Conversational analytics built for Tier 1 suppliers, OEMs, and contract manufacturers — turning MES, ERP, quality, and supplier data into the answers your operations team is already asking out loud.
Auto and discrete manufacturing run on a patchwork of MES, ERP, PLM, quality, and supplier portal systems. The data exists. The answers don't — or they take two days, three Excel files, and four meetings to assemble. By then, the line has moved.
You learn a Tier 2 component slipped only after assembly fails — not when the supplier's own data first showed drift. Quality escapes become recalls.
Availability, performance, quality — three numbers, four sources, a weekly report. Shift leads can't compare today against last Tuesday without a BI ticket.
When PPM spikes, the engineer who can correlate it across supplier lot, line operator, ambient temperature, and shift is buried in CSV exports for ten days.
Two plants report KPIs slightly differently. Headquarters can't tell whether Plant B is genuinely better or just measuring differently. Decisions get made on vibes.
New SKUs, new chemistries, new battery suppliers — and the BI team is six months behind on dashboards that already need rebuilding. Operations runs blind.
Finance asks where the $3M in unplanned overtime went. Operations knows it was the November supplier rework. Proving it on paper takes three weeks.
Data Dialogix sits over your existing MES, ERP, quality, and supplier systems. We don't move your data; we make it speak. Your engineers, plant managers, and procurement leads ask questions the way they'd ask a colleague — and get answers backed by the actual underlying systems, with the SQL and the lineage attached.
For automotive, that means we model the way you think: by program, by line, by supplier, by lot, by shift. Not by table name, not by SAP transaction code. When someone asks "what's our scrap rate on the F-series headliner this week," the platform knows which program, which BOM, which line, and which time window — and shows you the answer in fifteen seconds.
We started in Detroit for a reason. Every founding engagement runs through Tier 1 and OEM operations teams who tell us, directly and unfiltered, what's broken about every analytics tool they've tried. The platform is shaped by that feedback.
Live availability, performance, and quality across lines and shifts.
PPM, OTD, PPAP status, and quality trends — by program and by part.
Correlate defects across supplier lot, line, operator, shift, and environment.
Throughput, scrap, downtime — sliced any way you ask.
Standard vs actual cost by SKU, with drilldown to the variance source.
Real questions from automotive operations teams, answered in seconds rather than days.
Every metric below is computed live from source systems, available as a conversational query, and pinnable as an automated monitor.
An anonymized engagement profile drawn from typical Tier 1 operations. Names and specifics generalized — directionally representative of what a six-month engagement looks like.
The starting point. Quality engineers were maintaining a 47-tab spreadsheet to track supplier PPM across three OEM programs. Updates lagged by 5–10 days. Root-cause analysis on a supplier escape took 2–3 weeks of manual SQL queries against SAP.
What we did. Connected SAP MM/QM, the Plex MES, and the supplier portal in week one. Modeled the company's program / part-number hierarchy so questions could be asked in operational language. Built a conversational layer for the quality team and pinned monitors for the top 30 suppliers.
What changed. Within two weeks, the quality team was running root-cause queries in under a minute instead of two days. Within 90 days, the conversational alerts had pre-empted three supplier escapes that the previous reactive process would have missed.
Six months later. The 47-tab spreadsheet is retired. Procurement and quality run shared supplier scorecards. The team's BI engineer was redirected from "build me this dashboard" requests to higher-leverage data engineering work.
For manufacturers, ROI on conversational analytics shows up in three specific places. We instrument each so it's defensible to finance.
Quality, ops, and procurement leads recover 8–12 hours per week previously lost to spreadsheet wrangling. Compounds across teams.
Continuous monitors on supplier PPM and lot-level quality data catch drift 5–15 days earlier than reactive reporting cycles. A single recall avoided pays for several years of platform.
Your data team stops being a ticket queue and gets back to engineering. Reported ratio: 1 conversational analytics seat displaces ~40 ad-hoc BI requests per quarter.
Native connectors for the systems automotive and discrete manufacturing already operate. No data warehouse migration required — though we work with yours if you have one.
Automotive manufacturers operate under layered regulatory and customer-driven standards. The platform is designed to operate inside them.
Lineage and audit trails support the documentation expectations of the automotive quality management standard.
Encryption at rest and in transit, least-privilege access, full audit logging.
US-only data residency option for defense-adjacent programs.
Row-level masking and right-to-erasure workflows for European operations.
Book a 30-minute working session with our team. Bring one operational question your current tools can't answer fast. We'll show you what conversational analytics looks like against your kind of data.
Book an industry demo