# AutoRFP.ai vs Steerlab: Which AI RFP Platform Fits?
AutoRFP.ai vs Steerlab compared from current product, integration, security, and pricing evidence. See which AI RFP platform fits and what to test.
AutoRFP.ai vs Steerlab is the buyer cut between a lighter security-questionnaire product and a
governed mid-market or enterprise response operation. Steerlab's clearest fit is a security team
that wants to load a questionnaire, generate sourced drafts, use confidence scores to guide human
review, and start with one free project. Its public materials also cover proposal and presales
work, but the product evidence is deepest around security questionnaires. The same comparison
tables also live on the
[AutoRFP.ai vs Steerlab landing page](/alternatives/steerlab).
AutoRFP.ai is built for the response operation around those documents. It applies an
accuracy-first architecture across RFPs, security questionnaires, and DDQs, with approved sources
visible to reviewers. Two separate quality signals, sequential governance, exact-format Office
return, enterprise identity controls, and operations reporting make it the stronger documented fit
for mid-market and enterprise teams.
We build AutoRFP.ai. This guide therefore links the evidence and labels public-documentation gaps
as questions to verify. Research covered Steerlab's product, integration, security, team, and
comparison pages; its [Legal Terms](https://www.steerlab.ai/terms-and-conditions) and
[privacy notice](https://www.steerlab.ai/privacy-policy) (both last updated June 19, 2026); its
AWS Marketplace listing; dated G2 reviews surfaced by AWS; and independent funding coverage.
Sources were reviewed on August 25, 2026, with the legal pages re-read on August 27, 2026. Dated
page captures below were taken on August 26, 2026.
## The short answer
**Choose Steerlab** when a security team wants a lighter questionnaire workflow with sourced
drafting, confidence scoring, human review, and one free document.
**Choose AutoRFP.ai** when RFPs, security questionnaires, and DDQs must move through a governed
mid-market or enterprise response operation. Citations sit on the sentence, not only on the
answer: a reviewer can open the quoted passage, the named file or connected system, and the person
behind that source. Trust Score shows how strongly approved content supports an answer. Feedback
Score checks whether the draft answers the requirement. Unsupported questions route to a person,
and approved work returns in the issuer's original Excel or Word file with the response record
intact. That operation also needs published staffed coverage beyond a single European timezone.
Both vendors let you evaluate at no cost, and the scope differs. Steerlab covers one free RFP or
questionnaire. AutoRFP.ai runs a free two-week proof of concept: unlimited access to the whole
platform, your real workload rather than a single document, and our implementation team working
alongside your reviewers for the duration. One document shows you a draft. Two weeks of real
volume shows you the response operation, including the second and third questionnaire that arrive
in the same week as an RFP.
## Where Steerlab genuinely fits
[Steerlab's security-team page](https://www.steerlab.ai/security-teams) makes a clear promise:
answers are sourced, each carries a confidence score, and the product tells the user when it does
not know. That explicit unsupported-answer behavior is a real strength in a category where many
products stop at fluent drafting.
The [proposal-team page](https://www.steerlab.ai/proposal-teams) adds progress tracking, comments,
and collaboration. The [presales page](https://www.steerlab.ai/presales-teams) adds an in-tool
copilot, Slack Q&A, Go/No-Go analysis, and competitor-bias detection. Those are adjacent workflows.
The security-team experience remains Steerlab's clearest public lane.
That framing is consistent with Steerlab's own limitations disclosure. Its
[2026 cybersecurity buyer guide](https://www.steerlab.ai/blog/best-rfp-software-for-cybersecurity-companies-in-2026)
calls Steerlab "a younger company still scaling its customer base." The same guide identifies
human-in-the-loop review as part of the fit. Buyers willing to evaluate a younger vendor can put
one of their own questionnaires through it at no cost.
## Files and portals: inspect what comes back
Steerlab's Responsive comparison page says it ingests Excel, Word, PDF, and narrative proposals.
