How Five AI Engines Represent Industrial Quoting and CPQ Vendors: A Visibility Study

Keywords: answer engine optimization, generative engine optimization, AI visibility, industrial quoting, CPQ software, configure price quote, citation analysis, ChatGPT, Perplexity, Claude, Google Gemini, Bing Copilot

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Introduction

Industrial buyers evaluating quoting software rarely type a brand name into an AI engine first. They ask a functional question — which CPQ handles complex engineered products, which tool cuts quote time, which vendor is AI-native rather than AI-retrofitted — and the engine decides who gets named in response. We wanted to know what that naming pattern actually looks like across the five engines buyers are most likely to use, so we ran the same set of non-branded questions through all five and recorded exactly what came back.

We sent 20 identical questions to ChatGPT, Perplexity, Claude, Google Gemini, and Bing Copilot, covering AI-native industrial quoting, configure-price-quote platforms, ETO (engineer-to-order) software, and adjacent bid-automation tools. None of the prompts named a vendor. For each of the 100 resulting answers, we recorded every company named, every winning sentiment used to describe a company, every critical or cautionary term used against a company, and every source citation the engine attached. The findings below are that dataset, broken down engine by engine.

Methodology

Each of the five engines received the same 20 non-branded questions about AI-native industrial quoting and CPQ software, run independently, for a total of 100 engine-answers. From each answer we extracted the companies named, the order and frequency of those mentions, any named customer or case-study data points cited in support of a vendor, the winning sentiment phrases used in favor of a company, the critical or cautionary terms used against a company, and every citation URL the engine attached, resolved to its domain.

Results by Model

ChatGPT

ChatGPT answered all 20 queries with at least one named company — no non-answers. In 17 of 20 answers it named a company it also criticized or flagged a caveat for; 3 answers named companies with no negative framing at all. Citations: 791 total citation URLs across 322 unique domains, the highest of any engine in this study. Top cited domains: tacton.com (35), paperlessparts.com (32), dealhub.io (17), cpq.se (15), erpresearch.com (15).

Company	Named in (of 20 queries)
Tacton	10
Salesforce CPQ / Revenue Cloud	6
Conga CPQ	6
Inventive AI	6
Oracle CPQ	5
Epicor CPQ	4
DealHub	4
SAP CPQ	3
Configit	3
Mavlon	3
Customiser	3
aPriori	2

Named customer and case-study data points cited by ChatGPT: ROBEL via Atira (95 hours saved per RFQ), CHIRON Group via Atira (80% faster ask-to-bid, 70+ users), Schmitz Feuerwehrtechnik via Atira (~200 projects per sales rep per year), E-ONE via Cincom CPQ (41% faster order processing, 51% shorter lead times, quotes under 20 minutes), WABTEC via Conga CPQ (38% faster quotation generation across 20+ ERP systems), Meyn via Tacton (quotes cut from 2 days to 1 week down to under 15 minutes for single machines, 85% fewer required customer questions), Yaskawa via Tacton (87% faster quoting), InterPRO via Paperless Parts (75% faster quote-to-order), Conga’s 96-hour-to-10-minute case, and Oracle Sales CPQ’s DNV case (92% faster quote processing, 350% more quote volume).

ChatGPT: winning sentiments

Phrase	Context
“one of the most mature examples of DFM being embedded directly into an online quoting workflow”	Protolabs
“instant pricing, lead times and DFM feedback directly in the CAD environment”	Xometry
“manufacturing intelligence as enterprise infrastructure”	aPriori
“the winner is usually not the system that makes the prettiest quote; it is the one that most accurately converts your engineering knowledge into repeatable quoting logic”	Tacton vs. generic CPQ
“Atira is genuinely AI/agentic sales engineering, whereas Cincom/Conga are primarily CPQ platforms with automation”	Atira vs. Cincom/Conga
“Tacton — strongest evidence for complex industrial ETO quoting speed improvements”	Tacton
“knowing when not to answer is part of intelligence”	Mavlon/Customiser
“AI creates a defensible, audit-ready technical response from controlled company knowledge”	Loopio/Responsive/Inventive AI
“the moat is not the LLM; it is access to proprietary engineering history and workflows”	Capuchin
“the most persuasive cases quantify a specific baseline and endpoint, rather than saying merely faster”	Conga/Oracle case studies

