The RFP process on most sales teams is the same shape: the AE sends the Word doc to the SE on Monday, the SE farms questions out across five people in Slack on Tuesday, half of them get answered by Thursday, the SE rewrites the inconsistent copy on Friday, the AE submits a thin version on Monday because the deadline is Tuesday. The hours are high and the quality is low. Strkr's RFP automation drafts first-pass answers from your approved content library, routes the open questions to the right experts with an SLA, lets reviewers approve in-platform, and ships the final deck back into the deal record with full audit.
An RFP tool is only useful if it covers the whole flow: parse the document, propose answers, route open questions, enforce SLAs, package the result, and feed the audit back into the deal. Strkr ships each of those jobs as a step, not a generic knowledge base you have to orchestrate manually.
The RFP document (Word, Excel, PDF, or a vendor portal export) uploads and Strkr parses it into a structured question list with the section, the question type (short answer, long answer, Yes/No, matrix), and the required format. The AE sees the real workload before the first keystroke.
The Strkr assistant drafts a first-pass answer to each question from the approved content library (prior RFPs, security docs, product docs, pricing pages), tagged with the source and the last reviewed date. The AE and the SE open the RFP with 70% of the questions already drafted.
Questions the library cannot answer confidently route to the right subject-matter expert (security questions to the security owner, pricing to deal desk, product capability to the PM) with the context, the deadline, and the deal context attached. The expert sees a focused queue, not a Slack avalanche.
Each question has an SLA based on the final RFP deadline, with yellow and red thresholds. The AE sees the current state across every expert and the manager escalates on red items before Thursday. The RFP does not die from one person's silence.
The approved answers compile into the vendor's required format (Word with their template, Excel with their matrix, PDF with their letterhead) in one click. The AE no longer rebuilds the file every submission. The output format is a tenant-configurable template per RFP type.
After submission the approved answers write back to the content library with the deal, the vendor, and the submission date. The next RFP from the same industry drafts closer to final. The library grows with the team's work rather than requiring a dedicated content manager to maintain.
A good RFP content library is more than a doc dump. It holds seven specific kinds of content, each with freshness tracking, approval status, and canonical sources. The AE and the SE should be able to see which answers are approved, which are stale, and which need a subject-matter expert review before they ship to a client.
The security library carries the current SOC 2 Type II status, HIPAA posture, pen-test cadence, DPA templates, and the standard questionnaire answers. Each entry has a last-reviewed date and an owner. Stale answers surface for review before they reach a client.
The compliance library carries data residency, retention, breach notification, subprocessor list, and the compliance framework status per regulation. Updates propagate from the policy source so the library does not drift from the compliance operations tool.
Product capability answers are keyed by RFP phrasing, not by internal naming. A question about "sales territory routing" maps to the account routing feature; a question about "forecast predictability" maps to Forecast lock discipline. The AE does not translate internal language in real time.
The pricing library holds published prices, approved discount tiers, and the deal-desk owned bands. Questions in the published range answer directly; questions outside the range route to deal desk with the deal context. The AE never quotes outside the sanctioned range.
Reference content holds published logos, case-study metrics, and named references with the permission state (always-ok, ask-before-use, do-not-use). The RFP flow uses only the permitted ones and surfaces the right contact for an ask-before-use reference.
Legal maintains the standard MSA language, approved redlines, and the carve-outs that have been pre-negotiated for named large accounts. Legal questions in an RFP answer from this library rather than through a Slack ping to the GC.
Every submitted RFP writes back to the library tagged with vendor, deal, industry, and submission date. The next similar RFP drafts off those tagged answers first. The library self-grows and is auditable.
The AI role in RFP automation is specific: match, draft, flag, suggest, summarize, redline. Each task has a human review before it ships to a client. The assistant does not auto-submit answers it is unsure about, and every draft is tagged with the source so the reviewer can trace it.
The assistant matches each RFP question against the content library using semantic search over the approved content. A match carries a confidence score and the source document. High-confidence matches draft automatically; low-confidence matches surface the candidate pool for the owner to choose.
The assistant drafts the answer in the vendor's requested format (word count, formal/plain tone, Yes/No with explanation) using the matched library content. The reviewer approves or edits before the answer compiles into the final deliverable.
The assistant flags questions where the library content is older than the staleness threshold, where the answer requires legal review, or where the answer implies a capability outside the sanctioned content. The AE sees flags before they ship, not after.
For capability questions the assistant suggests a relevant reference logo, a case-study metric, or an in-product screenshot from the approved library. The AE accepts or declines. The RFP ships with the right proof points rather than generic marketing language.
