapting processes in real-time, the solution allows Oxbow to maximize yield and energy efficiency while meeting strict specifications. The results include a 1-3% increase in yield and a 15-30% reduction in natural gas consumption, providing true AI for industrial operations.

Big West Oil

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Big West Oil replaced costly, generic simulators with Imubit’s Dynamic Process Simulator to address complex operator training needs. By training a Reinforcement Learning Controller in a safe, AI-driven environment, operators can now test and compare optimization strategies. This transition has fostered collaboration, enhanced ownership of process optimization, and created healthy competition to identify the most effective strategies for the refinery.

Ash Grove Cement

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Ash Grove Cement partnered with Imubit to build a sustainable optimization automation infrastructure using Deep Learning Process Control (DLPC). By running 10,000 years of simulations in a virtualized plant, the AI developed behavioral control mimicking top operator functions. Ash Grove selected Imubit as the only industrial AI solution that combines deep learning with the transparency needed to meet its rigorous criteria for modern cement production.

What LATAM is Teaching Us About AI Adoption: Lessons from Innovarpel 2025

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The Innovarpel 2025 LATAM Conference highlighted that successful AI adoption is a culture shift, not just a tech update. LATAM leaders are prioritizing workforce transformation, breaking down operational silos, and using AI to anticipate problems rather than reacting to them. By focusing on decision quality, emotional intelligence, and continuous upskilling, they are driving long-term resilience and growth over simple automation.

Digitalization & AI in Mining North America 2025—Five Strategic Takeaways

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The mining sector is shifting from AI pilots to enterprise-scale digital programs. Key themes from Vancouver include the need for clear ROI, early cybersecurity involvement, and digital twins that drive autonomous action. "Talent translators" are essential to bridge the gap between domain expertise and analytics. Imubit’s Closed Loop AI Optimization (AIO) addresses these needs with outcome-first design and explainable models to increase throughput and efficiency.

AI, AFR, and 1L – oh my!

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The IEEE-IAS/PCA Cement Conference 2025 highlighted the industry's path to net zero by 2050. Key challenges include AFR adoption hurdles, Portland Limestone Cement (1L) logistics, and organizational silos. While AI is already used for predictive maintenance, Imubit’s Closed Loop AI Optimization (AIO) goes further. By using real plant data, the Optimizing Brain platform uncovers complex process relationships to achieve peak economic and emissions performance.

Closed-Loop AI and Process Control: Why This Public Debate Matters

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Closed-loop AI is entering the mainstream, marking a pivotal shift in industrial process control. Rather than replacing DCS or APC, it acts as an adaptive layer that optimizes plant behavior dynamically. Supported by real-world results, the industry is now addressing challenges like scalability and trust. This transparent dialogue is an invitation for the community to collaborate and shape a more intelligent, adaptive future for plant operations.

Controllable AI: What It Really Means for the Future of Plant Modeling

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Imubit CEO Gil Cohen explains why the future of plant modeling lies in Controllable AI. Moving beyond "black boxes," this approach focuses on five pillars: building trust through transparency, grounding AI in engineering first principles, enabling practical plant-wide optimization, tailoring GenAI to plant context, and empowering experts to make faster, smarter decisions. Discover how to shift from AI possibility to real, site-specific solutions.

Imubit Transcend EU: Real Conversations with Refining Leaders

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At Imubit's Transcend EU events, refining leaders identified safety, survival, and economic optimization as top concerns. While AI is essential for longevity, adoption is often hindered by concerns over model trustworthiness and data control. Imubit CEO Gil Cohen outlines how Closed Loop AI Optimization (AIO) addresses these challenges through plant-specific, transparent models that empower technical staff. Request your AIO Readiness Assessment today.

Tuning Out the Noise in the Industrial AI Landscape

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The Industrial AI market is saturated with "advisory-only" tools that offer insights but stop short of action. Real-time optimization requires automated execution—a task too complex for human operators alone. Most vendors fail here due to a lack of domain expertise and a robust technology stack. Imubit’s Closed-Loop AI Optimization (AIO) integrates directly with plant controls to autonomously execute optimal strategies, ensuring true, plant-level impact.