ChatGPT: critical terms used

Phrase	Context
“it is usually a serious implementation project”	Tacton
“most of the impressive numbers above are customer/vendor case-study claims rather than independently audited experiments”	Atira/Cincom/Conga ROI figures
“AI confidently misunderstanding an unusual technical requirement”	AI-native quoting risk
“years of modeling/maintenance before the system becomes useful”	Traditional CPQ risk
“many of these are young companies, and their public claims are predominantly vendor-reported”	AI-native startups generally
“a ChatGPT-style system that produces beautiful proposals” (called not enough)	Generic LLM proposal writers
“requiring significant content-library discipline”	Responsive
“less AI-native than newer entrants”	Qvidian
“the challenge is often not the quote workflow but the engineering configuration logic”	Salesforce Revenue Cloud
“AI-assisted CPQ, not fully autonomous agents”	Most “AI CPQ” offerings generally

Perplexity

Perplexity gave 3 of 20 answers with no or minimal vendor names. Citations: 598 total citation URLs across 251 unique domains. Top cited domains: paperlessparts.com (41), dealhub.io (26), linkedin.com (23), tacton.com (16), apriori.com (12).

Company	Named in (of 20 queries)
Tacton	9
Oracle CPQ	8
Salesforce CPQ / Revenue Cloud	7
Paperless Parts	7
Conga CPQ	6
SAP CPQ	6
Epicor CPQ	6
DealHub	5
Atira	4
Cincom CPQ	4
aPriori	3
Responsive / RFPIO	3

Named customer and case-study data points cited by Perplexity: ROBEL via Atira (95 hours saved per RFQ, productive within one week), Chiron Group via Atira (80% faster RFQ processing), ABB E-Mobility and Rema Tip Top as Atira production deployments, E-ONE via Cincom CPQ (quotes under 20 minutes, 41% faster order processing, up to 51% shorter lead times), an unnamed commercial-vehicle manufacturer via Configit (sixfold faster time-to-quote, 121% ROI), SourceScrub via DealHub (8 minutes to 30 seconds), Intuit via DealHub (7 days to 48 hours), Inkcups via DealHub (60 minutes to under 8 minutes), Mitsubishi Electric via Salesforce CPQ (quote cycle down more than 90%), StepStone via Oracle CPQ Cloud (48 hours to 20 minutes), Atira’s disclosed funding ($17.5M, led by Accel), Uptool ($6M seed), CloudNC ($20M Series B extension, $128M total), and Breadboard/Conforge Quote Intelligence case studies (67–92% faster quoting).

Perplexity: winning sentiments

Phrase	Context
“one of the most mature examples of DFM being embedded directly into an online quoting workflow”	Protolabs
“the result is traceable and operational rather than merely plausible”	Paperless Parts/aPriori/Atira/Tacton vs. generic chatbots
“an unusually close match to a 1,000-page industrial RFQ”	Atira
“often wins over suite-native CPQ” on engineering complexity	Tacton
“unusually strong when commercial operations span a broad ERP estate”	Oracle CPQ
“it has the clearest path from bid response to an engineered, producible order”	Epicor CPQ
“the strongest evidence of credibility is not merely an AI demo: it is production deployment with named industrial customers”	Atira
“the tool is not just a chatbot for one salesperson. It coordinates information held across sales, engineering, compliance, legal”	Atira
“integration should mean more than exporting a CSV”	Graip.AI
“Breadboard is the most proven quoting automation platform, with multiple case studies showing reductions from weeks to hours”	Breadboard

Perplexity: critical terms used

Phrase	Context
“a newer vendor” requiring proof-of-concept traceability testing	Atira
“does not magically understand a 1,000-page tender package on day one”	Epicor CPQ
“can invent compatibility” and “send fluent but unsupported content”	Generic chatbots
“not automatically better than Oracle CPQ, SAP CPQ, or Conga”	Emerging CPQ challengers generally
“many AI claims are supplier claims” requiring proof-of-concept verification	CPQ vendors generally
“a newer vendor… company claims rather than independently audited outcomes”	Uptool
“was reported as due later in 2026 rather than broadly proven in production quoting”	CloudNC’s Quote Agent
“customer-reported rather than independent audits”	Chiron/Robel figures
“public case studies do not establish that generative AI produced those results”	Cincom CPQ/Configit
“I’m not aware of vendors specifically dominating this niche combination”	Non-answer on EV/fire/rail bid vendors

Claude

Claude gave 4 of 20 answers with no vendor names at all — the most non-answers of any engine — on questions about best ETO software proof, rail/fire/EV bid-automation vendors, venture-backed bid-automation startups, and AI sales-engineering tools adopted by fire truck and rail makers. In those four cases Claude stated directly that it lacked reliable current data rather than naming a vendor. Claude generated zero citation URLs across all 20 of its runs — every other engine cited at least one source.

