Average labor productivity in the January 2025 Lighthouse cohort, expressed from WEF’s reported 53% increase.
World Economic Forum · January 2025 · Reported cohort ↗ThinkStack for manufacturing
Find the cause. Improve the process.
Bring inspection evidence, equipment history, and production data into the same investigation. ThinkStack agents surface patterns and assemble the supporting analysis so engineering and quality teams can evaluate causes, resolve exceptions, and plan the next improvement.
Agentic AI in perspective
What connected operations can deliver
Results from advanced manufacturing sites show the impact of coordinated operational change. These examples combine AI with broader digital technologies, rather than isolate agentic AI.
Average reduction in conversion costs in that cohort through AI, analytics, and other digital solutions.
World Economic Forum · January 2025 · Reported cohort ↗Reduction in new-product introduction times reported for value chains flowing through the cohort’s Lighthouse sites.
World Economic Forum · January 2025 · Reported result ↗Published industry research and examples, not ThinkTrends customer results. Estimates and individual outcomes are not guarantees of future performance.
The connected workflow
Equip your experts with modern data workflows
ThinkTrends governs and monitors agent access to tools through the Model Context Protocol (MCP). Combine retrieval-augmented generation (RAG), multi-agent orchestration, vision models, and runtime policies to investigate quality issues, explain production losses, and accelerate engineering review.
01 · Connect the relevant information
Inspection evidenceImages, observations, and labels
Production & equipment dataPermitted telemetry and operational extracts
Quality & maintenance recordsProcedures, events, and work history
Enterprise toolsConfigured MCP servers and APIs
ThinkStack
Agents, tools, and workflow orchestration
MCP-enabled toolsConnect existing MCP servers or build and host custom tools.Grounded retrieval · RAGRetrieve relevant knowledge with source attribution and access policies.Vision & predictive modelsUse configured image and time-series models alongside agent tools.Multi-agent orchestrationChain agents and branch workflows around defined inputs and outputs.Runtime guardrailsConfigure PII redaction, topic restrictions, and prompt-attack filtering.Traces & evaluationsInspect tool calls and score outputs against domain-specific rubrics.
Configured sources · Defined permissions · Specialist review
02 · Deliver outputs your specialists can use
Visual inspectionReview candidatesMaintenanceInvestigation briefsQuality eventsEvidence packetsPerformanceLoss analysisSupplier qualityReview summariesWork instructionsProposed revisions
Where to start
Multiple workflows. A shared platform.
Connect agents around your sources, your process, and your review requirements. Explore what a configured workflow could deliver for your team.
01Visual inspection reviewPut candidate defects and the supporting image in front of quality specialists.
- Start with
- Permitted inspection images, approved defect categories, labeled examples, and acceptance criteria.
- The agent workflow
- Run a configured vision model, organize candidate defects and confidence scores, and link findings to the original images.
- What your team receives
- A review set with detections, source images, and uncertain cases highlighted.
- Specialist judgment
- Quality teams validate model performance and make product acceptance and disposition decisions.
- Measure the value
- False positives, missed defects, review time, and performance by product or lighting condition.
02Maintenance investigation supportGive reliability engineers the equipment history behind an anomaly.
- Start with
- Equipment telemetry, selected anomaly outputs, maintenance records, and service procedures.
- The agent workflow
- Analyze trends, retrieve relevant work history and procedures, and prepare an investigation brief.
- What your team receives
- A source-linked timeline with candidate explanations and checks for engineering review.
- Specialist judgment
- Reliability engineers diagnose the issue and approve maintenance, shutdowns, and work orders.
- Measure the value
- Investigation time, useful findings, and repeat diagnostic effort.
03Quality deviation preparationConnect the evidence behind a quality event before the investigation meeting.
- Start with
- Nonconformance records, inspection results, production extracts, and relevant procedures.
- The agent workflow
- Structure the event, align related records, and assemble a chronology with evidence gaps and analysis.
- What your team receives
- A review packet linking observations, calculations, and source documents.
- Specialist judgment
- Quality engineers establish root cause, approve corrective action, and authorize disposition.
- Measure the value
- Evidence preparation time, documentation gaps, and reviewer rework.
04Production loss & performance analysisHelp operations teams understand where time and material are being lost.
- Start with
- Production counts, downtime logs, scrap records, and agreed performance definitions.
- The agent workflow
- Validate data, run configured SQL or Python analyses, and compare losses across periods, lines, or product families.
- What your team receives
- A performance brief with tables, trends, and questions for the operations review.
- Specialist judgment
- Engineers validate the calculations and decide which process changes to trial.
- Measure the value
- Reporting hours, reconciliation effort, and time to explain a loss.
05Supplier quality review preparationBring supplier documentation and incoming-quality evidence together.
- Start with
- Certificates, inspection records, nonconformance history, and approved supplier requirements.
- The agent workflow
- Extract key fields, check completeness, compare records with requirements, and prepare a source-linked summary.