It also publishes a Chrome extension for browser questionnaires. The public pages establish broad
input coverage, but they do not document a preservation contract for formulas, macros, validation
lists, or nested workbook structure. Steerlab also publishes no comparable document-size ceiling.
A [G2 review surfaced by AWS Marketplace](https://aws.amazon.com/marketplace/pp/prodview-dzqypcxo2svgq),
dated June 6, 2026, gives a concrete test condition: "When exporting with structured templates,
the formatting sometimes shifts slightly, which ends up costing me a few extra minutes to fix
before I can send it out." The same review praises Steerlab's verified-content drafting, clean
interface, and quick adoption, so the export note sits inside a clearly positive review.
AutoRFP.ai retains the original Office file. Import proposes the question, answer, and compliance
mapping for confirmation. Original-file export writes approved responses into the same Excel
cells or Word paragraphs while preserving workbook structure, formulas, macros, and validation
dropdowns. Public pages document support for 5,000+ requirements, 500+ page Word files, multi-tab
Excel, nested tables, hidden tabs, macros, dropdown validation, compliance matrices, multiple
files, and ZIP archives. PDFs import for in-product answering and completed PDF work exports as
Word.
The Portal Agent pulls questions from major procurement and security portals into a response
project. Drafting and review use the same governed workflow, then answers return beside the portal
for one-click copy.
### Files & Portals: AutoRFP.ai compared with Steerlab
What imports cleanly, what returns in the original file, and how portal work enters the response record.
| Capability | AutoRFP.ai | Steerlab |
| --- | --- | --- |
| Import RFPs from tens of formats | Yes: 5,000+ requirements; 500+ page Word files | Partial: Publishes Excel, Word, PDF, narrative proposals, and web portals |
| Answers return in the issuer’s original Office file | Yes | Partial: Structured-template export exists; preservation contract is not public |
| Preserves formulas, macros, sheets, and validation lists | Yes: Includes hidden tabs and nested structures | Partial: No public formulas, macros, or validation-preservation guarantee |
| Custom PDF-template export | No: PDF imports and completed work exports as Word | – |
| Portal questions enter a governed project and answers return beside the portal | Yes | Partial: Chrome extension published; retained project record is not documented |
_A dash means the capability is not clearly documented or the row does not apply._
That scale is live customer work, not a brochure ceiling. A verified
[G2 reviewer](https://www.g2.com/products/autorfp-ai/reviews#reviews:~:text=This%20really%20is%20a%20brilliant%20time%2Dsaving%20tool.%20It%27s%20very%20clever%2C%20and%20the%20range%20of%20answer%20types%2C%20criteria%20and%20scenarios%20it%20handles%20is%20impressive%2C%20as%20well%20as%20highly%20configurable%2C%20by%20RFP.)
calls "the range of answer types, criteria and scenarios it handles" impressive and highly
configurable by RFP. Another reviewer describes completing three RFPs, including
[one with 500 questions](https://www.g2.com/products/autorfp-ai/reviews/autorfp-ai-review-11669194).
[David F., Head of Sales](https://www.g2.com/products/autorfp-ai/reviews), says it takes a "dirty
Excel file" and converts it into highly accurate answers. A further verified reviewer reports four
"extremely disparate questionnaires" in one month and says AutoRFP.ai "seamlessly centralizes all
review and approvals." [IMTC processed questionnaires with up to 900
questions](/customer-stories/imtc-conquers-complex-rfps-with-ai-rfp-software), using Excel, Word,
and PDF imports. [SugarAI handles security questionnaires with up to 2,000
questions](/customer-stories/sugarai-answers-2000-question-security-questionnaires-with-one-fte)
and values the review process for keeping responses aligned before submission.
The file test should include a macro-enabled workbook, formulas, dropdowns, nested sheets, a Word
table, and one ambiguous answer column. Compare the returned files cell by cell and inspect the
record retained from the portal workflow.