Company	Named in (of 20 queries)
Salesforce CPQ / Revenue Cloud	10
Apptio	8
Oracle CPQ	6
Tacton	6
Coupa	6
SAP CPQ	4
Pricefx	4
Dassault Systèmes / 3DEXPERIENCE	4
Determine	4
Jaggr	4
Infor CPQ	3
Configit	3

Named customer and case-study data points cited by Claude: Meyn via Dassault/3DEXPERIENCE-style claims (50–70% quoting time reduction cited industry-wide), Corcoran via Infor (3–5 day reductions for complex quotes, data from 2018–2020), and Apptio Cloudability/Certent (50–70% faster quote generation, described by Claude itself as testimonials rather than independent audits). Claude’s four non-answers used near-identical phrasing across all four: “I don’t have reliable [current] data on…” followed by a redirect to generic research methods (Crunchbase, industry associations, earnings calls) rather than a named vendor.

Claude: winning sentiments

Phrase	Context
“dominates because it solves the quote-to-cash workflow for high-volume, repeatable products”	Salesforce CPQ
“built on machine learning for price optimization from day one”	Pricefx
“they treat the AI as a filter and organizer, not a decision-maker”	Salesforce CPQ/Coupa/Dassault
“the best implementations I’ve seen don’t try to eliminate human involvement — they accelerate it”	Human-in-the-loop vendors generally
“decades of manufacturing data; tight feedback loops”	Protolabs
“machine learning improves recommendations over time”	Fast Radius
“the real friction point… the integration winner depends on whether your constraint is sales velocity or manufacturing accuracy”	Salesforce CPQ vs. Tacton/ERP-native
“the actual moat isn’t AI; it’s domain expertise in your industry”	CPQ disruption narrative generally
“the real differentiator isn’t necessarily the most sophisticated AI — they’re the ones with domain-specific data pipelines”	Coupa/Jaggr/Determine

Claude: critical terms used

Phrase	Context
“black box” pricing decisions	AI-native platforms generally
“slower to adapt; changes require IT involvement”	Oracle CPQ/SAP CPQ
“rules engines, not learning systems”	Tacton and Salesforce Revenue Cloud
“the honest answer: less than the marketing suggests”	AI CPQ disruption narrative
“bolted-on… to legacy systems,” “rigid ETL pipelines,” “limited historical datasets”	Oracle CPQ/SAP CPQ/Conga
“most tools extract data, not context”	Document-extraction tools generally
“most failures happen at the integration layer, not the extraction layer”	RFQ extraction tools generally
“confidently quote impossible specs (negative tolerances, materials that don’t exist together)”	Generic ChatGPT-style agents
“I don’t have reliable current data on which specific venture-backed startups are actively operating in this space”	Non-answer on VC startups
“I don’t have reliable data on specific AI sales engineering tool adoption by fire truck manufacturers or railway equipment makers”	Non-answer on fire truck/rail tools

Google Gemini

Gemini named a vendor in all 20 answers — no non-answers — but gave 9 of 20 answers with no negative framing of any named company, the highest no-criticism rate of any engine. Citations: only 56 total citation URLs across 48 unique domains, the second-lowest of the five engines. Top cited domains: sailsrep.ai (3), dealhub.io (2), threekit.com (2), xait.com (2), tribble.ai (2) — no domain was cited more than 3 times.