The assistant drafts the one-page executive summary that most RFPs ask for, pulled from the matched capability answers and the deal context. The AE reviews and personalizes to the vendor's named stakeholders.
For MSA-style attachments the assistant proposes pre-approved redlines from the legal library and surfaces anything that would require GC review. The GC reviews the exception list, not the entire document.
A typical RFP cycle touches an email thread with the vendor, a shared drive for the input document, a Slack channel for routing, a spreadsheet for progress tracking, a Word doc for drafting, and the CRM for audit after the fact. Strkr collapses the six surfaces into one with the deal record as the anchor.
The vendor's clarification questions, revised deadlines, and submission portal reminders thread back to the deal record. The AE does not search three mailboxes for the latest version of a question. The audit trail is complete.
The uploaded RFP document and the vendor's revisions version on the deal with a diff view. The AE knows exactly what changed between v1 and v3 of the vendor's question list, not a mystery about which doc is current.
The subject-matter expert sees a focused queue of their open RFP questions with context, deadline, and deal detail. The Slack channel that scrolled questions off the top gets to be quiet; the expert works a list instead.
Progress across all open RFP items, drafted, in review, approved, flagged, lives on the RFP page itself. The manager reads the state without opening a sidecar workbook. The spreadsheet retires.
The approved answers compile into the vendor's required format on one click. The SE no longer merges answers into a Word template by hand. The output format is tenant-configurable per RFP type (strategic, mid-market, security-only).
When the deal closes won or lost, the submitted answers, the SMEs involved, and the final deliverable are on the deal record. A win/loss review reads the real content, not a tribal recollection. The content library improves on real feedback.
Honesty: for teams submitting a very high volume of RFPs with a dedicated proposal team, a specialist RFP tool (Loopio, Responsive, RFPIO) remains the right choice. Strkr's RFP automation covers the typical sales-team case well; it does not replace the dedicated proposal-management stack for the two cases below.
A team with five or more full-time proposal writers running fifty-plus RFPs a quarter has workflow needs (reviewer assignments, SLA dashboards, project-level ownership) that a specialist tool handles better than a CRM add-on. Strkr still works for them as the deal-record anchor; the specialist tool runs the proposal workshop.
Teams that submit through fifty distinct vendor portals with their own quirks (RFP360, Ariba, Jaggaer, GovWin) benefit from the specialist tool's portal integrations. Strkr's RFP automation handles the content and the audit; the specialist tool handles the submission layer for portal-heavy segments.
Content library, SME routing, SLA tracking, and vendor-format packaging on the deal record itself. The library grows per submission. Flat seat price.
Word (.docx), Excel (.xlsx), PDF (both text and scanned with OCR), and the common vendor portal exports. The parser extracts the question list with the section, the question type (short answer, long answer, Yes/No, matrix), and the required format. If the vendor sends a quirky template, the ops lead can configure a parser profile for that vendor so the next RFP from the same source parses cleanly.
Every library entry has an owner, a last-reviewed date, and a staleness threshold. Entries past the threshold flag for review and surface in the owner's review queue. Approved answers from each submission write back to the library tagged with vendor, deal, industry, and submission date, so the library grows with the team's real work rather than requiring a dedicated content manager to maintain. Security and compliance entries pull from their source policies when possible, so the library does not drift from the policy owner.
Open questions route to the right subject-matter expert (security to the security owner, pricing to deal desk, product to the PM, legal to the GC) with the question context, the final RFP deadline, and the deal context attached. The expert sees a focused queue, not a Slack avalanche. Each open question has an SLA with yellow and red thresholds, and the AE and the manager can see the state across every expert in one view.
For questions where the content library has a high-confidence match the assistant drafts automatically and tags the answer with the source. For low-confidence matches the assistant surfaces the candidate library entries for the owner to choose from. Every draft is reviewed by a human before the answer compiles into the final deliverable. The assistant does not auto-submit answers it is unsure about; the confidence threshold is tenant-configurable.
The approved answers compile into the vendor's required format on one click: Word with the vendor's template, Excel with the vendor's matrix, PDF with your letterhead. The output format is a tenant-configurable template per RFP type (strategic, mid-market, security-only, government). The compiled deliverable attaches to the deal record with the full audit of which answer came from which library entry.
For teams with five or more full-time proposal writers running fifty-plus RFPs a quarter, or for teams that submit through fifty distinct vendor portals with their own quirks, a specialist tool (Loopio, Responsive, RFPIO) remains the right choice. The specialist tool runs the proposal workshop; Strkr handles the deal-record anchor and the shared content. For the typical sales-team case where the AE and the SE share RFP responsibility across their regular work, Strkr's native RFP automation covers the cycle without a second subscription.
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