## Answer architecture and review burden
Steerlab's [features page](https://www.steerlab.ai/features) says the product auto-generates more
than 80% of a document with sourced answers. Its security-team page says each answer receives a
confidence score and unsupported questions are identified. The product also publishes linked
source documents on its Responsive comparison page.
Those claims establish a credible source-and-review architecture. They do not explain what the
confidence score measures, how it is calibrated, or the threshold that sends a response to a
person. The public pages also stop at linked source documents on the answer. They do not describe
a citation on each sentence, a quoted passage behind each claim, or a named person on the source.
AutoRFP.ai uses two separate checks because source support and answer completeness are different
problems:
- **Trust Score** measures how strongly the best matching approved source supports the draft and
exposes how the answer was produced.
- **Feedback Score** evaluates whether the response is complete, relevant, clear, and appropriately
detailed for the requirement.
- **No Search Results** marks an unsupported question at zero trust so a person takes over.
Citations are finer than a document link on the whole answer. After drafting, an attribution pass
pins each sentence to the quoted passage that supports it, the named file or connected system it
came from, and the person associated with that source. Reviewers verify a claim against a quote
and a name, not a filename. Claims without backing stay marked unsupported rather than borrowing a
source they did not use.
Zero hallucination by design: AutoRFP.ai drafts from approved content, cites the sentences it used
back to those sources and people, scores the source support, and routes anything it cannot support
to a person. Reviewers can sort by the evidence that needs attention instead of reading every
answer with the same level of suspicion.
### Content Architecture: AutoRFP.ai compared with Steerlab
How sources, approved answers, conflicts, citations, and shared-library changes are governed.
| Capability | AutoRFP.ai | Steerlab |
| --- | --- | --- |
| Source citations reviewers can inspect | Yes: Quoted sentences, named files, named people | Yes: Linked documents and a confidence score on each answer |
| Connected knowledge sources stay synchronized | Yes | Yes: Drive, SharePoint, OneDrive, Box, Confluence, and Notion |
| Human-approved answers override conflicting content | Yes | – |
| Automatic conflict resolution | Yes | Yes: Vendor says the library removes duplicates and conflicts |
| Self-cleansing library that learns from approved answers | Yes | Partial: Auto-classifies, deduplicates, and flags stale content |
| Shared-library changes pass through owner review | Yes | Partial: Human review is central; owner gate for shared changes is not public |
_A dash means the capability is not clearly documented or the row does not apply._
### What to test
Create a small evidence set with two deliberate traps:
1. Put different data-retention periods in two approved files.
2. Ask for a certification that neither file supports.
For every output, save the answer, each cited sentence, the named source and person, the score
explanation, and the routing decision. Then ask a subject-matter expert whether the product made
uncertainty easier to locate.
## Security and enterprise controls
[Steerlab's primary security page](https://www.steerlab.ai/security) publishes:
- SOC 2 assessed across the five Trust Services Criteria, without identifying the report type
- AES-256 encryption at rest and TLS 1.2 in transit
- explicit tenant isolation and European AWS data storage
- customer-enforced MFA, SSO, and roles including Admin, Contributor, and Proposal Manager
- multi-availability-zone deployment, infrastructure as code, monitoring, and vulnerability
scanning
This is a credible public security baseline. The same page does not state ISO 27001, SCIM, or
regional hosting outside Europe. European AWS storage is an EMEA fact, not Americas or APAC
coverage. Some newer Steerlab-authored buyer guides claim ISO 27001, so the correct procurement
step is to request the current certificate, legal entity, scope, and applicability statement.
AutoRFP.ai publishes ISO 27001:2022 and SOC 2 Type II through a self-service
[Trust Center](/trust), plus a public [subprocessor register](/trust/subprocessors). Production
runs in separate US, EU, and APAC deployments. Identity lifecycle includes SSO and SCIM through
Okta or Microsoft Entra. Team-exclusive collections and organization-scoped retrieval apply
permission boundaries to both users and AI.