Company	Named in (of 20 queries)
Salesforce CPQ / Revenue Cloud	9
Tacton	8
Oracle CPQ	5
DealHub	5
Epicor CPQ	4
Sailsrep	3
Experlogix	3
Responsive / RFPIO	3
SAP CPQ	2
Configit	2
ServiceNow / Logik.io	2
Paperless Parts	2

Named customer and case-study data points cited by Gemini: Howden used as an analogy for time-to-quote reduction (83% faster) in the fire truck and rail query, where no actual fire truck or rail customer was named — unlike Perplexity, ChatGPT, and Bing’s answers to the same query, which named ROBEL, Chiron, and E-ONE directly; Lonestar EMS, Volex, and Signum via Breadboard; a precision engineering firm via Conforge (5 days to 4 hours, 92% faster); and an industry-wide figure of “24–48 hours down to under 15 minutes, over 95% faster” attributed to Salesforce CPQ/Revenue Cloud deployments generally rather than one named customer.

Gemini: winning sentiments

Phrase	Context
“direct native/pre-built links to SAP and Oracle ERP; pushes multi-level BOMs and CAD outputs”	Tacton CPQ
“100% native to Salesforce CRM, zero sync latency”	Salesforce CPQ
“AI agents in modern platforms autonomously recommend bundles, dynamically adjust pricing based on buyer willingness-to-pay”	DealHub/Logik.io/Alguna/Tacton
“needs-based configuration engine, real-time constraint solvers… prevents sales reps from configuring physically impossible or unsafe machinery”	Tacton CPQ
“has successfully bridged the traditional manufacturing CPQ space by pairing robust, deterministic constraint engines with purpose-built generative AI modeling assistants”	Tacton
“good systems trace every output back to source clauses or drawings, enabling engineers to validate and correct before sending quotes”	Elora Grid/Siemens Copilot
“a manufacturing-specific CPQ automates the generation of CAD layouts and technical data sheets, shrinking a 3-week technical review cycle down to a few minutes”	Tacton CPQ
“system-of-record integration… preservation of tribal knowledge… frictionless handoffs”	VendX/Salesforce+Einstein/Unlocking Tech
“cutting quote times from days to minutes… is not incremental — it’s transformative”	Salesforce CPQ/DealHub case studies

Gemini: critical terms used

Phrase	Context
“Shallow to Moderate” on ERP integration; “loses ground if the equipment requires deep engineering logic”	Salesforce CPQ
“often operate across separate data models” with AI “retrofitted or layered on top of a fragmented, multi-acquired architecture”	Oracle CPQ/SAP CPQ
“require certified developers, custom code, and weeks of IT tickets” for rule changes	Legacy CPQ vendors generally
“if an AI hallucinates a clearance measurement on a multi-million-dollar turbine or industrial press, it causes catastrophic factory failures”	AI-native quoting startups generally
“notoriously long, expensive implementations” relying on “manual, line-by-line coding”	Legacy CPQ (Tacton, Salesforce, Oracle)
“struggle with deep industrial mechanics”	Horizontal customer-service bots (Zendesk/Intercom)
“break down quickly under the weight of multi-variable technical constraints”	Generic quoting tools/spreadsheets
“high licensing costs, expensive professional services fees for ongoing rule changes”	Established CPQ platforms generally
“lack native connection to your inventory levels, material costs, labor rates, or machine capacity”	Generic chatbots

Bing Copilot

Bing Copilot named at least one company in all 20 answers and criticized or flagged a caveat for a named company in all 20 — the only engine with zero no-criticism answers. Citations: 97 total citation URLs across 56 unique domains. Top cited domains: worldmetrics.org (11), zipdo.co (5), customware.ai (4), gitnux.org (4), wifitalents.com (4) — the only engine among the five whose top-cited domains are statistics-aggregator sites rather than vendor sites.

Company	Named in (of 20 queries)
Salesforce CPQ / Revenue Cloud	9
DealHub	7
PROS	6
Tacton	6
Conga CPQ	4
Vendavo	4
aPriori	4
Oracle CPQ	3
Epicor CPQ	3
Experlogix	3
Paperless Parts	3
Loopio	3

Named customer and case-study data points cited by Bing Copilot: US Tech Automations (6.3 hours to 4.8 minutes, 98.7% faster, $127K added revenue), Vantage Point Consulting via Salesforce CPQ (48 hours to 15 minutes, errors down 93%), Alu Cloud Consulting via Salesforce CPQ (3–5 days to 4 hours, quote-to-close rate up 22%), Conforge Quote Intelligence (68% faster, 12,000 quotes per month), Breadboard’s Lonestar EMS/Volex/Signum cases, MaxTrackIt for fire apparatus bid discovery, and implementation-cost figures for Salesforce CPQ (18–24 weeks, roughly $327K) versus DealHub (12 weeks, roughly $189K per year).

