| Posture |
| Primary use case | Buyer-facing CPQ slice: discovery through validated configuration, pricing, and proposal — governed quote record may live elsewhere. Catalog and commercial rules can be modeled in Talkulate AI CPQ AI CPQ's database without a Conga CPQ tenant when Talkulate AI CPQ-only is the program. | Conga CPQ (Advantage CPQ + Smart CPQ) covers enterprise quote-to-cash CPQ — constraint rules, rebates, ABO, quote-to-contract, and suite adjacency to CLM and billing — discovery is often rep-led, guided selling, or custom-built on Cart APIs. | Coexistence |
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| Primary user persona | Buyer self-serve (full / guided / sales-assisted); partner portals; internal presales paste-in. — Escalation target: < 10% of sessions. | Rep and deal desk in CPQ UI by default. Smart CPQ markets headless partner portals and B2B eCommerce — often SI-built on Cart APIs with Conga CPQ as rules core; depth of turnkey buyer UX versus custom portal is program-dependent. | Program-dependent |
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| Advantage vs Smart deployment | Standalone without a Conga tenant: chat widget, iframe, JS snippet, embedded page, headless API, messengers. Connects to any CRM or ERP stack. | Advantage CPQ: Salesforce-native or Conga Platform–hosted with subscription lifecycles. — Smart CPQ: CRM-agnostic constraint engine for manufacturing and distribution with Salesforce and Dynamics paths — packaging is an AE decision. | Program-dependent |
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| Entry UX | Plain-language task entry with optional persona routing (B2B technical / B2C / installer / fleet). — Contextual goals, not rigid decision trees. | Guided selling and rep-led flows in CPQ UI. AiMe and roadmap CPQ agents are platform assistance layers — you build buyer NL entry separately or via headless channels. | Lean Talkulate AI CPQ |
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| Real-time option swaps | Buyer swaps a compatible alternative → Engineer Agent revalidates the full BOM and reprices instantly. Out-of-rule swaps are blocked at the engine level. | Constraint rules and repricing on option change when rules and UI latency allow; Smart CPQ markets sub-second performance on large quotes as a vendor claim. | Lean Talkulate AI CPQ |
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| Self-serve modes | Three built-in modes: full, guided, and sales-assisted; benchmark < 10% escalation. | Smart CPQ markets partner portals and B2B eCommerce via headless architecture — Cart APIs plus SI or partner build are common; turnkey buyer-conversation depth versus custom portal varies by program. | Program-dependent |
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| Q2C suite adjacency | Billing hooks and downstream systems via scoped integrations — no first-party enterprise billing SKU in Talkulate AI CPQ. | Quote-to-contract on Advantage Platform; CLM and integrated billing lifecycle marketed on the CPQ hub — suite modules, not proof that CPQ alone is the billing system of record. | Lean Conga CPQ |
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| Discovery & pricing |
| Discovery model | Interviewer Agent: contextual goals — 6–10 questions, 4–8 minutes to validated BOM in reference case. | Guided selling and rep-led discovery in CPQ UI. AiMe, Discovery AI SKUs, and roadmap CPQ agents are adjacent — not documented as buyer NL discovery with configured-line constraint proof. Not established in Conga CPQ public CPQ materials reviewed (May 2026); verify with Conga CPQ. | Lean Talkulate AI CPQ |
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| CPQ workflow coverage | Buyer-facing CPQ slice: discovery through validated configuration, pricing, and proposal — governed quote record may live elsewhere. Entry through handoff (CRM, ERP, or downstream CPQ) in one buyer engine when Talkulate AI CPQ-only or as the front layer in coexistence. | Configure, price, quote in Conga tenant; ABO lifecycle actions; proposals and BOM outputs; downstream CRM, ERP, CLM, and billing pairing. | Coexistence |
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| Pricing engine depth | List price, volume tiers, bundles, regional lists, SLA adders, and multi-currency — commercial rules validated in the Engineer Agent pass against your catalog database; native enterprise rebate program administration is Conga CPQ CPQ's strength, not parity here. | Price Programs, Rebates, and Promotions with Admin APIs, pricing waterfall APIs, and multi-condition rebate logic — native rebate and incentive program mechanics when rebate governance is in scope. | Lean Conga CPQ |
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| Subscription / asset ordering | Encodes subscription and service lines in the sales BOM when modeled in the tenant catalog — handoff to billing systems is scoped per integration. | Asset-based ordering (ABO): on-demand renewal job APIs, ramp line split, bulk renewal quote generation with documented cart split thresholds — Advantage Platform release notes (Feb ’26). | Lean Conga CPQ |
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| Output formats | Interactive commercial proposal + PDF + per-line reasoning + compatible swaps + branded PDF. | Quotes, BOM, and contract documents via suite modules; price waterfall APIs for commercial transparency on rep-facing flows. | Lean Talkulate AI CPQ |
