The AI root cause investigation platform for manufacturing quality

Identify your root cause in hours, not weeks. Defensible results in front of any auditor.

For quality teams in regulated manufacturing, Lattice is the AI root cause investigation platform that turns scattered evidence into audit-ready findings in days, and learns from every investigation so failures don't make their way back.

Systematic workflow. Full traceability. Audit-ready documentation.

Quality teams in medical devices, pharma, semiconductors, electronics, and advanced mobility use Lattice as their AI root cause investigation platform to produce rigorous investigations faster, without cutting corners.

/ Why Lattice

Why not a spreadsheet, your QMS, or ChatGPT?

Each one helps you write down a root cause. None of them tests whether it's true, or shows an auditor how you got there.

Gathers the evidence

Spreadsheets
Partly: By hand
Your QMS
Partly: Only what's attached
ChatGPT
Partly: Only when asked
Lattice
Yes: Automatically, from every system

Finds the root cause

Spreadsheets
Partly: By consensus
Your QMS
Partly: Provides the template
ChatGPT
Partly: Plausible, but untested
Lattice
Yes: Tests competing hypotheses

Traces every claim

Spreadsheets
No: Lost in email threads
Your QMS
Partly: Tracks edits, not reasoning
ChatGPT
No: Can invent sources
Lattice
Yes: Every finding to its source

Holds up in an audit

Spreadsheets
Partly: Depends on the author
Your QMS
Partly: Proves it was filed
ChatGPT
No: Nothing to verify
Lattice
Yes: Full evidence chain

Learns across cases

Spreadsheets
No: Tribal knowledge
Your QMS
No: Records don't connect
ChatGPT
Partly: Preferences, not causes
Lattice
Yes: Carries proven causes forward

Stores your CAPAs

Spreadsheets
Partly: A tracker sheet
Your QMS
Yes: Its core job
ChatGPT
No: No
Lattice
Partly: Syncs with your QMS

Based on publicly documented product capabilities as of September 2026. QMS reflects ETQ Reliance and MasterControl. ChatGPT reflects ChatGPT Enterprise with connectors enabled. Capabilities vary by plan and configuration.

From defect to defensible report.
Here's what Day 1 looks like.

No integration project. No six-week rollout. Your team runs a real investigation in your first session.

SLK
#ncmr-escalationscoped✓
QMS
CAPA-2026-004 attachmentsscoped✓
IMG
sem_micrograph_03.pngupload✓
API
eDHR event: Cleanroom 4 holdwebhook✓

Connect your evidence

Grant scoped permissions to your QMS, SharePoint, and communication tools. Lattice agentically traverses issue history, syncs attachments, and monitors labels to auto-ingest evidence. No manual data entry.

SlackJiraSharePointWebhooksEmailFile uploadSQL
Gate Oxide Breakdown Voltage Shift
Systematic V_BD Degradation (NMOS)
Thermal Non-Uniformity in RTP...
Lamp Zone 1 (Center) Aging/Failure
Conductor Chat
PLAN
Conductor thinking...
CURRENT HYPOTHESIS
POTENTIAL CAUSES
KEY EVIDENCE

Conductor investigates

AI reconstructs your timeline, generates fault trees, and systematically tests hypotheses.

Fault treesTimelinesCausal analysis
NMOS Thin-Oxide Gate Breakdown Voltage Shift
Export
ReportInvestigation
TIME SAVED
9h 48m hours
FINANCIAL IMPACT
$100,000
Root Cause Findings
Corrective & Preventive Actions

Export a complete report

Every hypothesis tested, every piece of evidence linked, full root cause justification. A report you'd be comfortable handing to your auditor or your customer.

Full traceabilityCAPA linkagePDF / DOCX
Built with 20+ years of quality expertise by engineers from MIT • Johns Hopkins • Google X • Northrop Grumman
Supported by NVIDIA Inception Program • Autodesk Research Residency • Plug and Play
/ Use cases

Lattice handles the work from first signal to final deliverable.