### Information Security: AutoRFP.ai compared with Steerlab
What InfoSec and IT will check: identity lifecycle, permissions, auditability, certifications, and grounding.
| Capability | AutoRFP.ai | Steerlab |
| --- | --- | --- |
| Zero hallucination by design (100% source-grounded answers) | Yes | Partial: Sourced answers, confidence scores, and unsupported-answer handling |
| Enterprise Permissions | Yes | Yes: Admin, Contributor, and Proposal Manager roles |
| Single sign-on (SSO) | Yes | Yes: Okta, Google SSO, Auth0, and Microsoft Entra ID |
| Okta SSO | Yes | Yes |
| SCIM provisioning and deprovisioning | Yes: Okta and Microsoft Entra | No: No public SCIM documentation |
| Enterprise administrative audit trail | Yes | Partial: Version control published; administrative audit export is not |
| SOC 2 Type II certified | Yes | Yes: Primary security page says SOC 2; report type is not stated |
| ISO 27001 certified | Yes | Partial: Claimed in vendor content, absent from the primary security page |
_A dash means the capability is not clearly documented or the row does not apply._
Ask both vendors for current audit reports, certification scope, model-provider terms, data-flow
diagrams, deletion behavior, a SCIM demonstration, and a sample administrative audit export.
## Public legal terms
[Steerlab's Legal Terms](https://www.steerlab.ai/terms-and-conditions), last updated June 19, 2026,
are the public contract for "access to and use of the Services." A signed order form may replace
them. That replacement is not published. The clauses below are quoted from that page.
**Regulated-industry use is restricted.** Section 1 states: "The Services are not tailored to
comply with industry-specific regulations (Health Insurance Portability and Accountability Act
(HIPAA), Federal Information Security Management Act (FISMA), etc.), so if your interactions would
be subjected to such laws, you may not use the Services. You may not use the Services in a way
that would violate the Gramm-Leach-Bliley Act (GLBA)." Ask whether a later contract carves that
restriction out before sending healthcare, US federal, or GLBA-covered questionnaires through the
product.
**The product is provided as-is, with no published uptime or support obligation.** Section 16
provides the Services "ON AN AS-IS AND AS-AVAILABLE BASIS" and disclaims warranties of
merchantability, fitness for a particular purpose, and non-infringement. Section 12 says Steerlab
has "no liability whatsoever for any loss, damage, or inconvenience caused by your inability to
access or use the Services during any downtime," and that nothing in the terms "will be construed
to obligate us to maintain and support the Services." A public SLA URL was not found.
**The vendor can change the deal, or end it, without notice.** The opening agreement says Steerlab
may modify the Legal Terms and "you waive any right to receive specific notice of each such
change," with continued use treated as acceptance. Section 11 reserves the right, "IN OUR SOLE
DISCRETION AND WITHOUT NOTICE OR LIABILITY," to deny access "FOR ANY REASON OR FOR NO REASON" and
to "DELETE YOUR ACCOUNT AND ANY CONTENT OR INFORMATION THAT YOU POSTED AT ANY TIME, WITHOUT
WARNING."
**Liability and data-loss risk sit with the customer.** Section 17 disclaims "ANY DIRECT, INDIRECT,
CONSEQUENTIAL, EXEMPLARY, INCIDENTAL, SPECIAL, OR PUNITIVE DAMAGES, INCLUDING LOST PROFIT, LOST
REVENUE, LOSS OF DATA," then caps remaining liability at "THE AMOUNT PAID, IF ANY, BY YOU TO US
DURING THE six (6) month PERIOD PRIOR TO ANY CAUSE OF ACTION ARISING." Section 19 says the customer
is "solely responsible for all data" transmitted through the Services and that Steerlab "shall have
no liability to you for any loss or corruption of any such data."
