Golden Horizons
CAPABILITY · SALES & LEAD-GEN
Quote Builder
Intake answers become a priced, line-item quote in minutes without estimator involvement.
$8,000 build · $2,000–3,500/mo
Talk to us about a Quote Builder build →What it does
Client fills a structured intake; the agent applies your pricing rules and generates a line-item quote PDF with your branding. Handles material costs, labor rates, and margin floors. Sends for approval and tracks status.
Every quote a senior person builds from scratch is time that person isn't selling, managing, or delivering. At most B2B service businesses, quoting pulls a salesperson or an account exec through the same mental loop every time: pull the customer's segment, find the right pricing tier, check whether a volume discount applies, add the right add-on SKUs, calculate tax, verify margin floors, attach the right terms addendum, and send a PDF that looks like it came from a professional outfit. That loop takes twenty to ninety minutes per quote depending on deal complexity. Multiply by forty quotes a month and you've got a significant chunk of a senior salary producing a document that follows deterministic rules.
The deeper problem is inconsistency. When pricing lives in a salesperson's head or scattered across a version-controlled pricing sheet, quotes drift. One rep applies a discretionary ten percent discount. Another forgets to add the onboarding fee. A third uses last quarter's rate card. A deal closes and three months later finance finds revenue leakage because the quote didn't match the contract because the salesperson improvised. These aren't character failures — they're the predictable outcome of a manual process with no enforcement layer.
Golden Horizons builds a Quote Builder that encodes your pricing rules into a structured agent, so the rules run the same way every time without a human intermediating them. The flow starts with a short intake — web form, voice call, or embedded in your CRM — that captures deal parameters: company size, product or service configuration, contract term, payment cadence, add-ons. The agent applies your tier logic, discount schedule, margin floors, and tax rules against those inputs and produces a branded, line-item quote PDF. If the deal requires a discount beyond a threshold you define, it routes to a manager for approval before the quote sends. Nothing leaves without the right eyes on it.
What gets built is specific to your pricing model. A SaaS company with seat-based tiers, multi-year discounts, and implementation add-ons has different rule complexity than a managed-services firm that quotes by project scope or a professional-services shop that prices by engagement type. We start by mapping your current pricing logic — the written rules, the unwritten customs, the exceptions that actually happen — before a single line of code runs.
Use cases
- A B2B SaaS company lets prospects configure their seat count, contract term, and add-on modules through an embedded form; the agent prices the deal, applies multi-year discount rules, and sends a countersigned order form — no sales-ops touchpoint required for standard deals.
- A managed IT services firm stops quoting custom by client and instead runs every prospect through a scoping intake that captures device count, service tier, and response-time SLA; the agent outputs a fixed monthly rate with the correct terms addendum attached and flags sub-margin deals for VP.
- A healthcare-IT vendor configures deals against implementation complexity, training days, and integration scope; the agent enforces a pricing floor on implementation services that reps were routinely discounting away, and routes any exception to the VP of Sales before the quote PDF generates.
- A mid-market industrial manufacturer gives regional distributors a self-serve quoting portal that applies volume tiers, regional pricing schedules, and current surcharges automatically — reps receive a signed quote from the distributor with no internal estimator required for standard configurations.
- A professional-services firm running engagements in audit, advisory, and M&A support encodes its engagement-type rate cards and scope multipliers into the agent so junior account staff can produce accurate SOW-attached quotes without partner review for deals inside defined parameters.
- A commercial insurance brokerage uses the agent to quote standard lines from intake data — industry code, headcount, revenue, claims history — producing a preliminary quote PDF the broker refines before the carrier submission, cutting pre-submission prep time on standard accounts.
What’s included
- Fixed scope with written acceptance criteria before any build starts
- Customization layer for your brand voice and business rules
- Clean handover with documented runbook and live training
- Monthly ROI report for three months post-delivery
- Source code delivered to your GitHub on handover
What’s NOT included
- Third-party API subscription costs (billed to your accounts)
- Data migration from legacy systems
- Ongoing infrastructure costs after handover
Retainer
Monthly retainer covers monitoring, prompt tuning, config refinement, and minor integration additions. Range: $2,000–3,500/mo.
How clients use this
Fixed-scope build with clean handover, then an optional monthly retainer covering maintenance, monitoring, and minor changes. Most clients move to retainer within 60 days of delivery.
Part of
Used in: construction-firms
Questions Quote Builder clients ask
How complex can pricing rule encoding actually get?
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 doesn't replace is a full configure-price-quote system for products with thousands of SKU combinations or manufacturing bill-of-materials dependencies — those 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 there are no surprises about what fits and what doesn't.
How does discount approval routing work when a deal requires an exception?
You define the thresholds during the build — for example, deals up to ten percent off list price auto-approve; deals between ten and twenty percent route to the regional sales manager; anything above twenty percent requires VP sign-off. When the intake parameters produce a quote that hits an approval tier, the agent holds the quote, notifies the right approver by email or Slack 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. Approval decisions log against the quote record so there's an audit trail for finance and leadership. The thresholds, approver assignments, and routing logic are configurable and don't require a developer to update once the build is live.
Does the system track quote versions when a deal goes through multiple rounds?
Yes. Every time a quote is revised — whether the rep adjusts scope, the customer requests 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 was overwritten. Second, it gives sales managers visibility into deals that went through multiple revision cycles — a signal that either the intake didn't capture scope clearly enough or the pricing structure has a structural problem worth fixing. Version records persist in your CRM so the history travels with the deal, not locked in a separate quoting tool.
What e-signature integrations does the Quote Builder support?
The default build wires to DocuSign and HelloSign — both are well-documented, widely used, and straightforward to integrate with a CRM and a PDF generation layer. If your team already has an active DocuSign or HelloSign account, the build uses that account so signed envelopes land in your existing dashboard and audit trail rather than a parallel system. For teams without a current e-sign contract, HelloSign tends to be the lower-cost starting point for standard volume. Adobe Sign is supportable with additional scoping — their API is capable but adds integration complexity. What the build does not do is roll 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.
How does a signed quote sync back to our CRM?
When the e-sign provider confirms a completed signature event, the agent fires a webhook that updates the deal record in your CRM — deal stage advances, 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 because 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 eliminates 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 sales pipeline data becomes unreliable for forecasting. After the build, your pipeline data reflects reality because the update happens automatically at signature, not when a rep remembers to log it.