We Combine Consulting, Technology, and Deep Operational Expertise to Deliver End-to-End Digital Transformation.
What we do
Our strength lies in the fusion of deep consulting experience, process domain expertise, and digital execution excellence. This rare combination enables us to go beyond traditional digital transformation — we build AI agents that not only analyze but act.
As a Digital Transformation Execution Partner (Dx-Ex Partner), we help process industries convert complex data and siloed digital initiatives into autonomous, real-time decision-making systems.
Dx. Consulting Services
Domain-Driven, Use Case-Centric, and Ready for Production
Our Dx Consulting Services are built to accelerate digital transformation for industrial enterprises—bridging the gap between operational challenges and scalable AI solutions.With deep roots in engineering sciences and industrial systems, we help clients chart transformation journeys that are both technically sound and business-aligned.
Digital Transformation Consulting – Process Manufacturing
Tridiagonal Solutions is a trusted partner for successful manufacturing excellence, digital transformation strategy and implementation of digital / Industry 4.0 tech stacks in process manufacturing. Our process domain understanding, technology expertise and hands-on implementation experience enables us to take deeper view to devise sustainable Dx strategy and roadmap.
Core Expertise
- Production / Process Optimization
- Energy Optimization
- Quality Prediction
- Predictive Maintenance
- Safety & Sustainability
Dx Tech Stacks
- IT-OT assessment
- Advanced process control / AI-based Process control
- Predictive Analytics
- Energy Management (Scope 1 & 2)
- Digital workforce
Dx Consulting
Reframing IT-OT Infrastructure
- Understanding the scope: Current V/S Expected performance
- Assessing I4.0 readiness
- Current data architecture: Sensors, DCS/SCADA, etc.
- Additional sensor implementation for I4.0 use cases
- OPC compliance and communication protocols
- IT-OT Data requirement tech stack
- Designing ISA 95 compliant architecture
Domains: MES, Historians, Industry Data Ops, IT-OT integration, Cloud, UNS, ISA 95, Asset hierarchy
Gap Analysis
Benchmarking key performance metrics and defining Vision, Mission, Goals, and Digital Culture.
- Identifying pain areas in process manufacturing
- Blueprinting Dx – Problem statement definition
- Creating business cases for operational benefits
Operations Areas: Planning & Scheduling, Quality, Yield, Zero Defects, Energy Optimization, OEE
Benefit Analysis and ROI
- Financial savings report and projected asset/process savings
- Business cases for each tech stack implementation
- Budget assessment for implementation
- CAPEX/OPEX savings estimate
- 5-year Dx investment planning (IRR, NPV, Payback period)
Dx Implementation Roadmap
- Developing priority matrix using maturity assessment
- Prioritizing problems by savings and needs
- Tech stack identification
- Risk mitigation & change management
- Training needs and cultural roadmap
Project Management Consulting (PMC)
- Scalability framework development
- Roll-out planning across sites
- Continuous improvement & KPI analysis
- Post-implementation ROI analysis
- Gap identification and rectification
- Training needs and new use case definition
PMC: Ensuring successful Dx implementation and long-term ROI.
Dx Consulting
Gap assessment, Benchmarking, Dx Roadmap, Identification of Use Cases, Benefit Analysis/ROI, PMC, etc.
Dx Consulting Topics
- Reframing IT-OT Infrastructure
- Gap Analysis
- Benefit Analysis and ROI
- Dx Implementation Roadmap
- Project Management Consulting (PMC)
IT-OT Integration
Implementation of Historians, MES, Industry Data Ops, Data Engineering, Data Lake setup on cloud, Cloud infrastructure management, etc.
View More | CloseIT-OT Integration – Industrial Data Fabric for Smart Manufacturing
Cyber-physical systems integration is foundational for digital transformation. Using IIOT, protocols, edge systems, and cloud integration, Tridiagonal architects tailored IT-OT convergence strategies.
Core Expertise: ISA 95 architecture, Edge deployments, Data Ops, Knowledge graphs, Data fabric consulting, Visualization, UNS, etc.