3 Ways AI is Conquering Uncertainty in Chemicals

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Facing industry uncertainty, chemical plants must focus on operational excellence to maximize margins. This article shares three best practices for AI Optimization (AIO): 1) shifting from local to plant-wide optimization, 2) running existing assets to true constraints—reducing sub-optimal utilization by over 20%—and 3) empowering experts with no-code, explainable tools. Discover how AIO provides the agility needed to remain competitive in volatile markets.

Winning in the [Open] Industrial AI Era

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At the 2025 ARC Forum, Marathon Petroleum shared how Imubit’s AI Optimization (AIO) transformed naphtha system control, increasing yield while reducing carbon emissions. An expert panel defined five pillars for AI success: readying data and people, ensuring safety and trust, and choosing the right partner. By maintaining an operator’s "Golden Batch Day," AIO ensures that advanced technology remains online to drive maximum, sustainable industrial value.

A World Without Step Testing?!

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Traditional APC step testing is a costly, two-week process that creates friction between teams and produces limited data. Former APC Engineer Greg White explains how Imubit’s Closed Loop AI Optimization (AIO) eliminates disruptive step testing by leveraging historical data. By modeling thousands of process relationships, AIO aligns operations and engineering to drive continuous, constraint-respecting, and optimal plant performance.

Opportunities for Positive ROI from the Application of AI to Refinery Processes

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In Petroleum Technology Quarterly, Imubit’s Principal Hydroprocessing Engineer highlights high ROI applications for AI-based closed-loop optimization. Real-world results include a 0.5°F ULSD T90 improvement, 2% higher debutanizer throughput, and a 25% reduction in suboptimal coke drum cycles. Unlike traditional methods, Imubit’s AI allows hydrocrackers to automatically shift yields between naphtha and diesel based on market prices to maximize profitability.

Preem Partners with Imubit to Drive Sustainability and Lower Emissions Through Advanced Closed Loop AI Optimization

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Imubit, a leader in Closed Loop AI Optimization (AIO), has partnered with Preem, Sweden’s largest fuel company, to accelerate its journey toward net zero emissions by 2035. Imubit’s Optimizing Brain™ will be deployed at the Lysekil refinery to maximize Fluid Catalytic Cracking (FCC) unit efficiency. This collaboration aims to reduce emissions and fuel consumption by optimizing process variables, setting a new standard for sustainable industrial operations.

Imubit Opens New R&D Center in Romania to Accelerate AI Modeling Democratization within the Process Industries

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Imubit, the leader in Closed Loop AI Optimization (AIO), has opened a new R&D center in Cluj, Romania, to accelerate AI democratization. This expansion advances the Imubit Industrial AI Platform, giving customers autonomy to build and manage their own multipurpose AI models. By empowering teams to solve complex challenges in training, planning, and process insights, Imubit helps industrial sites boost margins, reduce emissions, and ensure future-proof operations.

You’re ready for AI, but is your data?

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AI Optimization (AIO) success in process industries starts with data readiness. Drawing on nearly 100 implementations, Imubit experts share six essential data requirements to keep projects on time and budget. Key pillars include 6+ months of data volume, 1-minute compression intervals, modernized extraction, rigorous quality cleansing, full instrumentation metrics (PV, SP, OP, MD), and base layer control readiness. Set your data foundation now to unlock AIO’s full value.

The Keys to Success: Transforming Plant Operations with Closed Loop AI Optimization (AIO)

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Industry leaders from Marathon Petroleum, Delek, and Oxbow shared five keys to successful Closed Loop AI Optimization (AIO) at the Transcend AI Tech Summit. Insights include matching AIO to complex problems, upskilling the workforce, and exploring multi-unit optimization. Powered by Imubit’s Foundation Process Model, AIO is an empowering tool that drives system-wide economic benefits and cross-team collaboration without replacing human expertise.