**Customer content is not carved out as confidential Customer Data.** Section 7 says any
Contributions "may be treated as non-confidential and non-proprietary." Section 8 grants Steerlab
an "unrestricted, unlimited, irrevocable, perpetual" license to "disclose, sell, resell, publish"
those Contributions, including company name and logos. The terms do not define a Customer Data
category that excludes uploaded questionnaires and answer libraries from that license. Ask for a
written Customer Data ownership and confidentiality clause before loading production files.
**Privacy names AI subprocessors, and there is no public DPA.** The
[privacy notice](https://www.steerlab.ai/privacy-policy) (also June 19, 2026) says Steerlab does
"not process sensitive personal information," and that "your input, output, and personal
information will be shared with and processed by" Anthropic, OpenAI, Mistral AI, and Cohere. The
site sitemap lists the terms and privacy pages. `/dpa`, `/legal/dpa`, `/data-processing-agreement`,
and `/msa` returned HTTP 404 on August 27, 2026. Steerlab's own
[GDPR guide](https://www.steerlab.ai/blog/what-is-gdpr-compliance) says a SaaS vendor acting as a
processor "must sign a Data Processing Agreement with each customer."
AutoRFP.ai publishes a [Master Services Agreement](/legal/msa), [Data Processing Agreement](/legal/dpa),
[Service Level Agreement](/legal/sla), and [security exhibit](/legal/security). The MSA states that
the customer exclusively owns Customer Data and Outputs, grants only a limited license to host that
data to provide the Services, and will not use Customer Data to train AutoRFP.ai or third-party
models except tenant-specific models for that customer. It does not contain a HIPAA, FISMA, or GLBA
use prohibition. The SLA commits to 99.95% monthly uptime with defined response targets. Confirm
sector-specific addenda (including any BAA) in the order form on both sides.
## Integrations: compare the job, not the logo
Both products connect the same core knowledge, CRM, and collaboration stack. Counted from each
vendor's own public directory on August 26, 2026, AutoRFP.ai publishes 32 entries against
Steerlab's 17, about 1.9 times as many, and the gap widens on what those connections actually do.
### Integrations: AutoRFP.ai compared with Steerlab
AutoRFP.ai publishes 32 integration directory entries against 17 from Steerlab, 1.9x as many, counted from each vendor's public integration directory on August 26, 2026.
| Connection type | AutoRFP.ai | Steerlab |
| --- | --- | --- |
| **Breadth: by category** | | |
| CRM | 4 | 3 |
| Knowledge, storage, help center, revenue intelligence | 13 | 7 |
| Communication | 3 | 2 |
| Identity and SSO | 4 | 4 |
| Browser and AI assistant | 6 | 1 |
| Named procurement or security portals | 2 | None listed |
| **Depth: what the connection does** | | |
| Documented behavior per connection | Yes | No: Systems named only |
| CRM status write-back | Yes | No |
| API | Yes | No |
| Webhooks | Yes | No |
| Model Context Protocol | Yes: Server and client | No |
Breadth is the easier half of that table to close. Depth is the part a buyer feels in month three:
whether the CRM connection writes status back to the opportunity, whether an integration can be
driven programmatically, and whether an assistant can reach governed content at all. The AutoRFP.ai
[integration directory](/integrations) documents the job each connection performs. Salesforce
carries intake, owner mapping, live opportunity status, and status write-back. API and webhooks
cover custom workflows. The MCP layer works in both directions: assistants can query governed
AutoRFP.ai knowledge, and AutoRFP.ai can pull permitted context from external MCP servers.
Steerlab's directory names its systems without publishing API, webhook, or MCP documentation, so
the connection behavior has to be confirmed in a demo.
Those 17 Steerlab entries are still a real stack, and worth conceding plainly. Its
[integration directory](https://www.steerlab.ai/integrations) names Google Drive, SharePoint,
OneDrive, Dropbox, Box, Slack, Microsoft Teams, HubSpot, Dynamics 365, Salesforce, Chrome,
Confluence, Notion, Okta, Google SSO, Auth0, and Microsoft Entra ID.