- What your team receives
- A supplier review packet with missing or inconsistent evidence flagged.
- Specialist judgment
- Supplier quality and procurement teams verify findings and decide acceptance and follow-up.
- Measure the value
- Preparation time, missing-document follow-up, and review corrections.
06Work instruction & change preparationKeep proposed instruction changes tied to approved engineering information.
- Start with
- Current instructions, approved engineering changes, procedures, and reference documents.
- The agent workflow
- Retrieve relevant passages, compare changes, and suggest revised wording with source citations.
- What your team receives
- Tracked instruction edits and a summary of changes requiring review.
- Specialist judgment
- Engineering, quality, and safety owners approve revisions before release to operators.
- Measure the value
- Drafting time, review rounds, and post-review corrections.
Quality investigation · workflow example
From scattered evidence to a clearer investigation
Combine inspection records, production data, and approved procedures in a coordinated workflow. Your quality team receives the context together and controls the conclusion.
Explore document workflows- 01
Gather the event
Collect the selected inspection evidence, records, and scope of the quality issue.
- 02
Connect the context
Retrieve related production history and approved procedures through configured tools.
- 03
Analyze & assemble
Compare the data and prepare a source-linked chronology with open questions.
- 04
Review & act
Engineers verify the evidence and determine root cause, disposition, and corrective actions.
Connectivity, governance & assurance
Enterprise controls for manufacturing.
Connect engineering expertise with governed analysis, while keeping plant operations, quality decisions, and system access under your team’s control.
MCP with managed credentials
Connect tools through registered MCP servers. Reference stored secrets or OAuth connections, and test the handshake before making a tool available.
Explore hosted MCP servers ↗Guardrails that run with the agent
Configure PII masking or blocking, custom identifier patterns, denied topics, and prompt-attack filtering. Set inbound and outbound rules independently, with response-grounding checks on output.
Explore Policy & Guardrails ↗Quality evidence before model changes
Evaluate model outputs against representative images and production conditions. Inspect traces and compare errors before changing the workflow your team relies on.
Explore Evaluation Harness ↗SOC 2 Type II & ISO 9001:2015
ThinkTrends has a SOC 2 Type II report and is ISO 9001:2015 certified for quality management. Discuss the applicable scope and supporting documentation with our team as part of your vendor assessment.
Discuss assurance documentation ↗What’s possible
Give operations teams room to respond sooner.
Production scheduling window14 → 1
days in the frozen scheduling period at Unilever’s Tinsukia factory
Unilever reports reducing its frozen production-scheduling period from 14 days to one through its AI-enabled planning transformation.
Connect operational context
Bring production, demand, and exception data into a defined analysis workflow.
Prepare changes for review
Give planners the evidence and assumptions behind proposed adjustments.
Prove it on your process
Measure planning effort and responsiveness alongside quality and service levels.
A reported result from one factory’s broader AI and digital program, not an agentic-only benchmark or a ThinkTrends customer result.
Unilever · 2025 · Tinsukia Lighthouse site ↗Supporting your evaluation
Bring your review team into the conversation
Share the model, runtime, and governance detail with quality engineering, IT/OT security, legal, and procurement reviewers.
Quality & engineering
Review model evaluation, trace evidence, and how proposed changes reach specialists.
Evaluation Harness MLOps & Vision AgentsIT & OT security
Assess connected tools, permitted actions, runtime isolation, and credentials.
Agent Runtime Environments Secrets ManagerLegal & procurement
Discuss data handling, ownership, and contract requirements with our team.
Discuss legal requirementsCommon questions
Frequently Asked Questions
What does ThinkTrends offer for manufacturers and industrial operators?
ThinkTrends offers agentic AI for quality and operations: inspection and nonconformance review, failure analysis across plants, work order checks and a field assistant for technicians. Agents read records and manuals, find what is out of spec and give engineers the evidence to act.
How is ThinkTrends different from ChatGPT Enterprise or Microsoft Copilot for industrial operations?
General-purpose assistants do not read your MES, ERP or inspection data. ThinkTrends runs purpose-built agents connected to those systems, answers only from approved procedures, keeps engineers in every disposition and can run on an isolated plant network.
Does a ThinkTrends agent disposition a lot on its own?
No. Agents find, explain and recommend. An engineer decides each disposition, and the decision is recorded with its evidence.
Which industrial systems does ThinkTrends read?
MES, ERP, quality and maintenance systems, inspection equipment output and document stores, through governed connectors.
Can ThinkTrends run on an isolated plant network?
Yes. It can run in your cloud, your data center or on an isolated network with no external dependencies.
How does the ThinkTrends field assistant stay accurate?
It answers only from the procedures and manuals you approve, shows the source with every answer and sends anything outside them to a supervisor.
Is our data used to train AI models?
No. ThinkTrends uses operational data only to do the work, inside your own environment. Your data is never used to train, tune or evaluate a model.