Imubit Named Leader in New Closed Loop AI Optimization Category by ARC Advisory Group

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ARC Advisory Group has named Imubit the leader in its new Closed Loop AI Optimization (AIO) category, establishing a new industrial AI standard. Powered by reinforcement learning, Imubit’s Optimizing Brain™ solution is proven in over 90 applications, boosting refinery margins by up to $0.50 per barrel and reducing natural gas consumption by 20%. This recognition highlights Imubit’s impact in democratizing AI and transforming complex industrial processes.

5 Ways AI is Attracting & Transforming the Engineering Workforce

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The petrochemical industry faces a critical skills gap with 40% of the workforce retiring soon. Imubit’s Closed Loop AI Optimization (AIO) addresses this crisis by automating routine tasks, accelerating onboarding, and democratizing technology. By unifying data in a low-code environment, AIO empowers engineers to focus on high-value innovation. Rather than replacing workers, AI enhances collaboration and helps attract the next generation of top technical talent.

The Evolution of Process Optimization and Control Technology: AI Drives a New Market Category with Imubit as Leader

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ARC Advisory Group has introduced Closed Loop AI Optimization (AIO) as a new market category, signaling a shift from 40-year-old legacy systems. Valued at $60M, the AIO market is growing rapidly due to engineer shortages and sustainability needs. ARC identifies Imubit as a leader, citing its Reinforcement Learning technology as a key differentiator for precision control. Imubit currently holds the second-largest market share in refining, driving 10% of the overall market.

Imubit Launches Optimizing Brain™ Solution: The Process Industry’s First Closed Loop AI Optimization Solution Powered by Reinforcement Learning

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Imubit defines the new Closed Loop AI Optimization (AIO) category with the launch of its Optimizing Brain™ Solution and Industrial AI Platform. Recognized by ARC Advisory Group, this technology leverages reinforcement learning and the Foundation Process Model™ to boost refinery margins by up to $0.50/barrel. Trusted by 7 of the top 10 US refiners across 90+ applications, Imubit is democratizing AI and driving operational excellence for the process industry.

Introducing the Imubit Foundation Process Model™: A New Paradigm in Plant Optimization

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Imubit's Foundation Process Model (FPM) is the "ChatGPT for the process world," transforming industrial operations through deep learning. By integrating massive plant data with engineering expertise, the FPM replaces fragmented models like APC and LP to break down silos. This evergreen asset empowers technical teams with site-specific training and faster updates, driving continuous optimization and unprecedented efficiency across the entire facility.

The Process Industries' First Reinforcement Learning-powered Closed Loop AI Optimization

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Imubit unveiled its Optimizing Brain and Foundation Process Model™ at the Transcend Houston Global AI Summit. ARC Advisory Group defined a new category, Closed Loop AI Optimization (AIO), highlighting Imubit’s reinforcement learning approach. Successes include Marathon Petroleum reducing coke drum giveaway by 25% and Big West Oil’s gamified operator training. The platform breaks down silos, unifying operations, planning, and engineering around a single view of plant reality.

Myth Busters: Reinforcement Learning

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Bust the myths clouding reinforcement learning (RL) in closed-loop optimization. We address three key misconceptions: first, RL models successfully integrate first principles with a data-first approach for flexible control; second, these robust models handle errors well without frequent, time-intensive retrains; and finally, a no-code platform empowers your in-house engineers, democratizing AI optimization and eliminating vendor-lock across your organization.

3 Reasons Your Refinery Needs<br> Closed Loop AI Optimization

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Big West Oil's high-conversion refinery faced challenges like an undersized debutanizer, static FCC operations, and conservative diesel flash point buffers. Implementing Imubit's Deep Learning Process Control (DLPC) brought major results: 2% debutanizer throughput increase, a 0.6% boost in liquid volume yield, and a 2-degree reduction in the diesel flash buffer to maximize throughput. Crucially, the success was underpinned by early operator buy-in and trust, achieving over 85% engagement.