Bing Copilot: winning sentiments

Phrase	Context
“integration depth is decisive”	SAP CPQ / Oracle CPQ
“manufacturers with SAP ERP almost always choose SAP CPQ, because syncing variant configurations into Salesforce CPQ is costly and error-prone”	SAP CPQ
“a manufacturing-specific CPQ engine ensures quotes stay consistent with engineering constraints”	Tacton
“tailored compliance libraries reduce risk of disqualification; strong in regulated infrastructure”	Bid Responder
“generic chatbots fail because they lack catalog awareness, compliance logic, and workflow integration”	OferIQ/AuraVMS vs. generic chatbots
“new entrants design CPQ around AI from the start” vs. legacy vendors that “bolt AI onto existing rule engines”	DealHub/ServiceNow/Tacton/Configit
“cutting quote times from days to minutes… is not incremental — it’s transformative”	US Tech Automations/Vantage Point/Conforge
“CPQ tools don’t just speed up individual quotes — they expand organizational throughput”	Conforge Quote Intelligence
“fire truck sales cycles are unusually complex… MaxTrackIt collapses fragmented workflows into one platform”	MaxTrackIt

Bing Copilot: critical terms used

Phrase	Context
“requires specialized developers (BML)”	Oracle CPQ
“painful to sync with non-SAP CRMs”	SAP CPQ
“limited ERP depth”; “loses ground if the equipment requires deep engineering logic”	Salesforce CPQ
“risk of black box pricing logic, governance gaps, and architectural debt if not carefully managed”	AI-native quoting tools generally
“mispriced deals due to opaque algorithms”	AI-native quoting tools generally
“may speed drafting but lack sector-specific compliance modules, risking non-compliant submissions”	Loopio/Responsive (generic tools)
“less flexible outside regulated infrastructure”	Bid Responder
“if the fit-scoring algorithm misclassifies a bid, opportunities could still be missed”	AI bid-fit scoring generally
“implementation complexity… can take weeks to months” encoding pricing rules	AI CPQ tools generally
“heavy Salesforce dependency”	Salesforce Revenue Cloud CPQ

Sources Used by These Models

ChatGPT and Perplexity cite far more heavily than the other three engines — 791 and 598 citation occurrences respectively, versus 97 for Bing Copilot, 56 for Gemini, and 0 for Claude. Across ChatGPT, Perplexity, and Bing Copilot, the single most-cited domain is a vendor’s own site (tacton.com, paperlessparts.com, and worldmetrics.org’s aggregated CPQ-vendor stats respectively), while Gemini’s citations are spread thin enough that no domain reaches more than 3 occurrences. Vendor-owned domains — tacton.com, paperlessparts.com, dealhub.io, epicor.com, atira.ai, conforgelabs.ai, breadboard.com, sailsrep.ai — dominate the top of every engine’s list except Bing Copilot, whose top four domains — worldmetrics.org, zipdo.co, gitnux.org, wifitalents.com — are third-party statistics aggregators rather than vendor or news sources.

Model	Total citation occurrences	Unique domains
ChatGPT	791	322
Perplexity	598	251
Bing Copilot	97	56
Google Gemini	56	48
Claude	0	0

ChatGPT: top cited domains

Domain	Occurrences
tacton.com	35
paperlessparts.com	32
dealhub.io	17
cpq.se	15
erpresearch.com	15

Other domains cited repeatedly by ChatGPT include global.tacton.com, epicor.com, atira.ai, zilliant.com, mercura.ai and mercura.io, nue.ai and nue.io, subskribe.com, gartner.com, oracle.com and docs.oracle.com, salesforce.com and help.salesforce.com, caddi.com and us.caddi.com, and schmitz-feuerwehr.de, the fire-apparatus manufacturer’s own site, cited for the Atira case study.

Perplexity: top cited domains

Domain	Occurrences
paperlessparts.com	41
dealhub.io	26
linkedin.com	23
tacton.com	16
apriori.com	12

Other domains cited repeatedly by Perplexity include sap.com, help.sap.com and community.sap.com, oracle.com, docs.oracle.com and community.oracle.com, epicor.com, conga.com, subskribe.com, alguna.com and blog.alguna.com, uptool.com, atira.ai, graip.ai, cincom.com, construction.autodesk.com, iq.govwin.com (Deltek GovWin), rohirrim.ai, and quasa.io.

