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SalesTop 10 Best AI Quoting Software of 2026
Ranked picks for ai quoting software for proposals and pricing, including Qwilr, PandaDoc, and Proposify, plus tools like ConnectWise Sell.
How we ranked these tools
Gitnux editors write the brief first: the topic, the inclusion rules, and the frame for what belongs.
Agents extract product evidence with provenance, then collect written reviews and transcribe video reviews and podcasts.
Framework: Features 40% · Ease 30% · Value 30%
Gitnux may earn a commission through links on this page — this does not influence rankings. Editorial policy
For technology service providers and MSPs that want controlled, repeatable quoting from CRM context with revision history and approvals, ConnectWise Sell is the surest overall pick, whereas Oracle CPQ fits enterprise teams needing governance tied to Oracle pricing data, and if you’re optimizing around AI-assisted quote drafts in HubSpot deals, HubSpot Sales Hub is a strong entry.
Editor’s top 3 picks
Three quick recommendations before you dive into the full comparison below — each one leads on a different dimension.
ConnectWise Sell
Guided selling flows that generate quote drafts from opportunity data while preserving revision history.
Best for: Fits when teams want controlled, repeatable quoting from CRM context with revision history and approvals.
Oracle CPQ
Editor pickOracle CPQ applies pricing and constraint rules in real time during guided quote configuration.
Best for: Fits when enterprise teams need CPQ governance tied to Oracle product and pricing data.
HubSpot Sales Hub
Editor pickQuotes inherit deal context and stay linked to CRM records, so follow ups and history remain on the opportunity timeline.
Best for: Fits when teams want AI-assisted quote drafts tightly aligned to HubSpot deals.
Comparison Table
ConnectWise Sell
vertical specialistConnectWise Sell is a quoting and proposal platform designed for technology service providers and MSPs.
Guided selling flows that generate quote drafts from opportunity data while preserving revision history.
ConnectWise Sell is designed for quote-to-cash workflows where opportunities, accounts, and products stay aligned while reps assemble quote content and pricing inputs. Quote generation supports quote versioning and revision history so deal teams can trace what changed between drafts. Approval routing can be tied to deal stages and thresholds so high-impact discounts and terms receive review before customer send-out.
A tradeoff appears in setup complexity because meaningful quote consistency depends on correct mappings between ConnectWise data and Sell configuration. ConnectWise Sell fits best when a deal desk or sales operations team needs controlled quoting across many reps and offers recurring quote revisions for the same opportunity.
- +Guided quote building ties line items to opportunity context
- +Quote revision history supports internal audit on changes
- +Approval routing supports threshold-based review flows
- +Extensibility supports custom logic around selling steps
- –Effective governance depends on careful Sell and ConnectWise setup
- –Deep customization can require admin time to maintain mappings
- –Some teams need process changes to match approval workflows
Revenue operations teams
Standardize quote steps across reps
Fewer off-process quotes
Deal desk reviewers
Review discount and term exceptions
Controlled exceptions
Show 1 more scenario
Sales reps
Create fast revisions during negotiations
Traceable negotiations
Reps can update quote lines and keep revision history for each change cycle.
Best for: Fits when teams want controlled, repeatable quoting from CRM context with revision history and approvals.
Oracle CPQ
enterpriseEnterprise configure-price-quote with machine learning optimization.
Oracle CPQ applies pricing and constraint rules in real time during guided quote configuration.
Oracle CPQ is engineered for structured quoting, with a pricing and rules engine that applies condition logic while reps configure quote lines. Quote templates and configuration logic help keep offers consistent across deal types, and quote lifecycle controls support revision tracking and approval steps before quote-to-order handoff. Integration typically centers on synchronizing price books and product data with ERP, and syncing customer and account context with CRM systems. Automation hooks matter for teams that want deal desk review queues and governance gates, rather than manual spreadsheet processes.
A key tradeoff is implementation overhead, because durable outcomes depend on accurate product models, pricing condition design, and permissions mapping across sales and operations roles. Oracle CPQ fits best when quoting volumes and pricing complexity require controlled changes, such as tiered discounting with margin guardrails or channel partner quoting with constrained overrides.
- +Rules-based pricing and constraints apply during quote line edits
- +Quote lifecycle supports revision history and approval routing
- +ERP-aligned price books reduce mismatches between quote and order
- +Configurable permissions support constrained sales rep override behavior
- –Time to implement increases with complex product configuration design
- –Advanced deal desk workflows require careful configuration planning
- –Custom process automation depends on integration effort beyond UI setup
- –Usability can feel heavy for low-complexity quoting motions
Sales operations teams
Standardize quote approvals and revisions
Fewer policy exceptions
Revenue operations teams
Maintain ERP-aligned price books
Lower margin reporting delays
Show 2 more scenarios
Deal desk analysts
Review and approve constrained deals
Faster compliant approvals
Deal desk queues and threshold policies route risky deals for controlled review.