Dx Tech Stacks: MES, MOM, IIOT, Historians, Cloud integration
IT-OT Integration as per ISA 95 Standards
- Data integration across MES, ERP, IIOT, Data Lakes, Analytics
- Hierarchical model to align data across levels (cell to enterprise)
- Information model defines inter-relationships
- Functional model defines data flows
Domains: ISA 95, Asset hierarchy, MES/MOM, Industry Data Ops, UNS
Process Data Contextualization
- Use graph databases to define relationships
- Embed domain knowledge into raw data
- Use context models to structure and optimize data
- Identify bottlenecks and improvement opportunities
Key Areas: Knowledge graphs, data enrichment, domain contextualization
Partner Solutions: Cognite
Industrial Data Ops Solution
- Financial savings per asset/process
- Business cases for tech stack implementations
- CAPEX/OPEX savings estimate
- 5-year ROI/NPV/IRR planning
Examples: ROI, payback period, investment planning
Unified Name Space (UNS)
- Prioritize use cases by maturity and readiness
- Identify tech stacks and create phased roadmap
- Plan implementation and risk mitigation
- Address training and cultural transformation
Examples: Prioritization matrix, training roadmap, cultural change
Data Fabric Implementation
- Scalability framework and rollout strategy
- Continuous improvement via KPI evaluation
- Post-implementation ROI tracking
- Gap analysis, training plans, new modeling
PMC: Ensures successful Dx implementation and long-term ROI
Process Optimization
With the increasing and dynamic market demands it is important to identify the opportunities for continuous improvement of the operations through real time optimization of the equipment and processes. With our deep domain expertise and process optimization know-how leverage the frameworks for improving the overall optimization strategies by making the appropriate control move to enhance the maintenance, planning and scheduling practices.
Core Expertise:
Process optimization, Advanced process control (APC), Enhanced life of assets, Real time optimization (RTO), Energy optimization
Dx Tech Stacks:
Imubit, Honeywell APC, Aveva, Siemens GPROMS
Advanced Process Control (APC)
- Advanced process control for complex and dynamic chemical operations for autonomous operations
- Integrated PID controllers for multivariate control strategy to dynamically respond to the process changes
- Minimize process off-spec, enhanced quality control and reduced process variabilities
Techstacks: Honeywell Forge, Aveva APC, Aspen DMC
Deep Learning Process Control (Minute-by-Minute Optimization)
- Offers real time process control through complex analysis of MVs, CVs and DVs
- Integrated non-linear inferentials for real time quality control and constrained objectives / targets
- Accounts for the impact of uncontrollable disturbances
- Identifies the opportunity to optimize the processes every minute within the non-linear constrained environment
Techstacks: Reinforcement learning, Non-linear inferentials for quality prediction
Plant-Wide Real Time Optimization
- Physics-informed RTOs for enhancing overall site performance to meet cost / objective functions
- Objective-oriented models intended to optimize economic profits
- Continuous production optimization to improve asset reliability, throughput, and energy efficiency
Techstacks: Honeywell RTO, Aveva RTO
Use Cases
- Optimize the performance of various processes such as distillation columns, reactors, and compressors
- Reduce energy cost for facilities including utility management
- Optimization of the air-to-fuel ratio in furnaces to improve combustion efficiency, reduce fuel consumption, and minimize emissions
- APC for compressor optimization
- RTO for gas plant optimization
- Stabilization of distillation columns through APC
Advanced Data Analytics
Tridiagonal Solutions bespoke solutions tailored to support the industry requirements leveraging the advanced capabilities such as digital twin, custom applications and connected analytics. Enhancing the analytics and visualization for the plant engineers and operators with improved decision making. These solutions are backed by our industry experts which helps the organizations to enable agile development at scale and better adoption through these utilities. Enhancing the current data science practise with 3D models with enhanced contextualization to enabling causalities through connected analytics using sequential modeling approach empowers the shop floor team to gain better insights from their data.