Autostart

Investigations that start before you do

Connect Lattice to signals and trigger cases automatically. It aggregates lot data, reconstructs timelines, and drafts initial hypotheses.

  • Trigger-based case initiation
  • Automated evidence collection
  • Centralized triage review queue
Autonomous Investigations
Inbox
Running
Needs attention
Lot 992A Hypotube Fracture
Running
Initiated from Jira • 12m ago
Cleanroom 4 Temp Drift
Needs attention
Initiated from File upload • 1h ago
Supplier Batch Deviation
Running
Initiated from Webhook • 2h ago
Yield Drop - Site 02
Running
Initiated from Jira • 3h ago
Material CoA Mismatch
Needs attention
Initiated from Webhook • 5h ago
Reports, 8Ds, CAPAs, Fishbones

Automated documentation and reports

Generate technical documentation directly from investigation data. Output standard industry formats with full traceability to source evidence.

  • One-click 8D and CAPA export
  • Bidirectional data traceability
  • Audit-ready, attributed logs
Timeline Summary

Automated timeline reconstruction

Synthesize events from disparate systems into a structured sequence. Provide automated summaries for rapid team onboarding.

  • Multi-system event correlation
  • Summary and deep-dive views
  • Batch-specific sub-timelines
Conductor

AI investigation copilot

Integrated tools for evidence retrieval, SQL queries, and image analysis. Identify logic gaps and adversarial weaknesses.

  • SQL and image analysis tools
  • Adversarial logic review
  • Automated task drafting
Living FMEA

Data-driven FMEA updates

Propose targeted FMEA revisions based on investigation findings. Identify new failure modes and severity shifts.

  • Real-time library cross-referencing
  • Proposed updates via inline diffs
  • Versioned change history
FMEA Library Update
Doc: Catheter Assembly v4.2
Approve All
Failure Mode
Potential Effect
SEV
RPN
Status
HypotubeHypotube Fracture
Patient Injury
89
128144
Update
Tip Split
Vessel TraumaArterial Trauma
47
64112
Update
Coating Delam
Particulate Risk
8
160
New
Seal Breach
Fluid Leakage
56
7590
Update
Lattice Root Cause

Multi-factor causal topology

Model failures as interconnected probabilistic dependencies rather than linear chains. Map physical and procedural factors.

  • Non-linear causal modeling
  • Probabilistic dependency mapping
  • Regulatory-grade documentation
Platform Capabilities

And much more

The rest of what Lattice does to streamline investigation workflows and detect systemic risk.

  • Living process maps: Proposed updates with inline diffs learned from each investigation.
  • Pattern detection: Recurring failures flagged across lots, lines, and sites.
  • Multimodal analysis: Native processing of defect photos, micrographs, and line footage.
  • Data requests: Automated evidence collection from suppliers and operators.
/ What's at stake

A weak investigation costs weeks. Lattice gives up to 80% of them back.

An investigation that closes on the wrong cause looks finished on paper. The bill arrives later.

Illustrative: one deviation, closed the usual way
  1. Day 0

    Deviation logged: particle count out of spec on Line 2.

  2. Day 9

    Closed as “operator error.” CAPA passes, on paper.

  3. Month 5

    The same defect returns.

    The failure comes back

  4. Month 5

    Three engineers spend two weeks reconstructing what happened.

    Weeks of engineering time

  5. Month 7

    An auditor asks how “operator error” was proven.

    A finding on your record

  6. Month 8

    Customer escalation. 8D requested.

    Customer trust erodes

What that time costs you

Your team runsinvestigations a month, each takingengineering hours, at$an hour.

Lattice gives back up to
$460,800 a year
3,840 engineering hours

Investigations per month × 12 × engineering hours each × 80% × hourly cost.

Bring us your hardest open investigation

Quality directors, CAPA owners, and failure analysis leads use the first session to run a real case, not a canned demo. Bring the one that has been open longest. We'll show you what Lattice finds in it, and where the evidence trail leads.