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| Approval & discount governance | Discount threshold approvals available as add-on — often optional on buyer self-serve where SKU compatibility and price accuracy are the bottleneck, not rep discount chains on day one. | Margin guardrails and automated approval workflows marketed on Advantage and Smart CPQ — valuable for rep-led discount governance; many buyer programs defer multi-step approvals until revenue risk requires them. | Lean Conga CPQ |
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| Deal guidance & price drivers | Engineer Agent applies customer-facing price lists and rules — not historical deal ML in the buyer path. | Smart CPQ AI logic analyzes historical deal data to suggest target prices and discount ceilings with transparent price drivers — rep-side deal guidance, not configured-line proof. | Coexistence |
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| Validation |
| Validation method | Deterministic Engineer Agent against live PostgreSQL via MCP — structured queries for core compatibility, not document similarity. | Patented constraint-based configuration engine (Smart CPQ) and constraint rules with Admin UI and ConstraintRuleActionExpression APIs (Advantage Platform Feb ’26). | Coexistence |
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| Invalid configuration handling | Engineer Agent validates each configured line against the live tenant catalog (structured queries, not document similarity). Incompatible combinations are refused with per-line reasoning before any Conga CPQ handoff. In one published hardware reference program (~3,400 SKUs), standard BOMs no longer required a separate engineering compatibility review after go-live. | Conga CPQ (Advantage CPQ + Smart CPQ) enforces configuration through constraint rules on the tenant catalog. Disallowed combinations are blocked when rules and master data are complete; closing gaps is modeling, testing, and governance work — a different mechanism than buyer-side conversational assistants. | Program-dependent |
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| AiMe & CPQ AI agents | LLM only in Interviewer Agent; Engineer Agent is non-generative for configuration choices. | AiMe (Mar 2026) is Conga CPQ’s unified AI layer on Advantage Platform — prescriptive and agentic positioning. CPQ roadmap highlights AI agents for quote creation and point-of-sale price optimization — treat as roadmap until GA evidence; confirm entitlements. | Coexistence |
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| Dual-agent architecture | Interviewer and Engineer fully separated; Engineer only runs allowlisted DB queries. | Conga CPQ (Advantage CPQ + Smart CPQ) core is rules-driven — not LLM-fronted for configuration. AiMe and Discovery AI are separate layers from constraint proof. | Lean Talkulate AI CPQ |
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| Catalog source connectors | PostgreSQL, MySQL, MSSQL, SAP, NetSuite, Dynamics, Salesforce CPQ, Excel, PDF specs, XML, REST, file drops. | Advantage Platform catalog with Salesforce sync; Smart CPQ integrates with Salesforce and Dynamics and connects to SAP and Oracle via APIs per marketing — connector depth confirm with vendor. | Program-dependent |
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| Per-line audit trail | Per-line reasoning: which constraint triggered each selection — buyer and rep facing. | Price waterfall APIs document commercial breakdown; buyer-visible reasoning for every configured line is not established in CPQ-primary materials reviewed here. | Lean Talkulate AI CPQ |
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| Observability & tracing | Langfuse per session (Interviewer and Engineer traces separately); rate limits on chat and overview endpoints. | Cart and Revenue API references on the developer portal; per-endpoint SLOs and LLM trace layer for AiMe not established in public CPQ materials reviewed here. | Lean Talkulate AI CPQ |
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| Large-quote scale | Optimized for buyer-facing sessions and validated BOM handoff — throughput depends on catalog modeling in Talkulate AI CPQ tenant. | Feature matrix cites Advantage CPQ up to 100,000+ line items per transaction; Smart CPQ markets 10,000+ lines with sub-second performance — vendor claims; tenant benchmarks confirm with Conga CPQ. | Program-dependent |
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| Channels & time to value |
| Embed channels | Widget, iframe (~10 min deploy), JS snippet, embedded page, headless API, internal-tool mode. | Cart APIs with sorting, callbacks, and configuration layout in API responses; CustomConfigurationUrl can load an external configurator in an iframe — you build the external shell. | Coexistence |
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| Async messenger channels | WhatsApp, Telegram, Teams, Slack, Messenger, LinkedIn — same validation engine, scoped per channel. | Messenger-native CPQ intake is not documented as a standard Conga CPQ feature. — Not established in Conga CPQ public CPQ materials reviewed (May 2026); verify with Conga CPQ. | Lean Talkulate AI CPQ |
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| Time to production buyer surface | Envelope 5 days–6 weeks; typical 3–5 weeks; reference case 5 weeks. | Implementer’s Guide frames collaborative programs across business, finance, product, operations, and IT — ABO, rebates, and multi-module Q2C calendar depends on catalog and SI scope. | Lean Talkulate AI CPQ |
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| Customer effort | About 10–15 hours total across 2–3 weeks (typical mid track; min. — 2–3 workshops plus embed). | Heavy stakeholder alignment, constraint and catalog modeling, integration testing, and hypercare — effort scales with ERP, headless, and platform prerequisites. | Lean Talkulate AI CPQ |