Channel partners
Quote within override limits
More consistent partner offers
Partner quoting configurations restrict discounting and options to policy-aligned choices.
Best for: Fits when enterprise teams need CPQ governance tied to Oracle product and pricing data.
HubSpot Sales Hub
SMBHubSpot Sales Hub includes quote and proposal automation tools with e-signature integration.
Quotes inherit deal context and stay linked to CRM records, so follow ups and history remain on the opportunity timeline.
HubSpot Sales Hub supports quote creation that stays attached to HubSpot deals, contacts, and associated products when those records are maintained in the CRM. Deal team collaboration and internal activity logging align quote actions with pipeline movement. AI-assisted drafting works best when sales reps already structure opportunities with consistent products and properties.
A tradeoff appears when quoting needs heavy CPQ-grade configuration, complex pricing rules, or multi-step approval routing that depends on external approvals rather than HubSpot deal workflows. It fits teams that want quote drafts, version tracking inside deal context, and automated follow ups without a separate quote-to-cash command center.
- +CRM-attached quote workflow reduces handoffs and duplicate data entry
- +Deal stage and activity history improves quote revision traceability
- +AI assistance benefits from structured deal fields and product records
- +Sales sequences can automate quote follow up steps
- –Advanced pricing logic needs partner CPQ patterns or custom process
- –Quote approvals and complex routing depend on workflow configuration depth
- –Product configurator depth is limited compared with CPQ-focused tools
- –Line item governance requires consistent CRM catalog hygiene
Sales operations teams
Standardize quotes per deal stage
Fewer template and field mismatches
Enterprise sales reps
Draft proposals from CRM context
Faster first-draft turnaround
Show 2 more scenarios
Deal desk analysts
Review quote revisions in deal history
Reduced review rework cycles
Analysts coordinate approvals with deal updates and can trace what changed without exporting files.
Channel partner managers
Create partner-aligned quote outputs
More consistent partner proposals
Partners produce proposal content that stays consistent with CRM records for account and opportunity context.
Best for: Fits when teams want AI-assisted quote drafts tightly aligned to HubSpot deals.
Vendavo CPQ
enterpriseVendavo CPQ combines guided selling, pricing governance, approvals, and quote creation for B2B sales.
Approval threshold policy tied to pricing and quote content with a revision-scoped audit trail for deal desk traceability.
Vendavo CPQ targets enterprise quote-to-cash execution with deep pricing and approval automation tied to existing commercial systems. It supports configurable quote generation, quote line editing, and revision history workflows designed for deal desk review and structured approvals.
- +Pricing logic runs consistently across quote revisions and downstream pricing documents
- +Deal desk review and structured approvals fit multi-stakeholder sales operations
- +CRM and ERP price book sync keeps quote data aligned with source-of-truth pricing
- +Quote audit trail supports troubleshooting across automated and manual changes
- –Tight governance around pricing and approvals demands careful change control
- –Advanced configuration workflows can slow down sales rep iteration without training
- –External system dependencies make end-to-end testing more complex to stage
- –Guided selling experiences require deliberate template and rules configuration
Best for: Fits when an enterprise needs CPQ governance, pricing-rule automation, and approval workflows tied to CRM and ERP data.
Pricefx CPQ
enterprisePricefx CPQ supports guided selling, pricing calculations, quote configuration, and approval workflows.
Pricing rules engine with margin guardrails that evaluate during quote generation, not after the fact.
Pricefx CPQ generates configured quotes from product rules, guided configuration, and pricing logic that can account for complex constraints. It supports an approval-ready quote-to-cash workflow with quote versioning and revision history tied to pricing outcomes and sales changes.
- +Rule-based product configuration supports constrained bundles and dependencies
- +Pricing rules engine can enforce margin guardrails during quote generation
- +Quote revision history links changes to pricing results and configurator inputs
- +API-driven automation supports deal desk workflows and controlled updates
- –Requires a structured setup of pricing and configuration rules to avoid rework
- –Quote line editor workflows can feel heavy for simple one-off proposals
- –Complex guided selling setups take time to model for each product family
- –External system dependencies can slow iteration during CPQ configuration changes
Best for: Fits when enterprises need CPQ with controlled pricing logic, configurable products, and approval-aware quote revisions.
Subskribe
API-firstSubskribe manages subscription quoting, product catalogs, pricing, approvals, contracts, and billing handoff.
AI drafting paired with quote version history to support controlled revisions before approval.
