# Iris Pricing in 2026: Plans, Features, and What to Expect
Iris, the RFP response platform from HeyIris (heyiris.ai), uses quote-only pricing based on active users. Paid plans include unlimited RFPs and questionnaires, while collaborators without an active seat can join for free. The real cost depends on how many people need full access, so teams should map out who will draft or approve responses before asking for a quote.
## **How Does Iris Pricing Work Across Your Team?**
A difficult RFP can quickly pull people from across the business into the same deadline. The answers may already exist, but someone still has to find them and get the right people involved.
Iris, HeyIris's RFP response platform, helps keep that work together by drafting from company knowledge and giving contributors a place to review responses. It can also bring deal context into the proposal, so teams have more of the information they need as they work.
Because Iris charges for active users, the people who need full access can have a direct impact on your quote. This guide breaks down how Iris pricing works, what you get for the cost, and what to consider before choosing a plan.
### **Why Listen to Us?**
AutoRFP.ai supports RFP and questionnaire teams in more than 44 languages, working with companies across APAC, EMEA, and North America. That experience comes from helping teams handle the same kinds of response work covered in this comparison.
For instance, workforce.com [doubled its RFP participation rate](/customer-stories/how-workforce-com-doubled-their-rfp-response-rate-with-ai-rfp-software) with AutoRFP.ai, while [Cubiko](/customer-stories/how-cubiko-slashed-security-questionnaire-response-time-by-85-with-ai-rfp-software) cut security questionnaire response time by 85%.
## **How Much Does Iris Cost?**
As of September 2026, Iris does not publish a dollar price. Instead, it charges by active user and asks buyers to contact sales for a quote.
Here's what Iris makes public:
| Pricing detail | Iris |
| ---------------------------- | -------------------------------------- |
| Published price | No |
| Pricing model | Per active user |
| RFP and questionnaire volume | Unlimited |
| Collaborators | Unlimited |
| Per-submission fees | None published |
| Contract options | Annual or multi-year |
| Evaluation | Guided evaluation and proof of concept |
An active user is someone who logs in to draft, review, or approve responses. Stakeholders who only need to view final exports do not count toward the paid-seat total.
So when you ask for a quote, focus on how many people actually need to work inside Iris. Unlimited collaborators can help, but anyone actively working on responses may still require a paid seat.
## **What Drives the Final Iris Price?**
Iris pricing mainly depends on who needs full access and how long you commit.
- Active users: Your quote rises with the number of people who need to draft or approve responses inside Iris, while added seats are prorated for the rest of the billing period.
- Contract length: Iris offers annual and multi-year agreements, with longer terms potentially reducing the price even though the discount is not published.
- Response volume: Paid seats include unlimited RFPs, DDQs, and security questionnaires, so higher submission volume does not create a published overage fee.
For teams with a small group of active users and a high response volume, that pricing model can be easier to plan around.
## **What Do You Get With Iris?**
### **Decide Which RFPs to Pursue**
Iris scores incoming RFPs using criteria your team sets, such as deal fit and historical performance. The resulting qualification summary can help you decide whether an opportunity is worth pursuing.
### **Draft RFPs and Proposals**
Iris drafts responses from approved company knowledge and can bring CRM context into the response.
It supports structured RFPs and longer narrative proposals, with unlimited AI response generation included in paid plans.
### **Check the Sources Behind Answers**
Iris shows the supporting documents behind generated answers and uses confidence scores to flag responses that may need more attention.
Reviewers can edit or approve responses, with version history available to track changes.
### **Manage Company Knowledge**
The Knowledge Map connects information from tools such as SharePoint, Google Drive, Confluence, and Salesforce.
Iris can [flag aging or expiring content](/features/content-management), helping teams identify information that needs another review before reuse.
### **Coordinate Reviews**
Teams can assign questions to contributors and track progress inside Iris. Approval workflows support responses that need formal sign-off, with role-based access controlling who can work on them.
Some stakeholders can also collaborate without requiring a paid active seat.
### **Support Public-Sector Bids**
Iris integrates with GovSpend for teams pursuing government contracts. GovSpend surfaces public-sector opportunities, and Iris can help qualify them before the response work begins.
## **Iris Pros and Cons**
### **Pros**
- Unlimited response volume: Paid users can work on unlimited RFPs and[ security questionnaires](/security-questionnaire-automation) without published per-submission fees.