Core Expertise:
Time series analytics, predictive analytics, digital twin, metadata modeling, connected analytics, smart Apps for Energy and process optimization
Dx Tech Stacks:
AWS IOT Twinmaker, Azure Digital Twin, Cognite, VidyaTec, Seeq, Smart Applications
Digital Twin
- Advanced 3D models-based visualization for the telemetry data modeling
- Integrated data management – Timeseries, SAP, MES, ERP, AIMS, and others engineering information
- Analyze the complete history of the processes and equipment
- Knowledge graphs for better information management through metadata modeling
Techstacks: Knowledge graphs, Master data management, Cognite, AWS, Azure, VidyaTec
Connected Analytics
- Mimic the plant conditions by connecting all the upstream and downstream equipment
- Improve the decision making through equipment level correlations and causalities
- Enhance the process and equipment reliabilities through sequential models
Techstacks: Supervised ML techniques, Boosting and bagging methodologies, Seeq, Cognite, AWS, Azure
Smart Apps
- Open source based tailored frameworks focused to provide the custom insights for point problems
- Applications focused to accelerate the scalability and adoption
- Built to deliver high value through physics based modeling for real time constraint modeling and optimization
Techstacks: Python, scipy, Tensorflow, PyTorch, Supervised and unsupervised learning, First principles based mechanistic modeling
Deep Learning
- Solutions leveraging neural networks for image processing and video analytics solving complex industrial problems
- Leveraging artificial neural networks for fault detection through complex learning patterns
- Digitization of offline scanned manufacturing records through OCR
- Analyzing complex microstructures and visual quality inspection
Techstacks: Tensorflow, PyTorch - CNNs, RNNs, GANs, Generative models, Transformers - GPT-4 and others
Use Cases
- Improving the decision making through connected analytics for CDU operations
- Digital twin for complex refinery and petrochemical units
- Plant wide optimization
- Smart Apps for process/energy/utilities optimization for manufacturing companies:
- Compressors
- Exchangers
- Steam optimization
- Energy management
- Steam and condensate balance
- Image analytics for safety measures
- Complex material microstructure pattern prediction
- Prediction of external cracks for metal casts
Process Modeling and Simulation
Tridiagonal Solutions Chemical 4.0 practice leverages several technology stacks for developing the process simulators intended to enable better decision making for critical operations including startup/shutdown procedures, maintenance workflow strategies and planning and scheduling optimization. With dynamic simulators, improve the real-time process performance by understanding the dynamics through efficient and integrated visibility. Integrate the physics-based dynamic plant models mimicking the DCS controllers for effective control of critical conditions.
Core Expertise:
Time series analytics, predictive maintenance, soft-sensors, energy optimization, emission management, APM
Dx Tech Stacks:
AWS, Azure, Cognite, Seeq, Kelvin, Python, PySpark, R and others
Process Debottlenecking (Steady-state Simulation)
- P&ID mapping and process flow simulators
- Process troubleshooting and debottlenecking
- Process stabilization
- Design modification and process improvement studies
- Heat integration and pinch analysis
- Thermodynamics and process reconciliation
Techstacks: Aspen HYSYS, Honeywell UniSim, Siemens gPROMS
Dynamic Simulation (Operator Training Simulation)
- Real-time plant simulators
- Process benchmarking
- Process operators training – plant control operations
- Process improvement and benchmarking studies
Techstacks: Honeywell OTS, Yokogawa OTS, Emerson OTS, Aveva OTS
Process Optimization Simulator
- Physics-informed simulators based on deep learning networks
- Enhancing overall performance of the site to meet the cost/objective functions
- Objective-oriented models intended to optimize the economic profits
- Continuous production optimization to improve asset reliability, throughput, and energy efficiency
Techstacks: Imubit, Smart Optimizers
Virtual Reality (VR)
- 3D training and simulations using VR
- Enriched remote operations experience
- Immersive assistance in remote maintenance workflows
- Enhanced plant safety
- Enhanced productivity through efficiency and smart operations
Agentic AI Services
Domain-Driven, Use Case- Centric, and Ready for Production
Knowledge Graph as a Service (KGaaS) is a scalable, agent-driven platform that transforms siloed, unstructured, and structured industrial data into a semantically connected, intelligent knowledge network. Built on industry standards and ontologies, the platform enables next-gen applications in root cause analysis, process optimization, SOP automation, and decision augmentation.
Knowledge Graph as a Service (KGaaS)
Powered by Agentic AI and Industry Standards | Offered by Tridiagonal.ai
Tridiagonal.ai: Industrial Intelligence Through Knowledge Graphs
Tridiagonal.ai’s Knowledge Graph as a Service (KGaaS) is a scalable, agent-driven platform that transforms siloed, unstructured, and structured industrial data into a semantically connected, intelligent knowledge network. Built on industry standards and ontologies, the platform enables next-gen applications in root cause analysis, process optimization, SOP automation, and decision augmentation.
