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Engineering AI Benchmarks Named Customers, Measured Outcomes

Verifiable named-customer outcomes vs marketing-grade accuracy claims. McDermott live: 10,247 tags / 600 P&IDs / 99.5% measured field-level accuracy. GCKC + Zetwerk in production builds. Methodology, audit process, and competitor comparison below.

McDermott

Live (Production)

Tag-Document Register Extraction

Tags extracted

10,247

P&ID drawings processed

600

Measured field-level accuracy

99.5%

Engagement detail. Live production engagement. Continuous revision-tracked maintenance over the engagement lifecycle. Every tag mapped to every source P&ID with positional context. Output structured into CFIHOS 2.0 native asset register feeding McDermott's downstream asset management workflow.

Methodology. Accuracy measured at field level (each extracted attribute, not document level). Sample-based audit on 1,200 randomly-selected tags from the 10,247-tag set; 6 tags found out of spec, audited and corrected, accuracy calculated at 99.51% per audit cycle. Audit performed by independent QA engineer with no involvement in extraction. Per-tag audit trail provided with bounding-box source evidence.

Reference availability. Reference call available under NDA; named-customer case study in publication pipeline (target Q2 2026 release).

GCKC

In Build

P&ID Revision Delta → PO Impact + MR Package Assembly

Procurement scope

$60M+

Workflow scope

Live revision cycle pilot

Target accuracy SLA

99.5%

Engagement detail. Active production build with GCKC on the P&ID revision delta → open PO impact analysis workflow combined with upstream MR package assembly. Pilot scope covers a live revision event on a $60M+ capex procurement programme with 8,000+ open PO lines.

Methodology. Per-revision pilot methodology: upload Rev A + Rev B P&IDs; Pathnovo extracts delta; structured impact report against active PO register; cost impact validated by GCKC procurement engineering team; recovery savings measured against baseline manual MoC review process. Early signals: $6,000-$600,000 of previously-invisible procurement exposure detected per first revision event processed.

Reference availability. GCKC reference will be available on case study publication (target Q3 2026 release pending pilot completion + commercial outcome confirmation).

Zetwerk

In Build

BOM Generation + Vendor Datasheet Compliance

Procurement workflow

Multi-vendor RFQ

Document scope

Datasheet compliance

Target accuracy SLA

99.5%

Engagement detail. Active production build with Zetwerk on BOM generation from drawings combined with downstream vendor datasheet compliance validation. Multi-vendor RFQ workflow integration with structured deviation reports per vendor.

Methodology. Per-package methodology: BOM extracted from drawing set; MR template auto-populated; vendor RFQ responses received; per-vendor compliance check executed; deviation reports generated. Recovery measured against baseline manual MR + compliance review process at Zetwerk procurement engineering team.

Reference availability. Zetwerk reference will be available on case study publication (target Q3 2026 release pending pilot completion).

Pathnovo's accuracy claim is backed by methodology, not marketing. Field-level measurement, independent audit, contractual SLA with remedy clause. Verifiable.

Field-Level Accuracy, Not Document-Level

Accuracy measured per extracted attribute (tag, line, equipment, instrument, valve), not per document or per drawing. A single P&ID may have 50-200 extractable attributes; document-level accuracy hides per-attribute performance. Field-level measurement makes the SLA meaningful.

Independent Audit Process

Audit performed by an independent QA engineer with no involvement in the extraction process. Sample size selected per ISO 2859-1 (statistical sampling for inspection by attributes) at AQL 0.65 unless otherwise specified by client. Per-attribute audit trail provided so any out-of-spec attribute is traceable to source.

Contractual SLA with Remedy Clause

99.5% field-level accuracy is contractual, not aspirational. Remedy clause: re-process at no cost and credit the difference if accuracy slips below 99.5% on any audit cycle. Audit cycles run quarterly on production engagements; on-demand audits available for client-driven verification.

Named-Customer Outcomes vs PE-Exam Claims

Other engineering AI vendors (e.g. IntuigenceAI) cite PE (Process Engineering) exam scores as proxy for capability. PE exam tests theoretical knowledge; it does not test extraction accuracy on production engineering documents. Pathnovo's benchmark is the actual extraction outcome on McDermott (10,247 tags / 600 P&IDs / 99.5% measured) — the engineering reality, not the test-score proxy.

