AI agents for sales quoting

The quoting speed problem

In most sales organizations, the gap between a customer expressing interest and receiving a quote is measured in days, not minutes. Reps wade through SKU lists, pricing matrices, and discount approval chains. Configuration errors get caught late — sometimes only when the order hits engineering or operations. Every hour spent manually assembling a quote is an hour not spent on the next opportunity, and every pricing error erodes a margin point the business never recovers.

From customer requirement to quote draft

With quortix.ai, an AI agent connected over MCP reads the customer's requirements — from a call summary, an email, or a structured form — and resolves them against your live catalog and pricing rules. In seconds, it produces a valid draft quote with the right configuration, correct pricing, and any eligible promotions applied. The rep opens the visual workspace, reviews the draft, makes adjustments, and sends. Impossible configurations are blocked before they ever leave the rep's screen.

• AI agent resolves customer requirements against your live catalog automatically.
• Promotions, discounts, and bundle pricing applied according to your rules.
• Invalid configurations blocked before the quote is sent — not caught by operations.
• Rep reviews and finalizes in the visual workspace — no new tool to learn.

Fits into the rep's existing workflow

Adoption is the graveyard of CPQ projects. quortix.ai avoids it by meeting reps where they already work: the AI agent can be embedded in CRM workflows, triggered from opportunity records, or run from a chat interface the rep already uses. The visual workspace is the review layer, not the quoting layer — reps don't need to master a new interface to get value from day one.