Answering the Important Questions

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This FAQ post, following our webinar with Big West Oil, answers key questions on Closed-Loop AI Optimization. We explore the DLPC architecture, its success in FCC units, and how Reinforcement Learning outperforms traditional APC. Learn how Imubit combines Deep Learning with domain expertise via AutoML for sustained performance, and how our team proactively maintains models to adapt to new operating regimes and instrument limitations.

AI-first Optimization and Control

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The AFPM/Imubit white paper highlights the shift to Deep Learning Process Control (DLPC) to overcome the limits of traditional APC. Using advanced AI and reinforcement learning, DLPC masters complex process dynamics in high-risk environments. By integrating Explainability and AutoML, DLPC replaces "black box" models with transparency. This allows operators and engineers to build trust through "what-if" scenarios and collaborate for safe, closed-loop value delivery.

Discover True AI: 3 Key Questions to Distinguish AI Reality from Hype

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Cut through the AI hype with this guide for industrial leaders to evaluate plant optimization solutions based on three criteria: Is it Real (AI-first), Accessible (no-code), and Closed Loop (autonomous)? Learn how to move beyond advisory tools to capture maximum economic value through true AI that manages complex process variables for sustained, automated performance.

Monroe Energy Embraces New Technology for a Competitive Edge

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Monroe Energy’s success with Imubit’s Closed-Loop AI shows how new technology levels the playing field for single-site refineries. Key takeaways from the AFPM Annual Meeting highlight that AI models built on plant data bypass complex algebra, making optimization accessible to all domain experts. By reducing operator burden and providing clear performance evidence for executives, Imubit helps refiners stay competitive while attracting talent and ensuring continuous growth.

The ABCs of Closed Loop AI Optimization

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Closed Loop AI Optimization (AIO) outperforms legacy RTO by using deep learning and years of plant data instead of complex simulations. By leveraging reinforcement learning and millions of offline scenarios, the controller gains thousands of years of experience, enabling real-time decisions without a solver. This data-first approach builds team trust and can be operational in under six months, compared to the 18-24 months required for traditional methods.

One Reality, One Model, One Goal

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Imubit’s Optimizing Brain™ helps refiners accelerate decarbonization by integrating sustainability goals into closed-loop AI optimization. Moving beyond purely financial objectives, this technology has delivered a 15-30% reduction in natural gas usage and a 2% yield increase. By parsing thousands of operating scenarios, Imubit makes the non-intuitive decisions needed for a profitable, sustainable future. Join our upcoming webinars to learn more.

Imubit Tech Day – Revolutionizing AI Process Optimization

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At Imubit's Tech Day, industry leaders from Chevron, HF Sinclair, and CVR Energy shared how "true AI" is transforming process optimization. Using Imubit's Optimizing Brain, a cyber-secure model powered by Deep Reinforcement Learning, refiners achieved 15-30% less energy usage and 1-3% yield improvements. This approach unifies data across all plant disciplines to create a single model of reality, enabling sustainable change and next-gen AI process control.

An Optimizing Brain™ for Your Plant

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The energy industry’s complexity hinders digital transformation, sustainability, and talent acquisition. To achieve operational excellence, plants must move beyond AI hype to practical solutions. Imubit’s Optimizing Brain uses reinforcement learning and plant-specific data to maximize yields and reduce emissions. This Closed-Loop AI approach also simplifies change management by optimizing human collaboration, making operations safer and more efficient.

Renewable Diesel Optimization

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The refining industry is shifting toward sustainable operations, driven by incentives like the Inflation Reduction Act and the demand for low-carbon fuels like Renewable Diesel and SAF. This transition introduces complexities like variable feedstocks and non-linear trade-offs. Imubit’s Closed-Loop AI, using Deep Reinforcement Learning, provides minute-by-minute optimization to maximize profitability and minimize carbon intensity while ensuring safety and quality.