No directory proves depth on its own, on either side. A
[G2 review dated June 3, 2026](https://aws.amazon.com/marketplace/reviews/reviews-list/prodview-dzqypcxo2svgq)
asks Steerlab for "stronger native integration with some of the smaller consumer service CRMs we
use." Another review dated April 24 says CRM sync was quick and helped sales and engineering
collaborate, so the CRM connectivity works. Run both products against your own fields, triggers,
owner mapping, status write-back, and least common system, then keep the connection that survives
the test rather than the one with the better logo wall.
## Collaboration, approvals, and shared content
Steerlab publishes contributors, comments, task assignments, review flows, version control,
progress tracking, and bottleneck visibility. Its Responsive comparison page also says the content
library classifies material, removes duplicates and conflicts, flags outdated responses, and
learns from completed submissions.
That is substantial workflow coverage. The public material does not show ordered approval stages,
a separate content-owner gate before edited text becomes authoritative across the organization, or
the administrative audit export an enterprise buyer can inspect. Buyers should ask Steerlab to
demonstrate those controls instead of interpreting documentation silence as product absence.
AutoRFP.ai supports multiple reviewers and sequential approval layers. Shared-library changes can
pass through a content owner, confidential projects stay outside reusable content, and locked
responses remain protected from agent edits. Version history and the response record show who
changed, reviewed, approved, and exported the answer.
### Collaboration Scale: AutoRFP.ai compared with Steerlab
Who can contribute, how many people can review, and what must happen before content is approved.
| Capability | AutoRFP.ai | Steerlab |
| --- | --- | --- |
| Unlimited collaborator users (no per-seat fees) | Yes: Live co-editing, comments, and assignments | – |
| Multiple reviewers on one answer | Yes: Any or all reviewers can be required | Yes: Contributors, assignments, comments, and review flows |
| Sequential approval layers | Yes: Ordered review stages and locks | Partial: Review flows are published; ordered approval layers are not |
| Approval-gated saves to shared content | Yes | – |
| Answer edit history and restoration | Yes | Yes: Vendor comparison page publishes version control |
| Slack | Yes | Yes |
| Microsoft Teams | Yes | Yes |
_A dash means the capability is not clearly documented or the row does not apply._
For the pilot, model the real sign-off chain. Include a proposal owner, a security reviewer, legal,
and an executive approver. Then remove one reviewer from the identity provider and verify what
happens to access and outstanding work.
## Reporting and deal insights
Steerlab's distinct reporting angle is deal strategy. The features page publishes data-backed win
probability and competitor-bias detection. Its presales page adds a Go/No-Go agent. The Responsive
comparison page names inconsistencies, response gaps, bias and risk, win/loss patterns, progress,
contributors, and bottlenecks.
The public pages do not define the methodology behind win probability or competitor-bias
detection, and they do not show the output of an operations report. A
[G2 review dated June 2, 2026](https://aws.amazon.com/marketplace/pp/prodview-dzqypcxo2svgq)
says, "A few more integration choices and better reporting would make it even stronger for larger
proposal teams." Another review dated May 30 says "the reporting side still has room to grow."
Both reviews also praise the AI assistance, organization, and ease of use.
AutoRFP.ai's reporting covers projects, workload, automation, compliance gaps, and scheduled
delivery. At approval, the platform word-diffs the final answer against its draft so the automation
rate has a defined method. The ROI model exposes the buyer's own assumptions, and reports export
to CSV, Excel, and PDF.