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| "No structured catalog" path | Data structuring service ($3,450–$17,250 one-time) for Excel, PDF, and tribal knowledge. | Catalog and rule modeling are admin- and partner-scoped; no public fixed-fee structuring SKU on CPQ product pages. | Program-dependent |
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| Verticals | Eight first-class vertical packs on one engine. | Advantage sectors include technology, healthcare, and services with subscription lifecycles; Smart CPQ targets manufacturing and distribution — partner-led verticalization, not eight named packs. | Lean Talkulate AI CPQ |
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| Security & governance |
| Error mode | Refuse: incompatible combinations are blocked before the buyer accepts output; the engine does not publish out-of-rule builds from document similarity. | Constraint rules block disallowed combinations when modeled; gaps in rules can produce plausible but incorrect quotes until audited. | Program-dependent |
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| Regulatory constraint encoding | CE, FDA, UL, NSF, RoHS, and similar rules encodable in validation engine. | Implementation-dependent in product and constraint rules — depth depends on SI and customer team. | Program-dependent |
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| Anti-prompt-injection | Engineer Agent allowlisted queries only; vendor does not need internal margin data. | Conga CPQ (Advantage CPQ + Smart CPQ) core quoting is not LLM-fronted; AiMe is a separate layer — confirm data handling in DPA. | Lean Talkulate AI CPQ |
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| GDPR / PII posture | DPA; no training on client catalog or conversations; data minimization. | Data Security Exhibit cites ISO 27001 and SOC 2 Type 2 for Subscription Services generically; CPQ-specific scope, residency selectors, and AiMe training posture were not mapped in this publication pass — verify with Conga CPQ. Not established in Conga CPQ public CPQ materials reviewed (May 2026); verify with Conga CPQ. | Program-dependent |
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| Multi-tenant isolation & hosting | Cloud AWS/Azure EU regions; per-tenant DB. — On-prem: $69,000 enterprise license. | SaaS Subscription Services positioning; CPQ-specific data residency selectors not established in this publication pass. | Program-dependent |
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| Built-in analytics | Conversation funnel analytics and demand-sensing export. | Portfolio marketing cites proactive AI agents for cross-sell during configuration; buyer conversation funnel analytics not established in CPQ-primary docs reviewed here. | Lean Talkulate AI CPQ |
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| Margin & cost protection | Data minimization; discount threshold approvals as add-on. — Vendor does not require internal margin data. | Margin guardrails, automated approvals, and deal guidance with discount ceilings — mature rep governance on marketing surfaces. | Lean Conga CPQ |
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| Outcomes & commercial |
| Quote cycle (reference metrics) | See the reference deployment band below. | Customer stories on Smart CPQ marketing surfaces; no matched public study on equivalent buyer self-serve catalog complexity in this publication pass. Not established in Conga CPQ public CPQ materials reviewed (May 2026); verify with Conga CPQ. | Lean Talkulate AI CPQ |
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| First-pass accuracy | See the reference deployment band below. | No matched public study on equivalent catalog complexity in this publication pass. | Lean Talkulate AI CPQ |
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| Quote capacity | See the reference deployment band below. | Buyer-facing self-serve capacity uplift is not published in Conga CPQ materials reviewed here. — Not established in Conga CPQ public CPQ materials reviewed (May 2026); verify with Conga CPQ. | Lean Talkulate AI CPQ |
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| Conversion uplift | A separate buyer-facing pilot (not the server-reseller reference case) reported better web conversion and fewer “waiting for a quote” drop-offs versus that pilot’s own baseline — treat as directional; measure on your traffic. | Buyer-facing conversion uplift from external CPQ UX is not published in Conga CPQ product page pass. — Not established in Conga CPQ public CPQ materials reviewed (May 2026); verify with Conga CPQ. | Lean Talkulate AI CPQ |
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| RFQ unit economics | Illustrative unit economics only (not a price quote for your tenant): manual complex RFQs are often cited around $230–$460 versus automated self-serve often cited up to about $12 per RFQ at volume — use Talkulate AI CPQ pricing and ROI tools for your case. | License economics are quote-based with no public per-seat CPQ list grid — net TCO requires Conga AE and implementer quotes. | Program-dependent |
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| Pricing model | Implementation ($18,400) + monthly ($1,725, 600 dialogs) + per-dialog overage + integration ($115 / hour). Enterprise on-prem: $69,000. | Conga CPQ (Advantage CPQ + Smart CPQ): public pricing page routes to contact sales — no published per-seat CPQ list grid (May 2026). Bundled Q2C SKUs and post–PROS B2B packaging require AE validation. List only — not net TCO. | Program-dependent |
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