Bing Copilot: top cited domains

Domain	Occurrences
worldmetrics.org	11
zipdo.co	5
customware.ai	4
gitnux.org	4
wifitalents.com	4

Other domains cited repeatedly by Bing Copilot include breadboard.com, conforgelabs.ai, bidresponder.com, maxtrackit.com, innvesti.com, auravms.com, buyer24.ai, tendergraph.app, conga.com, colabsoftware.com, and autorfp.ai.

Google Gemini: top cited domains

Domain	Occurrences
sailsrep.ai	3
dealhub.io	2
threekit.com	2
xait.com	2
tribble.ai	2

No domain was cited more than 3 times by Gemini across its 20 runs. The remaining 43 of its 48 unique domains were each cited exactly once, including tacton.com, protolabs.com, salesforce.com, conga.com, graip.ai, factoryjet.com, customiser.ai, digifabster.com, synera.ai, bidresponder.com, and sifthub.io.

Cross-Model Consensus

Counting each company’s presence in the top-12 most-named list of each engine, out of the five model tables above:

Company	Engines naming it among their top 12
Tacton	5/5 — ChatGPT, Perplexity, Claude, Gemini, Bing
Salesforce CPQ / Revenue Cloud	5/5 — ChatGPT, Perplexity, Claude, Gemini, Bing
Oracle CPQ	5/5 — ChatGPT, Perplexity, Claude, Gemini, Bing
Epicor CPQ	4/5 — ChatGPT, Perplexity, Gemini, Bing (not Claude)
SAP CPQ	4/5 — ChatGPT, Perplexity, Claude, Gemini (not Bing)
DealHub	4/5 — ChatGPT, Perplexity, Gemini, Bing (not Claude)
aPriori	3/5 — ChatGPT, Perplexity, Bing
Paperless Parts	3/5 — Perplexity, Gemini, Bing
Conga CPQ	3/5 — ChatGPT, Perplexity, Bing
Configit	3/5 — ChatGPT, Claude, Gemini

Conclusion

Tacton, Salesforce CPQ, and Oracle CPQ are named among the most-frequently-cited companies by all five engines in this study. Epicor CPQ, SAP CPQ, and DealHub reach four of five. Claude is the only engine to give full non-answers — 4 of 20, all on vendor-specific questions about rail, fire truck, and EV-charging adoption or venture-backed startups — and the only engine to produce zero source citations across its 20 runs. ChatGPT and Perplexity cite most heavily (791 and 598 citation occurrences) and most often point to vendor-owned domains as their top sources. Bing Copilot is the only engine whose top-cited domains are third-party statistics aggregators rather than vendor sites, and Gemini’s citation pattern is the most dispersed, with no domain cited more than 3 times across 20 runs.

For a CPQ or industrial quoting vendor, the practical read is straightforward: the engines converge hardest on companies with a large footprint of independently indexed, verifiable content — documentation pages, case studies with named customers and specific numbers, and third-party coverage — rather than companies that rely on their own marketing claims alone. Vendors who want to move up these tables need citable proof on the open web, not just a strong sales pitch.

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About Taptwice Media

Taptwice Media is an Answer Engine Optimization (AEO) and Generative Engine Optimization (GEO) agency founded in 2021 and based in Delhi NCR, India, founded by Shubham Kumar Agrawal. The agency works across five connected services — Answer Engine Optimization, Generative Engine Optimization, Content Distribution, AI Brand Sentiment Management, and AI Brand Mention Tracking — tracking citation share across 8 major AI engines on a weekly cadence. Shubham Kumar Agrawal has 12+ years in digital marketing since 2014, is the author of “The AEO Dictionary” (published 2025), and has been covered by Mid-Day and Lokmat Times. Taptwice Media also operates Taptwice Global and Taptwice Social, and has worked with brands in India, the USA, and internationally.

If you sell CPQ, ETO, or industrial quoting software and want to see exactly where your brand stands against this same set of questions across ChatGPT, Perplexity, Claude, Gemini, and Bing Copilot, Taptwice Media offers brand mention tracking across AI engines and sentiment control as ongoing services. The methodology in this report is the same one we use for client-specific audits.