### Reporting & Insights: AutoRFP.ai compared with Steerlab
What a bid lead can see across the queue: automation, workload, win/gap analysis, and enterprise reporting.
| Capability | AutoRFP.ai | Steerlab |
| --- | --- | --- |
| Enterprise Reporting | Yes | Partial: Deal insights published; operational reporting depth is not detailed |
| Workload Reporting | Yes | Partial: Tracks contributors, sections, progress, and bottlenecks |
| Win/Gap Analysis Reporting | Yes | Yes: Go/No-Go, competitor bias, gaps, and win/loss analysis |
_A dash means the capability is not clearly documented or the row does not apply._
Steerlab may be the better starting point when a security team prioritizes a lighter workflow and
Go/No-Go insights. AutoRFP.ai is the stronger documented fit when leadership needs capacity,
automation, compliance-gap, and savings reporting across a sustained response operation.
## Pricing and commercial fit
Steerlab's first RFP or questionnaire is free, which is a genuine way to see output on a real
document before any commercial conversation.
Paid pricing is quote-based. The AWS Marketplace listing uses private offers, displays a placeholder
price, and says pricing scales with purchased Units. It does not define whether a Unit means a
seat, workspace, response, or another measure. Public sources also leave paid usage limits,
overage behavior, and renewal terms unspecified.
Support tiers belong in the same quote. The listing says Steerlab provides "various tiers of support
levels from basic support through email ... all the way to 24x7 premium support with an assigned
customer success manager." That sentence sits in the vendor-authored support section, on a page
where AWS states that "vendors are responsible for their product descriptions and other product
content" and that it does not warrant them. Staffed hours, response targets, escalation paths, and
regional cover are not published anywhere public. [Steerlab's about
page](https://www.steerlab.ai/about) says the company is based in Paris. [Tracxn's company
profile](https://tracxn.com/d/companies/steerlab/__-hS08LWxWadSgIZA1hAo7QjMfbJmdb_1iOygwddxnN4)
lists 14 employees as of July 31, 2026 at that Paris-based company, and the about page does not
list another office. Reviewers do praise responsiveness: a
[G2 review dated June 3, 2026](https://aws.amazon.com/marketplace/reviews/reviews-list/prodview-dzqypcxo2svgq)
says "the support team is quick to respond whenever you flag something." Treat 24x7 and global
cover as questions rather than published features. Ask which hours are staffed, from which
cities, against what response targets, and put the answer in the agreement instead of the listing.
AutoRFP.ai publishes [Scale at $899 per month and Accelerate at $1,299 per month](/pricing), billed
annually with unlimited users. The plans use annual project allowances, which accommodates an
uneven response year.
The evaluation is also free, and it covers more ground. A two-week proof of concept opens the full
platform with no usage cap, connects your own content sources, and includes implementation support
while your team runs live work through it. Reviewers, approvers, and security stakeholders all
participate, because users are never metered.
Ask Steerlab to price the real team and response pattern. Include a quiet month, a burst of
simultaneous questionnaires, external reviewers, premium support, and renewal. Compare that
written proposal with AutoRFP.ai's annual allowance and included-user model.
## Company evidence and implementation
Steerlab is a newer, smaller vendor in this category. [Its about
page](https://www.steerlab.ai/about) says it was founded in 2023 and is based in Paris, led by
founders Rami Iguerwane and Othmane Hamzaoui. It
[announced a $1.9 million pre-seed round](https://www.steerlab.ai/blog/steerlab-secures-eu1-7-million-to-empower-presales-teams-to-win-more-deals-with-ai)
in September 2024. [Tracxn's company
profile](https://tracxn.com/d/companies/steerlab/__-hS08LWxWadSgIZA1hAo7QjMfbJmdb_1iOygwddxnN4)
lists 14 employees as of July 31, 2026 at the Paris-based company. The about page names Paris
leadership and does not publish other offices, so Americas or Asia-Pacific staffed coverage is not
a public fact. Its public site shows customer logos and short testimonials, but no full
case-study library was found as of August 26, 2026. AWS Marketplace surfaced a
**4.6 rating from 56 G2 reviews**. Those reviews praise traceable sources, quick adoption, and
support, while dated comments ask for better reporting, more flexible dashboard exports, stronger
native support for smaller CRMs, and more reliable structured-template formatting.