Subskribe targets sales teams that need AI-assisted quote drafting with tight control over pricing logic and revision tracking. It focuses on proposal output generation, line-item editing support, and guided workflows that reduce freeform quoting.
- +AI-assisted quote drafting reduces time spent on first drafts
- +Template-driven proposals keep formatting consistent across revisions
- +Approval workflows support gated publishing instead of manual discipline
- +Quote version history helps trace edits across deal cycles
- –Limited evidence of deep CPQ configuration rules for complex product trees
- –Automation coverage depends on clear workflow mapping rather than out-of-the-box deal desk logic
- –API and integrations need verification for CRM sync and ERP price book sync depth
- –Advanced approval policies can require careful governance design to avoid bottlenecks
Best for: Fits when teams need AI-driven quote drafting with structured approvals and revision history.
PROS Smart CPQ
enterprisePROS Smart CPQ combines product configuration, pricing guidance, approvals, and quote generation.
PROS pricing rules execution tied to quote configuration ensures line-level commercial logic stays consistent across revisions.
PROS Smart CPQ is built for quote-to-cash flows where pricing rules and product configuration need to stay consistent across proposals, revisions, and channel handoffs. It combines a guided quote configuration experience with quotation document generation, including line-item level control that maps to enterprise pricing structures.
- +Tight alignment between pricing rules execution and configured quote line items
- +Quote revision history supports deal desk review of changed assumptions
- +Strong workflow fit for approval routing and deal governance steps
- +Enterprise integrations support consistent commercial data across CRM and order systems
- –Advanced configuration work benefits from specialized admin ownership
- –Guided selling UX can feel heavy for low-complexity quoting motions
- –Complex bundles can require more rule tuning to avoid edge-case outcomes
- –Template customization takes time when document standards differ across teams
Best for: Fits when enterprise teams need consistent, rules-driven quoting across revisions, approvals, and downstream fulfillment.
Zilliant CPQ
enterpriseZilliant CPQ applies pricing guidance, product recommendations, configuration, and quote workflow controls.
Zilliant CPQ applies complex pricing rules during quote line edits while maintaining revision history for controlled deal governance.
Zilliant CPQ targets quote-to-cash workflows with a pricing rules engine tied to configurable catalog and deal execution needs. It is designed for large-scale commercial quoting where pricing logic, approval routing, and quote governance must stay consistent across sales channels.
- +Pricing rules engine supports dynamic discounting and controlled margin outcomes
- +Quote versioning and revision history support controlled deal changes
- +Strong integration focus supports keeping quote data aligned with CRM and ERP
- +Approval routing supports deal desk workflows and governance checkpoints
- –Guided selling configuration can require significant setup for complex catalogs
- –Quote editor usability can feel heavy for simple, one-off proposals
- –Automation depth can limit flexibility without disciplined configuration
- –Extensibility depends on integration work for bespoke quote behaviors
Best for: Fits when pricing governance and approval control must remain consistent across high-volume sales teams.
Nue
API-firstNue provides quote-to-cash software for subscription, usage-based, and hybrid commercial models.
AI quote drafting that outputs structured, revisionable quote text from configured deal fields.
Nue creates AI-assisted quoting drafts from structured inputs like product selections, customer context, and negotiation notes. It focuses on generating quote text and line-item content while keeping revisions traceable through versioned outputs and repeatable prompts.
- +AI drafts quote language from deal context and configured templates
- +Versioned quote outputs support revision reviews across iterations
- +Field-driven generation reduces missing sections in proposals
- +Consistent phrasing improves deal-to-deal uniformity for reps
- –Pricing logic enforcement needs tight inputs rather than full CPQ control
- –Deep quote line editor features are limited compared with CPQ-first tools
- –Complex approval workflows require external process wiring
- –Governance controls for rep overrides are less granular than deal-desk CPQ systems
Best for: Fits when sales teams need AI-written proposal quotes with repeatable fields and controlled templates.
Configure One
vertical specialistConfigure One provides product configuration, pricing, proposal generation, and order management for manufacturers.
Guided configuration logic drives quote generation so quotes reflect the same structured rules across revisions.
Configure One is an AI quoting solution aimed at companies that need configurable product quotes with structured configuration data. It supports guided configuration inputs and generates consistent quote outputs for complex offerings with many options and constraints.
- +Guided configuration inputs support consistent option selection for quotes
- +Quote outputs stay consistent across revisions by reusing configuration logic
- +Automation reduces manual quote assembly for option-heavy offerings
- +API enables integration into CRM and internal quote generation flows
- –Configuration and quoting setup requires ongoing governance to stay accurate
- –Guided flows can become complex for highly flexible deal structures
- –Approval routing depth depends on workflow integration design
- –Output customization can require technical work for advanced layouts
Best for: Fits when sales teams quote configurable products and need repeatable quote generation with automation and integration.