Other engineering AI vendors cite different proof points: marquee customer redrawing volumes, PE exam scores, horizontal benchmarks. None are equivalent to verified field-level extraction accuracy on production engineering documents. Side-by-side:

IPS iDrawings (Mitsubishi reference)

Their claim

5,000+ P&IDs converted to SmartPlant format with 'up to 60% cost reduction'

Pathnovo's verified counter

Mitsubishi outcome is a SmartPlant-format redrawing volume; cost reduction is a marketing claim, not an accuracy measurement. Pathnovo's McDermott outcome is an extracted structured tag-document register with measured 99.5% field-level accuracy, audited.

IntuigenceAI (PE exam claim)

Their claim

81% PE Process Engineering exam pass rate; '8x better than frontier LLMs'

Pathnovo's verified counter

PE exam tests theoretical process engineering knowledge, not extraction performance on production drawings. Pathnovo's McDermott outcome (10,247 tags, 99.5% measured) is the extraction reality on the actual buyer use case.

Reducto AI (horizontal benchmark)

Their claim

$0.015/page general-purpose document parsing API

Pathnovo's verified counter

Reducto is benchmarked on horizontal document tasks (tables, forms, simple PDFs). Engineering drawings (P&ID symbols, isometric topology, ISA 5.1 conventions) are out of distribution; Reducto degrades sharply on these. Pathnovo's domain-specific accuracy on McDermott is not comparable to Reducto's horizontal benchmark.

Hexagon SDx2 (Chiyoda Qatar NFE LNG reference)

Their claim

$500M+ capex SmartPlant projects

Pathnovo's verified counter

Hexagon's customer scope (SmartPlant-authored content) is a different use case than Pathnovo's (extraction from any source format). Both are real production engagements at scale; comparison requires scope clarification. For brownfield + multi-vendor extraction (where SDx2 cannot operate), Pathnovo's McDermott reference is the relevant proof point.

AVEVA AIM (Wood, SCG Chemicals reference)

Their claim

Multi-year owner-operator AIM programmes at tier-1 scale

Pathnovo's verified counter

AVEVA's customer references are AIM platform deployments (storage + visualisation + operational integration). Pathnovo's role is upstream extraction feeding AIM platforms. McDermott's tag-document register (Pathnovo) feeds whichever AIM platform McDermott's downstream asset management is on; the two scopes are complementary, not directly comparable.

99.5% field-level accuracy SLA across every Pathnovo workflow. Each document type has its own measurement methodology; full documentation available on request.

P&ID extraction: 99.5% on tags, lines, instruments, equipment, valves

Isometric MTO: 99.5% on pipe lengths, fitting counts, flange ratings

Mill certificate traceability: 99.5% on heat number, chemistry, mechanical properties

HAZOP register extraction: 99% action capture + 98% field-level extraction

Datasheet extraction: 99.5% on parameter values + 98% on parameter classification

Cross-document verification: 99.5% on tag reconciliation + 99% on discrepancy detection

Tag-document register: 99.5% on tag-to-document mapping (McDermott live)

Vendor datasheet compliance: 99.5% on parameter comparison vs MR / PMS spec

What does 99.5% accuracy SLA mean exactly?

99.5% of extracted attributes (tags, lines, equipment IDs, instrument loops, IBR-scoped pressure parts, hazardous-area zones) are correct against the source document. Measured at field level, not document level. Sample-based audit per ISO 2859-1 statistical sampling. Independent QA engineer (not extraction team). Contractual remedy clause: re-process + credit if accuracy slips. McDermott engagement: 99.51% measured per most recent audit cycle.

Is the McDermott engagement public or under NDA?

Engagement scope (10,247 tags / 600 P&IDs / 99.5% accuracy) is publishable as named-outcome reference. Detailed engagement narrative (specific project, exact timeline, downstream asset management platform) is under NDA pending case study publication (target Q2 2026 release). Reference calls available under NDA on request via Pathnovo sales channel.

Are GCKC + Zetwerk references available now?

GCKC and Zetwerk are in active production builds. Reference availability is gated on (1) pilot completion, (2) commercial outcome confirmation, (3) client publication approval. Target Q3 2026 release per Pathnovo case study publication pipeline. Until release, engagement scope is publishable (P&ID revision delta + MR package for GCKC; BOM + datasheet compliance for Zetwerk) but detailed customer narrative is held back per pilot-stage NDA.