- Fast first drafts: Iris generates responses from company knowledge and supports both structured requirements and longer proposal content.
- Source visibility: Responses can include citations and confidence indicators, with version history available for review.
- Qualification before drafting: Go/no-go analysis helps teams decide which opportunities are worth pursuing before response work begins.
- Public-sector support: The GovSpend partnership connects government opportunity discovery with Iris's proposal workflow.
- [Collaboration](/features/collaboration): Iris supports assignments and approvals, with CRM connections and unlimited non-active collaborators.
### **Cons**
- Quote-only pricing: Iris explains its per-user model but does not publish the cost of an active seat.
- Paid access for core users: Anyone drafting or approving responses inside Iris counts toward the paid-user total.
- Knowledge quality still needs attention: The platform's own documentation says Iris is only as useful as the information placed in the Knowledge Map.
- GovSpend is a separate dependency: Teams interested in the public-sector integration need both Iris and GovSpend access for the connection to work.
## **Best Iris Alternative: AutoRFP.ai**
Iris covers much of the same response workflow, but AutoRFP.ai goes further on how each answer is checked before submission. Its accuracy-first, AI-native approach is built for structured RFPs, security questionnaires, and [DDQs](/ddq-response-software) where teams need clear evidence behind every response.
Each answer is generated from approved company content and shows the supporting sources, with review controls that help teams manage formal sign-off. That makes AutoRFP.ai a stronger fit when the response needs to stand up to compliance review.
### **Know Which Answers Need Attention**
AutoRFP.ai gives reviewers separate signals for the evidence behind a response and how well it answers the requirement.
A winning response is correct, complete, and in your company's voice, and AutoRFP.ai measures every answer on all three before a person reads it.
- Trust Score: Shows how strongly the available company content supports the response.
- Feedback Score: Flags answers that may still need more detail.
- Exact Match: Reuses a previously approved response when there is a strong match.
- No Results Found: Routes unsupported requirements to a person rather than guessing.
Reviewers can also inspect the source material inside the Response Editor. That gives your team a clearer path to the answers that need judgment.
That is the mechanism behind zero hallucination by design: approved sources only, a citation on every answer, confidence scored, and anything unsupported routed to a person. It is abstention built into the workflow, not just source display.
### **Bring Response Work Into Your Existing Tools**
AutoRFP.ai connects with the systems where your knowledge and reviewers already work.
- Knowledge sources: SharePoint, Google Drive, Confluence, and Notion can feed content into the platform.
- Reviews: Slack and Microsoft Teams can bring response questions closer to SMEs.
- Sales workflows: Salesforce keeps [RFP work](/rfp-software) tied to the opportunity.
- Procurement portals: The Portal Agent can pull requirements into AutoRFP.ai without manual retyping.
The Q&A Agent can also answer from the shared library inside Slack or Teams and show the supporting sources.
### **Go Beyond Internal Sources When Needed**
The standard response workflow centers on company content. Users can separately ask AutoRFP.ai's agents to search the web or work from connected sources when outside research is useful.
Any resulting material goes through review before it becomes part of the response, keeping that research distinct from approved company knowledge.
### **Keep Your Content Governed**
AutoRFP.ai still relies on a shared content library, with people responsible for what enters circulation. Content Managers can:
- Edit or archive outdated material.
- Assign ownership when content needs review.
- Update tags and organize approved knowledge.
- Feed approved project responses back into the library.
This keeps human ownership in place without forcing teams to rebuild the same response knowledge after every project.
### **Set Clear Rules for Sign-Off**
Admins can control when responses are locked and who can reopen approved work. Export approvals can also keep completed projects from leaving AutoRFP.ai before final sign-off.
AutoRFP.ai is also ISO 27001:2022 certified and undergoes annual SOC 2 Type II audits, giving security reviewers the documentation they need without as much back-and-forth during vendor reviews.
## **How Much Does AutoRFP.ai Cost?**
AutoRFP.ai publishes pricing for its two standard plans:
| Plan | Price | Projects |
| ---------- | ----------------------------- | -------- |
| Scale | $899/month, billed annually | 24/year |
| Accelerate | $1,299/month, billed annually | 50/year |
| Enterprise | Custom | Scalable |
Scale and Accelerate include unlimited users and unlimited AI usage. All core features, SSO, integrations, support, and online training are included as well. Current rates are on the AutoRFP.ai pricing page.
