AI Quote Generator

More complex than most teams expect to fit, less complex than a full CPQ platform. The agent handles tiered pricing by customer segment or contract term, volume discount schedules with thresholds and step-downs, add-on and bundle logic, margin floors by product category, regional or currency adjustments, and conditional terms addenda that attach based on deal type. What it won't replace is a full configure-price-quote system for products with thousands of SKU combinations or manufacturing bill-of-materials dependencies, which have their own tooling category. The practical ceiling is a deal structure where a senior salesperson currently carries the full ruleset in their head or in a spreadsheet. If a human can follow the logic from a pricing sheet and a customer record, the agent can encode and enforce it consistently. We map your actual rules in a discovery session before building, so nothing about what fits comes as a surprise.

You define the thresholds during the build. For example: deals up to ten percent off list auto-approve, deals between ten and twenty percent route to the regional sales manager, anything above twenty percent needs VP sign-off. When the intake parameters produce a quote that hits an approval tier, the agent holds it, notifies the right approver by email or team chat with the deal summary and the requested discount, and waits for an explicit approve or reject before the quote sends. Approvers get a direct link to the deal record, no logging into a separate system. If the approver rejects, the agent can route back to the rep with a counter-suggested price or let the rep revise and resubmit. Every approval decision logs against the quote record for a clean audit trail. The thresholds, approver assignments, and routing logic are all configurable and don't need a developer to update once the build is live.

Yes. Every time a quote is revised, whether the rep adjusts scope, the customer asks for a different term, or an approver requires a price change, the agent generates a new version and archives the prior one. The quote record shows the full version history: who requested the change, what changed, when it was sent, and which version the customer ultimately signed. This matters for two reasons. First, it closes a common audit gap where finance can't reconcile a signed contract against the original quote because the PDF got overwritten. Second, it gives sales managers visibility into deals that churned through multiple revision cycles, which usually signals the intake didn't capture scope clearly enough or the pricing structure has a real problem worth fixing. Version records persist in your CRM, so the history travels with the deal instead of sitting locked in a separate quoting tool.

The default build wires to DocuSign and HelloSign, both well-documented, widely used, and straightforward to integrate with a CRM and a PDF generation layer. If your team already runs an active DocuSign or HelloSign account, the build uses that account, so signed envelopes land in your existing dashboard and audit trail instead of a parallel system. For teams without a current e-sign contract, HelloSign tends to be the lower-cost starting point at standard volume. Adobe Sign is supportable with extra scoping; its API is capable but adds integration complexity. The build never rolls its own signature mechanism. We use the established platforms because their audit trails and legal standing are already tested across jurisdictions. During scoping we confirm which platform fits, and the e-sign flow is built to match your existing process rather than forcing a new one.

When the e-sign provider confirms a completed signature event, the agent fires a webhook that updates the deal record in your CRM. The deal stage advances, the signed PDF attaches to the record, and any fields you want populated from the quote data (contract value, term start date, product configuration) write back automatically. The default build targets HubSpot and Salesforce, since they cover most of the B2B service market and have reliable APIs. For teams on a different CRM, we assess during scoping; most modern CRMs have webhook or API support that accommodates this. The sync kills the manual step where a rep downloads the signed PDF, uploads it to the CRM, and updates the deal stage by hand, a step that gets skipped often enough that pipeline data turns unreliable for forecasting. After the build, your pipeline reflects reality because the update happens automatically at signature, not whenever a rep remembers to log it.