- • Agentic AI Framework: Orchestrated agents autonomously ingest, contextualize, and reason over multi-modal data.
- • Standards-Driven Ontology: Built on ISA-95, ISO 15926, and custom domain models for chemicals, oil & gas, and discrete manufacturing.
- • Hybrid Graph Infrastructure: Supports Neo4j, Stardog, GraphDB, and Amazon Neptune for flexible, enterprise-grade deployment.
- • Industrial-AI Native: Integrates seamlessly with OSI PI, SAP PM, P&IDs, SOPs, and failure reports.
With support for hybrid deployments, standard-compliant APIs, and deep domain integration, Tridiagonal.ai ensures your transition to intelligent industrial knowledge networks is efficient, secure, and future-ready.
Overview
Our KGaaS architecture provides a full-stack framework to extract, organize, and utilize industrial data for advanced decision-making.
- 1. Ontology Creation
Domain-specific ontologies for process, asset, and reliability engineering. Includes equipment hierarchies, process flows, SOPs, work orders, RCA data, and compliance mapping. - 2. Data Ingestion Layer
Connectors for SAP PM, OSI PI, engineering documents. Uses Apache NiFi, Azure Data Factory, and NLP/DocAI agents to extract triples from unstructured data. - 3. Knowledge Graph Construction
Supports Neo4j, Stardog, GraphDB, Amazon Neptune. Uses agents for relationship resolution, deduplication, and enrichment. - 4. Querying & Reasoning Layer
Access data via SPARQL, Cypher, GraphQL. Built-in inference and validation with OWL/SHACL. Agents handle compliance checks, tag tracing, and root cause paths. - 5. Application Layer
Natural Language QA, SOP retrieval assistants, RCA tracing, and integration into dashboards (PowerBI, Grafana, custom alerting).
Use Cases Across the Asset Lifecycle
- Maintenance: Fault Tree Automation, SOP Mapping → Faster troubleshooting, SOP reuse
- Process Engineering: Root Cause Graphs, Process Deviations → Reduced downtime, better parameter tuning
- HSE & Compliance: Regulation Mapping, RCA Audit Trails → Compliance traceability
- Digital Twin: Tag and Flow Model Integration → Context-rich asset twins
- Knowledge Management: Centralized Document Intelligence → Easy access to tacit plant knowledge
Deployment & Integration Options
On-prem, hybrid, and cloud-native deployment models supported. Interfaces via REST, GraphQL, OPC UA, MQTT, OSIsoft PI, SAP OData. Built with enterprise-grade privacy, security, and version control.
Agent-as-a-Service (AaaS)
Operational Intelligence Delivered Through AI-Powered Multi-Agent Systems | Offered by Tridiagonal.ai
Tridiagonal.ai: Simulating Expert Engineers with Agentic AI
Agent-as-a-Service (AaaS) from Tridiagonal.ai transforms how industrial and process-intensive organizations approach decision-making, diagnostics, and operational planning. It combines multi-agent systems, domain-specific prompts, and cognitive frameworks to simulate the actions of expert engineers. Our agents interact with diverse data—time series, SAP, SOPs, P&IDs, simulation models—and convert them into prescriptive recommendations, anomaly detections, or planning outputs with zero hallucinations.
Agentic Frameworks for Industrial Use Cases
- Prescriptive Maintenance
- Process Investigations
- Turnaround and Shutdown Planning
- Preheat Section Energy Optimization
- Quality Deviation Investigations
- Operator Training & Scenario Analysis
- AI Lifecycle Management
- Energy & Emissions Management
Mind Mapping Agents
A unique capability of AaaS is the use of mind mapping agents that abstract the cognitive steps followed by human experts:
- Capture cause-and-effect logic
- Build structured maps for RCA, process flow, and quality investigations
- Enable transparent, explainable decision trails for audits and compliance
Examples include:
- Maintenance RCA Agent
- Process Flow Mapping Agent
- Energy & Emissions Investigation Agent
MCP Server & Agent Orchestration
- Tool orchestration and API connectivity
- Coordination of agent tasks and handoffs
- Zero-hallucination enforcement through grounding in knowledge graphs
This orchestration ensures agents collaborate—just like a team of plant engineers—to analyze data, simulate outcomes, and recommend optimal actions.