North America Refining Market Outlook 2022

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The North American refining market is entering a rare, prolonged up-cycle. A 5.5% drop in US capacity since 2019, rebounding fuel demand, and limited new investment due to ESG mandates have created a unique supply shortage. Combined with the impact of the Russia-Ukraine war, global supply is tightening further. This environment offers a significant opportunity for refiners to maximize output and capitalize on higher margins as prices rise to meet demand.

Economic Engineering Update | September 2021

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Global natural gas price spikes and rising EU carbon costs signal the end of cheap energy, making plant optimization more critical than ever. To remain competitive, hydrocarbon processors must navigate complex, non-linear trade-offs between energy usage, yield, and throughput. Imubit’s Closed-Loop AI platform manages this high-cost reality in real-time, factoring in dynamic market prices and fuel mixes to help facilities optimize energy intensity.

Imubit Announces $50 million in Total Funding to Expand its AI Process Optimization Platform

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Imubit raised $50M, featuring a $30M round led by Zeev Ventures and Insight Partners, to scale its AI-driven Closed-Loop Neural Network platform globally. Designed for refiners and chemical operators, the technology solves complex optimization challenges once considered impossible. With a major operator reporting a $10M annual margin boost, Imubit’s Deep Learning Process Control represents a step change beyond traditional industry software.

Economic Engineering Update | July 2021

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The IEA's forecast shows developed nations have passed "peak gasoline," shifting growth to petrochemicals and non-OECD diesel. This requires refiners to be more nimble to capture volatile arbitrage and manage geographical shifts. Imubit’s Closed Loop Neural Network™ provides the essential platform for this transition, empowering operators to respond to real-time market signals and execute optimizations that were previously infeasible to maximize profitability.

Transforming Safety Culture from a Program to an Organizational Principle

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In the downstream industry, safety must be a core organizational principle rather than just a checklist. Guided by the principle "build safety, operate safety," Imubit has transformed its culture through leadership engagement and employee accountability. This post explores the impact of our employee-led Safety Committee and the use of "Safety Moments" to integrate vital discussions—from proper lifting to cybersecurity—into daily operations for a safer workplace.

Economic Engineering Update | June 2021

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High crack spreads are deceptive. Record-high Renewable Volume Obligations (RVOs), driven by soaring RIN prices, are eroding US refiners' profits. The RVO Adjusted Crack Spread reveals that compliance costs make generic optimization obsolete. Imubit's Closed Loop Neural Network™ provides real-time, granular control to balance complex plant trade-offs against a live economic objective, maximizing profitability despite market and regulatory volatility.

Economic Engineering Update | April 2021

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The EIA forecasts an uneven recovery for US fuel demand, with gasoline and jet fuel likely lagging 2019 levels beyond 2022. While business travel remains a concern, distillate demand serves as a growth-oriented bright spot. In this volatile market, Imubit’s Closed-Loop AI Optimization (AIO) provides the agility and precision refineries need to navigate shifting product demands and maximize profitability through advanced process control.

Economic Engineering Update | March 2021

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Refining margins have a rosy outlook for summer 2021 due to increasing vaccinations and the impact of the Texas deep freeze. With travel demand rising and gasoline stocks drafting heavily after the freeze-induced supply drop, refining and petrochemicals are positioned for higher prices. Operators using agile, high-profitability strategies are best equipped to capture the coming recovery in spreads.

Economic Engineering Update | January 2021

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Resilient product demand is driving improved conversion unit margins, specifically for the Fluid Catalytic Cracker (FCC). Maximizing these gains requires continuous optimization across monthly planning, weekly tactics, and daily process adjustments. Due to the interactive complexity of FCC yields, achieving peak profitability depends on seamless, real-time coordination between planning, engineering, and operations.

Economic Engineering Update | December 2020

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The December 2020 Economic Update explores the shifting distillate-gasoline spread. Despite recent inventory draws, a mild winter forecast and low air travel suggest weak underlying demand. In this volatile post-pandemic market, refiners must be exceptionally agile to capture fleeting margins. Imubit’s Closed-Loop AI Optimization (AIO) provides the real-time, precise response needed to navigate these shifts and maximize profitability.