United States, South Charleston - August 28, 2026 - Atlas Prediction Control has introduced a suite of process control solutions built around three distinct engagement models, each designed to address control loop degradation, constraint management, and performance improvement across industrial chemical plants.

The suite - structured around Atlas Advisor™, Remote Resident™, and Project-Based Engagements - gives plant operators defined access to Advanced Process Control (APC), PID tuning and control loop performance monitoring (CLPM), and model predictive control capabilities. The structure allows facilities to access these services without maintaining a full-time in-house control engineering team.

Three Engagement Models Targeting Different Operational Needs

Atlas Prediction Control developed the three engagement models around the recognition that facilities differ in their control challenges, staffing capacity, and capital availability.

The Atlas Advisor™ model delivers continuous advisory and diagnostic oversight, providing plant engineers with ongoing monitoring, loop performance assessments through CLPM, and root-cause diagnostics on a subscription basis. The model is designed for facilities seeking persistent visibility into control system health without committing to a fixed project scope.

The Remote Resident™ model takes a more direct operational role, functioning in a fractional control engineer capacity. Under this arrangement, a dedicated control engineer from Atlas Prediction Control serves as an embedded resource for the client facility - working remotely while maintaining consistent oversight of DCS integration, controller performance, and constraint management. The model is structured to replicate the functional presence of an on-site resident engineer while reducing the overhead associated with full-time staffing.

Project-Based Engagements address targeted implementation needs with defined deliverables and fixed scope. These engagements are built around discrete objectives - deploying an Advanced Process Control strategy for a specific unit, conducting a PID tuning and CLPM campaign across a problematic plant section, or completing a root-cause diagnostic study for chronic loop instability. The fixed-scope format makes these engagements compatible with facilities operating under capital project frameworks.

Atlas Advisor™: AI-Native Diagnostics Built on Small Language Models

Central to the new suite is Atlas Advisor™, an AI-powered engineering advisor designed to address a recurring operational challenge: engineers spending significant time moving between APC diagnostics, historian data, and separate engineering tools to determine what is changing in a process and why. That process is time-consuming, experience-dependent, and produces inconsistent results depending on who is on shift.

Atlas Advisor™ is built as an AI-native application using small language models purpose-built for process control data and engineered for plant-floor deployment. The system continuously monitors plant stability and deviations, correlates APC, CLPM, and historian signals to isolate issues, and delivers engineering guidance based on current plant conditions. It integrates directly with DCS, APC, and CLPM systems alongside a facility's existing engineering tools, and supports drift detection, root-cause identification, corrective-action recommendations, multilingual use, and on-premises deployment with no internet access for facilities that require isolated on-prem PCN environments.

The outcome is faster diagnosis and a consistent standard of interpretation, independent of which engineer is on shift or their level of experience. Additional detail on Atlas Advisor™ is available at atlasprx.com/advisor.

How Engagements Begin: A Structured Diagnostic Path

Facilities that have not yet defined a specific project scope typically enter through one of two diagnostic offerings before selecting an engagement model. A Plant Performance Scan is a single-day, on-site assessment that scores a facility across six operational dimensions, giving plant leadership a structured read on where control performance currently stands.

For facilities seeking a more detailed picture, a Plant Audit provides greater depth. The audit begins with a pre-visit data request so Atlas Prediction Control engineers arrive with process context already established, followed by a full day on-site that includes control room observation, an equipment walk-through, and structured interviews across the facility's process areas. Findings are scored after the visit and presented to the client in a focused session that leads with operational implications and closes with a prioritized list of next steps.

That diagnostic path informs which engagement model fits a given facility - whether that is ongoing Atlas Advisor™ support, an embedded Remote Resident™ engineer, or a scoped Project-Based engagement addressing a specific problem.

Capabilities Spanning APC, PID Tuning, CLPM, and DCS Integration

Across all three engagement models, Atlas Prediction Control delivers a consistent set of technical capabilities. PID tuning services address controller detuning, oscillatory behavior, and loop interaction - problems that compound over time and directly erode product quality, energy efficiency, and throughput stability. Control Loop Performance Monitoring (CLPM) continuously tracks loop health across the facility and flags degradation before it compounds into larger operational issues.

The Advanced Process Control offerings extend beyond basic regulatory control, incorporating dynamic constraint management and multivariable coordination. Model predictive control applications are deployed where process interactions, time delays, or hard operating constraints require coordinated controller action across multiple inputs and outputs simultaneously. DCS integration support ensures that deployed control strategies align with the specific historian, control platform, and operator interface environment at each facility.

These capabilities are supported by machine learning and AI-based tools, including the small-language-model-driven diagnostics built into Atlas Advisor™. These tools are designed to interpret plant data alongside engineering context, supporting the judgment of the control engineer on shift.

Root-cause diagnostics form a foundational element of the suite. Before implementing new control strategies, Atlas Prediction Control engineers identify the underlying sources of variability - whether mechanical, procedural, or control-design related - so that corrective measures target the actual failure mechanism driving the variability.

Addressing a Persistent Challenge in Chemical Plant Operations

Control loop degradation is a documented and ongoing problem in continuous process industries. Studies of operating chemical plants have consistently found that a substantial fraction of control loops perform below design intent at any given time, contributing to unnecessary process variability and off-specification production.

"Our goal with these engagement models is to give plant teams a practical path to eliminating that variability - one that fits their actual operational structure," said Madhur Bedre, Founder and President of Atlas Prediction Control. "Whether a facility needs ongoing advisory support, a dedicated remote presence, or a focused project to solve a specific control problem, the technical work centers on the same objective: getting controllers to perform the way the process requires, and keeping them there."

About Atlas Prediction Control

Atlas Prediction Control provides process control engineering services to industrial facilities, with a focus on Advanced Process Control, PID tuning, model predictive control, CLPM, root-cause diagnostics, and AI-native engineering tools including small language models. The company delivers its work through three structured engagement models - Atlas Advisor, Remote Resident, and Project-Based Engagements - and supports clients across DCS integration and dynamic constraint management. Atlas Prediction Control is headquartered at 1740 Union Carbide Dr, South Charleston, WV 25303.

Learn more at Atlas Prediction Control

Contact Information:

Atlas Prediction Control

1740 Union Carbide Dr, South Charleston, WV 25303
South Charleston, WV 25303
United States

Madhur Bedre
+1-304-205-9527
https://atlasprx.com