Quote turnaround time is a win-rate problem before it is a productivity problem. Teams that respond to RFPs and bid requests in three to five days lose to competitors whose quotes arrive in hours, and the numbers back it up: the average RFP response now takes 25 hours, a typical winning proposal still consumes 10 to 40+ hours of specialist time, and in construction a full quote can take weeks of estimator hours to assemble.
Every week spent rebuilding a quote from a blank template is a week in which a faster competitor has already anchored the decision.
Shakudo's RFP response automation removes the rebuild. The AI pulls the scope of work directly from the RFP, spec, or bid documents, then searches your own comparable jobs, past quotes, and pricing history to draft the complete quote: line items, bill of materials, pricing, and your margin rules applied. Your estimator reviews a finished draft, adjusts, and approves. Quote creation is cut from weeks to under one day, the estimator's role moves from building quotes to reviewing them, and the team's quote turnaround time lands in the sub-24-hour tier where the first credible bid wins the deal. Loblaw Digital uses Shakudo sovereign AI to move data-intensive operations from slow manual cycles to automated same-day workflows, including the quote and estimation work that used to sit in an estimator's queue for days.
This works on sensitive commercial data because the AI is sovereign: it runs on your own infrastructure, you fully own it, and your data never leaves your environment. That ownership is exactly why the system can read your pricing history, contracts, and margin logic at all. No external cloud, no shared models, no copied credentials. The alternative is an RFP or CPQ SaaS that gives you AI drafting only by moving your answer library, bid history, and pricing patterns into its cloud. Sovereign automation keeps every artifact on your side of the firewall while doing the same work: scope extraction, comparable-job pricing, and a draft quote your team can review.
The workflow runs on a stack your sales ops and data teams already know. Snowflake is where the pricing history, comparable jobs, and bid data live. dbt keeps the margin logic and pricing transforms versioned and testable. LangChain drives the drafting agent that reads the RFP and the comparable jobs. Qdrant is the vector store that makes past quotes and contracts searchable in plain language. n8n orchestrates the submission, review, and approval workflow, and Rill serves the quote dashboard the sales team actually looks at.
Sales, estimating, and RFP teams at RFP-heavy businesses, including construction, industrial, wholesale, and logistics, where the pricing history and bid data are too sensitive to send to a CPQ SaaS vendor.
A CPQ SaaS gives you AI drafting only by moving your answer library, bid history, and pricing patterns into its cloud. Shakudo's AI runs on your own infrastructure, so your pricing history, contracts, and margin logic never leave your environment, and the model stays fully owned and controlled.
From weeks to under one day. The AI drafts the complete quote, line items, bill of materials, pricing, and your margin rules applied, and the estimator reviews and approves instead of building from scratch. The team's quote turnaround time lands in the sub-24-hour tier.
Reviews a complete draft instead of building one. The AI handles the scope extraction, the comparable-job pricing, and the line-item assembly. The estimator adjusts, approves, and sends. The role moves from data entry to judgment, which is where the margin is.
Days, not quarters. You connect the AI to your pricing history and comparable-job data, and the first draft quote lands from your own history in hours. Loblaw Digital runs the same pattern to move data-intensive operations into automated same-day workflows.
With Shakudo, you can deploy this on your own infrastructure within days, not quarters. Book a demo and see how a draft quote is built from your own history in hours.