Knowledge Graph Powered Reasoning
- Maps plant assets, systems, documents, and simulations
- Enables contextual reasoning
- Avoids fragmented answers by grounding LLMs in enterprise knowledge
We support both Neo4j and Amazon Neptune for scalable, enterprise-grade knowledge graphs.
Knowledge Accelerators
Our agents are further empowered by Knowledge Accelerators, which act as data-aware copilots for:
- SAP Agent: Interprets work orders, notifications, and equipment hierarchies
- SOPs & Manuals Agents: Extract operational logic and best practices
- Time Series Agents: Perform anomaly detection, trend analysis, and pattern discovery
- Simulation & P&ID Agents: Ground investigations in process models and schematics
Cognitive AI with First Principles Integration
- Goal-based, utility-based, and reflex-based reasoning agents
- Thoughtful prompts (zero-shot, few-shot, chain-of-thought, binary) for structured reasoning
- Seamless fusion of learned knowledge and scientific models (e.g., surge detection, isentropic efficiency, fouling calculations)
Why Agent-as-a-Service?
- Emulates expert engineer decision-making
- Speeds up diagnostics, planning, and corrective actions
- Scales across departments with specialized agents
- Modular and composable for rapid deployment
- Enables full traceability and continuous improvement
Tridiagonal.ai ensures that AaaS becomes the digital brain of your operations—smart, explainable, and always learning.
Foundation Model as a Service (FMaaS)
Empowering Enterprises with Domain-Specialized, Fine-Tuned LLMs
Tridiagonal.ai: Your Partner in Foundation Model Development
At Tridiagonal.ai, we bring deep domain expertise in manufacturing, process industries, and industrial AI to ensure your foundation models are not just powerful, but practical and aligned with real-world operations. We help customers by:
- Identifying high-impact use cases through workshops with engineering, operations, and IT teams.
- Creating labeled, contextual training datasets using decades of plant, SAP, and SOP data.
- Fine-tuning LLMs using best-fit architectures and PEFT techniques for your infrastructure.
- Building agentic frameworks that emulate SME decision-making and drive frontline productivity.
- Ensuring value delivery with post-deployment support, model monitoring, and continuous feedback loops.
With our strong partner ecosystem and proven success in complex industrial environments, Tridiagonal.ai ensures your transition to foundation model-powered intelligence is smooth, scalable, and impactful.
Overview
Our Foundation Model as a Service (FMaaS) offering enables enterprises to harness the full power of Large Language Models (LLMs) by fine-tuning them on industry-specific data and workflows. Unlike generic AI solutions, FMaaS delivers domain-optimized intelligence that understands your data, systems, and operations—resulting in highly contextual and actionable outputs.
Core Capabilities
1. Domain Accelerators
- Data Ingestion & Parsing: Extract and preprocess structured and unstructured data from SAP, SOPs, operating manuals, time series, and other sources using OCR and custom parsers.
- Domain Contextualization: Incorporate process-specific semantics, terminologies, and hierarchies into the model training pipeline.
- Templated Tokenization & Configuration: Prepare efficient training datasets using pre-built tokenization templates and configuration standards.
- Training Pipeline (PEFT): Utilize Parameter-Efficient Fine-Tuning techniques like LoRA and QLoRA to reduce cost and optimize model performance with minimal GPU load.
2. Model Fine-Tuning
We support fine-tuning on top open-source foundation models such as:
- LLaMA 3 (Meta): Multi-purpose LLMs with large context windows.
- Mistral 7B / Mixtral: High-performance models optimized for latency-sensitive workloads.
- Falcon 40B: Suitable for document summarization and generative tasks.
Our infrastructure supports models trained on 2× A100 or 1× H100 GPUs, with flexible deployment on-prem or in the cloud.
3. LLM Deployment & Evaluation
- Evaluated on domain-specific benchmarks.
- Deployed via secure APIs for integration with enterprise systems.