How does Pathnovo's accuracy measurement differ from competitors?

Three differences. (1) Field-level vs document-level: Pathnovo measures per extracted attribute; many vendors measure per document, which hides per-attribute performance. (2) Independent audit: Pathnovo's audit process uses an independent QA engineer with no extraction involvement; many vendors audit internally. (3) Contractual remedy: Pathnovo's 99.5% is contractual with remedy clause; most vendor accuracy claims are marketing-grade with no contractual binding.

How is Pathnovo's benchmark different from Intuigence's PE exam claim?

PE exam (Process Engineering Principles & Practice) tests theoretical process engineering knowledge: thermodynamics, fluid mechanics, reaction kinetics, distillation, separations. It does not test extraction accuracy on production engineering documents (P&IDs, isometrics, datasheets, HAZOP studies). Pathnovo's benchmark is the engineering reality: actual extraction outcome on McDermott's 10,247 tags / 600 P&IDs at 99.5% measured accuracy. PE exam is a credibility proxy; McDermott is the production proof.

Why does Pathnovo focus on McDermott (one customer) vs many customers?

McDermott is the deepest production engagement: 10,247 tags is large enough to be statistically robust (not a marketing pilot of 50 drawings), and the engagement is live and continuous (not a finished-and-archived project). For credibility purposes, one large continuous engagement at 99.5% measured accuracy is more verifiable than ten small pilot engagements at 'up to' marketing claims. As GCKC + Zetwerk + future engagements complete, Pathnovo will publish each as a named-outcome reference following the same depth standard.

Can clients audit Pathnovo's accuracy independently?

Yes. Every Pathnovo engagement provides per-attribute audit trail with bounding-box source evidence. Client QA engineers can re-audit any sample; results are reproducible from the audit trail. For tier-1 owner-operators with strict procurement standards, on-demand third-party audit (TÜV SÜD, Bureau Veritas, SGS, Lloyd's Register, DNV) is supported with audit fee absorbed by Pathnovo if accuracy validates.

What's the methodology for accuracy measurement on different document types?

P&ID extraction: 99.5% on tags / lines / instruments / equipment / valves; measured per ISO 2859-1 sample-based audit. Isometric MTO: 99.5% on pipe lengths, fitting counts, flange ratings; sample-based audit on randomly selected isometrics. Mill certificate traceability: 99.5% on heat number / chemistry / mechanical properties; per-cert audit with chemistry value verification. HAZOP register extraction: 99.5% on action capture (no missed recommendations) + 98% on field-level extraction. Each document type has its own methodology; full methodology documentation available on request.

Pillar

Tag-Document Register

The McDermott workflow: live with 10,247 tags / 600 P&IDs / 99.5% measured accuracy.

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Pillar

P&ID Data Extraction

Core extraction capability with the same 99.5% SLA.

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Pillar

Asset Information Management

AIM register foundation that the McDermott engagement feeds.

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Pillar

Isometric Extraction

99.5% SLA on pipe lengths, fitting counts, flange ratings. Excel S6 #1 ranked workflow.

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Pillar

Mill Certificate Traceability

180,000+ formats with 99.5% chemistry / mechanical / heat number accuracy.

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Pillar

HAZOP Safety Intelligence

99% action capture + 98% field-level extraction across 800-3,000 page studies.

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Alternative

IPS iDrawings Alternative

Compare McDermott vs Mitsubishi reference engagements + accuracy claim methodology.

Learn more

Alternative

IntuigenceAI Alternative

Compare named-outcome benchmark vs PE-exam claim methodology.

Learn more

Alternative

Reducto AI Alternative

Compare engineering domain accuracy vs horizontal benchmark.

Learn more

Alternative

Hexagon SDx2 Alternative

Different scope (SmartPlant authoring vs extraction); both real production engagements.

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Alternative

AVEVA AIM Alternative

AIM platform deployments vs upstream extraction. Complementary.

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Pricing

Pathnovo Pricing

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Reviews

Customer Reviews

Customer testimonials beyond benchmark accuracy figures.

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Compliance

Indian EPC Compliance Bundle

IBR + OISD + PESO + CCOE compliance overlay layered on extraction accuracy.

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Trust

About Pathnovo

Company background, leadership, methodology origins.

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