Your plan comes down to how many RFPs or questionnaires you expect to handle each year. That also makes the comparison with Iris easier. AutoRFP.ai prices around project volume, while Iris bases its quote on the number of active users.
## **AutoRFP.ai Pros and Cons**
### **Pros**
- Separate review signals: Trust Scores assess the evidence behind an answer, while Feedback Scores flag responses that may need more work.
- Clear failure path: Teams can set quality thresholds so weak or unsupported responses are routed for human review.
- Stronger approval controls: Response locking and export approval help teams manage formal sign-off.
- Unlimited users: Scale and Accelerate let SMEs and reviewers participate without adding seat costs.
- [Broad integrations](/integrations): AutoRFP.ai connects with tools such as SharePoint, Salesforce, Slack, and Microsoft Teams.
- Built for structured responses: RFPs, RFIs, security questionnaires, and DDQs run through the same response workflow.
### **Cons**
- Higher starting price: Scale begins at $899 per month when billed annually.
- Annual project limits: Scale includes 24 projects and Accelerate includes 50.
- Content still needs owners: Content Managers remain responsible for reviewing and maintaining shared knowledge.
- Less suited to narrative-heavy bids: AutoRFP.ai focuses more on structured response work than long-form government proposal writing.
## **Which One Fits Your Team**
- If you want the fastest possible first drafts and pursue public-sector bids through GovSpend: Iris.
- If accuracy and a defensible compliance review on every answer matter most: AutoRFP.ai.
- If you want AI-native drafting that still passes a security or audit review: AutoRFP.ai.
- If unlimited submission volume for a small, fixed group of seats is the priority: Iris.
## **Iris vs. AutoRFP.ai**
| Feature | Iris | AutoRFP.ai |
| --------------------------- | ----------------------------------------------------------------------------------------- | ------------------------------------------------------------------------------------------------------------------------------- |
| Best fit | Teams wanting fast AI-assisted RFP and proposal creation with unlimited submission volume | Mid-market and enterprise B2B teams handling structured RFPs, security questionnaires, and DDQs with formal review requirements |
| Pricing visibility | Quote-only | Scale and Accelerate published |
| Pricing model | Per active user | Annual project volume |
| Users | Paid active users, unlimited collaborators | Unlimited users on every plan |
| Submission volume | Unlimited RFPs, DDQs, and security questionnaires | 24 projects on Scale, 50 on Accelerate, scalable Enterprise |
| AI-native | Yes | Yes |
| Source citations | Yes | Yes, through the Citation Engine |
| Answer confidence | Confidence scoring | Trust Score / Trust Rankings |
| Requirement completeness | Compliance and response-quality tooling | Separate Feedback Score |
| When support is weak | Low-confidence responses can be flagged for review | Low Trust / No Results Found plus configurable requirement-satisfaction threshold and human routing |
| Exact approved answer reuse | Knowledge and approved-answer reuse supported | Exact and Near Match workflows, with verbatim reuse available where appropriate |
| Long-form proposals | Strong capability | Supported, but structured responses are the primary focus |
| Go/no-go analysis | Yes | Yes |
| Content management | Knowledge Map, freshness controls, connected sources | Shared library with ownership, review queues, expiry controls, snippets, tags, and approved-project updates |
| Collaboration | Assignments, approvals, audit trails, free collaborators | Assignments, co-editing, sequential reviews, approval policies, Slack and Teams workflows |
| Portal workflows | Browser and portal workflows | Portal Agent for online procurement and security portals |
| Public-sector workflow | GovSpend partnership | Not a primary focus |
| Web research | Prospect and deal research used in proposal workflows | Separate Project and Response Agent research paths |
| Security | SOC 2 Type II, GDPR, SSO/SAML, RBAC, audit controls | SOC 2 Type II, ISO 27001:2022, SSO, response policies, audit trails, regional hosting |
| Evaluation | Guided evaluation and proof of concept | Two-week proof of concept on the buyer's own RFPs |
| G2 Rating | 4.9/5 | 4.8/5 |
## **Try AutoRFP.ai With Your Own Content**
AutoRFP.ai is built for teams that want more control over how answers are checked before submission. You can see the source behind each response, review its Trust Score, and use Feedback Scores to spot answers that need more work.
We would rather show you than tell you: prove it on your own RFPs in a two-week proof of concept. [Book a demo](/book-demo) and we will run AutoRFP.ai on one of your own RFPs or security questionnaires.