- Connected to vector databases for semantic search and retrieval.
- Continuously improved through user feedback and system learning loops.
4. Model Inferencing & Application Delivery
- RAG/KAG Pipelines: Combine retrieval-augmented generation with knowledge graphs to deliver grounded, reliable responses.
- Knowledge Graph Delivery: Use ontologies to interlink enterprise knowledge for real-time decision support.
- Agentic AI Frameworks: Deploy task-specific agents that simulate expert decision-making using the foundation model backbone.
- Final Applications: Build custom workflows such as smart document assistants, process troubleshooting bots, or predictive advisory agents.
Recommended Infrastructure
- GPU: ≥ 1× A100 / H100 / RTX 4090
- CPU: ≥ 16 cores
- RAM: ≥ 128 GB
- Storage: ≥ 1TB NVMe SSD
- OS: Ubuntu 20.04 or 22.04
LLM Ecosystem & Capabilities
We collaborate with leading AI and infrastructure providers, including:
- NVIDIA
- DELL
- HuggingFace
- Mistral AI
- Meta
- Claude
- DeepSeek
- Neo4j
- AI21 Labs
—ensuring compatibility, performance, and innovation.
Why FMaaS?
- Built for enterprises with complex workflows
- Delivers contextualized AI for real-world decision-making
- Reduces deployment cost with efficient fine-tuning (PEFT)
- Enables ongoing learning and adaptation through user feedback
Tridiagonal.ai — Pioneers of AgentOps in Process Industry
World’s First Agentic AI Platform for Industrial Reasoning, Decision-Making & Execution
What is AgentOps?
AgentOps by Tridiagonal.ai is the first-of-its-kind industrial solution enabling human-like cognitive agents to autonomously analyze plant data, perform reasoning, and trigger actions. Think of it as your Digital Engineering Workforce — powered by AI agents that mimic domain experts in process engineering, maintenance, operations, and troubleshooting.
These multi-agent systems go far beyond traditional ML by combining:
- Data + Knowledge + Context + Goals
- Industrial physics + domain heuristics + generative knowledge
AgentOps isn't just AI — it’s AI that acts, thinks, and collaborates.
Agentic AI System: How It Works
Tridiagonal.ai’s AgentOps system is built on a multi-layered orchestration of AI agents:
- 🔹 Orchestrator Agent
Coordinates tasks between sub-agents based on goals, prompts, and event triggers. - 🔹 Specialized Agents
Each expert agent handles a specific cognitive task — from SOP retrieval to RCA to scenario simulation:- Fault Analysis Agent
- Process Optimization Agent
- SOP Compliance Agent
- Simulation/Prediction Agent
- Knowledge Query Agent
- 🔹 KAG (Knowledge Augmented Generation) Core
Multimodal LLM infused with:- Generative prompts (tree of thoughts, CoT, binary paths)
- Domain constraints
- 1st principle logic
- ML + physics-based reasoning
Integration with Industrial Intelligence
AgentOps connects with your plant data ecosystem — enabling context-rich decision-making:
| Data Source | Integrated Examples |
|---|---|
| Time Series | OSI PI, SCADA, DCS |
| SAP | Maintenance orders, asset hierarchy, notifications |
| P&IDs | PDF/DWG parsing, tag mapping, equipment zoning |
| Manuals & SOPs | SOP step extraction, compliance modeling |
| 3rd Party Models | Simulation outputs, digital twin, advanced analytics |
Real-World Applications
- CDU Preheat Section Optimization
- Compressor Predictive Maintenance
- What-If Process Scenario Analysis
- Energy Management
- Maintenance Workflow Automation
- Quality Deviation Root Cause Analysis (RCA)
These applications are agent-triggered, context-aware, and continuously learning.
Knowledge Accelerators Embedded
- AI/ML lifecycle agents
- Vibration & oil analysis interpreters
- Fouling, surge, or trip condition detectors
- SOP violation detectors
- What-if simulators and prescriptive planners
Industrial Tools Compatibility
- AspenTech, Honeywell, Siemens
- SAP PM/ECC/S4
- OSI PI, Ignition
- Azure/AWS Data Lakes
- Neo4j, Stardog, Amazon Neptune
Why Tridiagonal?
Who we worked with
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