Conclusion
After evaluating 10 ai quoting software, ConnectWise Sell stands out as our overall top pick — it scored highest across our combined criteria of features, ease of use, and value, which is why it sits at #1 in the rankings above.
Use the comparison table and detailed reviews above to validate the fit against your own requirements before committing to a tool.
How to Choose the Right Ai Quoting Software
We separate options in ai quoting software by how the system turns inputs into consistent, reviewable quotes and then keeps them aligned when details change. The biggest differences show up in configuration flexibility, data handoff quality, and auditability of quote edits via audit log.
Document and email input capture
Why it matters
Document and email input capture determines whether reps can start quoting from real inbound text without retyping. In ai quoting software, this also affects how reliably the system extracts line items and quantities.
How to check
In a demo, import a sample email plus an attached spec or PDF and ask for a quote draft. Then verify the extracted quantities, part names, and quantities in the quote preview match what the source shows.
Catalog sync and attribute mapping
Why it matters
Catalog sync and attribute mapping matters because quotes only stay correct when product attributes and units stay consistent. If mapping is sloppy, reps must fix details before sending.
How to check
Ask the vendor to show how they map your item identifiers, units of measure, and optional attributes into quote lines. Provide one test: change a catalog attribute (like unit or description) and see whether a new quote draft reflects it correctly.
AI draft control and repeatability
Why it matters
AI draft control and repeatability controls whether the output matches your intent and stays stable across similar inputs. That matters when quotes are used for day-to-day selling and not just one-off drafts.
How to check
Run the same input twice and compare whether key fields (line items, quantities, suggested terms) stay consistent. Then test an override: change one detail and verify the quote updates only what should change.
Audit log for quote changes
Why it matters
Audit log for quote changes reduces friction when reps, managers, or ops need to understand what changed and why. It also helps when a draft must be corrected after review.
How to check
Create a quote draft, make edits, and then request the change history view. Confirm you can see before/after values, who made changes, and timestamps for each stage of revision.
Review workflow and gating
Why it matters
Review workflow and gating ensures the system can require checks before a quote is sent. For ai quoting software, gating is the difference between drafts and controlled approvals for higher-risk quotes.
How to check
Ask for a demo workflow where certain quotes trigger review before export or sharing. Then try one low-risk and one high-risk example and confirm the system enforces the different paths.
Quote output templates and formatting
Why it matters
Quote output templates and formatting determine whether the delivered quote matches your sales document standards. In ai quoting software, formatting gaps often force manual cleanup after generation.
How to check
In the quote preview, switch between at least two templates or layouts and verify the content layout, fields, and line item formatting update accordingly. Export and review the output to confirm the fields you expect appear consistently.
Red flags
- The system frequently drops quantities or misreads line items from emails or PDFs.
- Catalog updates don’t reliably propagate into new quote drafts.
- Change history is missing field-level before/after details.
Fit by situation
- If your quoting starts from inbound emails and PDFs, prioritize document and email input capture.
- If you rely on a product catalog with changing attributes, prioritize catalog sync and attribute mapping.
- If managers must understand what changed between drafts and final quotes, prioritize audit log for quote changes.
Frequently Asked Questions About Ai Quoting Software
How do ConnectWise Sell and HubSpot Sales Hub handle quote context during AI-assisted drafting?
Which tools provide a real CPQ pricing rules engine instead of AI text generation only?
When does quote versioning matter for approval routing, and how is it implemented in Vendavo CPQ or Pricefx CPQ?
What breaks if an AI quoting workflow lacks revision-scoped audit logs, as seen in Zilliant CPQ versus Nue?
How do API and extensibility options differ between Configure One and Configure One-style integrations, and how does that affect automation?
How do security controls and access permissions show up in Oracle CPQ compared with Subskribe?
Which tool fits renewal quoting workflows where deal lifecycle handoff depends on consistent quote outputs?
What is the typical integration path for CRM sync and ERP price book sync in Pricefx CPQ and Vendavo CPQ?
Where do AI drafting tools like Nue and Subskribe fall short compared with CPQ-focused platforms?
Tools reviewed
Primary sources checked during evaluation.
Referenced in the comparison table and product reviews above.
Funding and competing interests
This study was co-funded by several of the vendors assessed in it. No single vendor funded it. Funders could propose the market studied.
They had no role in selecting vendors, setting or weighting criteria, analysing data or drawing conclusions, and they received the same factual-accuracy check as every other vendor assessed.
Market definition, inclusion rules and criteria weights were fixed by an editor before research began and did not change afterwards. Editorial process →
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