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Architecture review before implementation
Implementation scope and rollout planning
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Uncover hidden bottlenecks and optimize production by applying AI to your factory's event logs.
Your existing factory systems—MES, SCADA, ERP—generate a continuous stream of event logs. This data holds the precise blueprint of your actual production flow, not the ideal one on paper. Our AI-powered process mining service transforms this dark data into actionable intelligence.
We automatically discover, visualize, and quantify your true production processes, identifying deviations and inefficiencies that cost you throughput and profit.
Apache Spark-powered analytics.This isn't just dashboarding. It's a systematic engineering approach to elevate your Overall Equipment Effectiveness (OEE). Learn how our work in Industrial AI Copilot Integration and Predictive Machine Maintenance creates a closed-loop intelligent factory.
Our AI-driven process mining transforms raw factory event logs into actionable intelligence, delivering quantifiable improvements to your bottom line. We focus on outcomes you can measure.
Automatically discover and quantify hidden production delays, enabling targeted interventions that increase throughput. Our models analyze event logs to pinpoint the exact machines, shifts, or process steps causing the most significant drag on your Overall Equipment Effectiveness (OEE).
Continuously monitor actual workflows against ideal SOPs and regulatory standards. Our system flags deviations in real-time, ensuring quality control and audit readiness, which is critical for industries like automotive and pharmaceuticals. Learn more about our approach to AI Governance and Compliance.
Move from reactive firefighting to proactive management. Our AI identifies subtle, early-warning patterns in process flows that precede quality defects or equipment failures, allowing for preemptive correction. This complements our Predictive Machine Maintenance services.
Reveal inefficiencies in material usage, energy consumption, and labor allocation. Our analysis provides data-driven recommendations for re-sequencing tasks and reallocating resources, directly reducing operational expenses and supporting Sustainable Manufacturing goals.
Decompress your production timeline by identifying and eliminating non-value-added steps and wait times. Our process mining visualizes the critical path and simulates the impact of changes, accelerating time-to-market for your products.
Accelerate problem-solving by automatically tracing quality incidents or delays back through complex, interconnected process steps. Instead of manual investigation, get AI-generated causal maps that highlight the most probable sources of failure. This intelligence feeds directly into Industrial Reasoning Engines.
A structured, phased approach to deploying AI-powered process mining in your manufacturing environment, ensuring clear deliverables and measurable outcomes at each stage.
| Phase & Deliverables | Starter (4-6 Weeks) | Professional (8-12 Weeks) | Enterprise (12-16 Weeks) |
|---|---|---|---|
Initial Process Discovery & Data Audit | |||
Multi-System Event Log Integration (MES, ERP, SCADA) | 1-2 Core Systems | 3-5 Core Systems | Full Plant Integration |
AI Model for Bottleneck & Deviation Detection | Basic Anomaly Detection | Advanced Causal Analysis | Predictive Bottleneck Forecasting |
Interactive Process Visualization Dashboard | Static Reports | Real-time Dashboard | Customizable Multi-plant View |
Root Cause Analysis & Optimization Recommendations | Manual Report | Automated Insights | Agentic AI Recommendations |
Integration with Industrial AI Copilot | Basic Alerts | Full Two-way Integration | |
Ongoing Monitoring & Model Retraining | Quarterly | Monthly | Continuous (Automated) |
Support & SLA | Business Hours | 24/7 Priority | Dedicated Engineer + 99.9% Uptime |
Typical Investment | $40K - $60K | $80K - $150K | Custom Quote |
We deploy a systematic, four-phase approach to transform your manufacturing event logs into actionable intelligence for process optimization and bottleneck elimination.
We architect secure pipelines to ingest and normalize event logs from your MES, SCADA, and ERP systems, establishing a single source of truth for your production workflows. This foundational step ensures data integrity and sets the stage for accurate AI analysis.
Our specialized algorithms automatically discover, map, and visualize your actual production processes, identifying deviations from ideal workflows and quantifying bottlenecks. We move beyond simple visualization to causal analysis, explaining why deviations occur.
We implement deterministic rule engines alongside probabilistic AI to perform deep conformance checking. Our systems correlate process deviations with equipment sensor data, quality metrics, and operator logs to pinpoint the root cause of inefficiencies, such as a specific machine model causing delays.
We deliver prescriptive recommendations—not just insights—and integrate them directly into your operational systems. This includes automated work order generation in your CMMS or dynamic scheduling adjustments in your MES, creating a closed-loop system for continuous process improvement. Learn more about our related service: Industrial AI Copilot Integration Services.
From day one, we engineer solutions with industrial-grade security. Data pipelines are encrypted, access is role-based, and all analytics comply with relevant industry standards (e.g., ISO 27001, NIST CSF). Your proprietary process intelligence remains fully secured within your environment.
We establish a governance framework for your process mining AI, enabling continuous retraining as your operations evolve. This includes monitoring for model drift, tracking the business impact of optimizations, and ensuring your digital twin of operations never becomes outdated. Explore our approach to responsible AI: Enterprise AI Governance and Compliance Frameworks.
Enabling Efficiency, Speed & Accuracy
We build AI systems for teams that need search across company data, workflow automation across tools, or AI features inside products and internal software.
Common questions from CTOs and operations leaders evaluating AI for process discovery and optimization.
Standard deployments take 2-4 weeks from data connection to actionable dashboard. This includes 1 week for data pipeline setup and validation, 1-2 weeks for model training and process discovery, and 1 week for dashboard configuration and stakeholder training. Complex multi-factory deployments with legacy system integration may extend to 6-8 weeks.
About the author
CEO & MD, Inference Systems
Prasad Kumkar is the CEO & MD of Inference Systems and writes about AI systems architecture, LLM infrastructure, model serving, evaluation, and production deployment. Over 5+ years, he has worked across computer vision models, L5 autonomous vehicle systems, and LLM research, with a focus on taking complex AI ideas into real-world engineering systems.
His work and writing cover AI systems, large language models, AI agents, multimodal systems, autonomous systems, inference optimization, RAG, evaluation, and production AI engineering.
How We Work
One-fit-all AI don't work for modern businesses. At Inferensys, we aim to understand your business & custom requirements; which we use to define most efficient agentic workflows, the data, and the tools for your business.
The first call is a practical review of your use case and the right next step.