AutoRFP.ai publishes full customer stories, a **4.9 G2 rating from 60 reviews**, and teams in New
York, Vancouver, Stockholm, and Brisbane, covering support across North America, Europe, and
Asia-Pacific. Its security evidence is self-service through a public Trust Center. For a
mid-market or enterprise buyer, that record is easier to inspect before loading sensitive response
content into a proof of concept.
### Implementation & Support: AutoRFP.ai compared with Steerlab
Published support hours and data hosting for the Americas, EMEA, and APAC.
| Capability | AutoRFP.ai | Steerlab |
| --- | --- | --- |
| Dedicated support team (24/6) | Yes | Partial: 14 Paris-based staff; no published global coverage window |
| Data hosting and support (Americas) | Yes: Separate US deployment | No: No Americas region published |
| Data hosting and support (EMEA) | Yes: Separate EU deployment | Yes: European AWS storage; Paris-based support |
| Data hosting and support (APAC) | Yes: Separate Australia deployment | No: No APAC region published |
_A dash means the capability is not clearly documented or the row does not apply._
## Is Steerlab's AutoRFP.ai comparison still accurate?
Steerlab's
[comparison page dated November 5, 2024](https://www.steerlab.ai/blog/choosing-the-right-rfp-software-solution)
remains live without an update date. It makes five claims about AutoRFP.ai. Every one conflicts
with the current public product record, customer evidence, or both. That does not establish what
was available on the day the page was published. It does mean the page is not a reliable
description of the product a buyer can evaluate now.
| Area | What Steerlab's page says about AutoRFP.ai | Current public record |
| ------------------ | ----------------------------------------------------------------------------------------------- | -------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| Complex RFPs | "Specializes in quick turnaround for standard RFPs but may struggle with complex requirements." | AutoRFP.ai publishes support for 5,000+ requirements, 500+ page Word files, multi-tab Excel, nested tables, hidden tabs, macros, dropdown validation, compliance matrices, multiple files, and ZIP archives. Steerlab publishes no comparable document-size ceiling. Customer evidence is in the files section above. |
| Content management | "Limited in content management functionality, making it more suitable for one-off proposals." | AutoRFP.ai has a dedicated [Content Management](/features/content-management) area with semantic search, connected-source sync, auto-categorization, ownership, moderation and approvals, renewal and expiry schedules, freshness alerts, and an audit trail. Every approved response can feed future work. |
| Collaboration | "Collaboration tools are limited, making it less ideal for complex projects." | [Collaboration](/features/collaboration) includes unlimited users, live co-editing, assignments, requirement-level comments, Slack, Teams, and email alerts, workload and deadline tracking, version and approval history, any, all, and sequential review processes, plus response and export locks. |
| Integrations | "Offers minimal integration options, limiting its utility for larger organizations." | The current public directories list 32 AutoRFP.ai entries against 17 from Steerlab. AutoRFP.ai also publishes an API, webhooks, CRM status write-back, and MCP server and client behavior. The detailed count and depth comparison appears in the integrations section above. |
| Data security | "Limited security features make it less ideal for handling sensitive data." | AutoRFP.ai publishes ISO 27001:2022, SOC 2 Type II, separate US, EU, and APAC deployments, SSO, SCIM, role and collection permissions, tenant isolation, a self-service [Trust Center](/trust), a public [subprocessor register](/trust/subprocessors), audit controls, and a contractual commitment that customer content is not used to train public models. |
The integrations line is the easiest to check in public sources. A
[capture of Steerlab's own directory](https://web.archive.org/web/20241112185503/https://www.steerlab.ai/integrations)
from November 12, 2024, one week after that page went up, shows the same 17 connectors it carries
today. The AutoRFP.ai [integration directory](/integrations) carries 32, among them SharePoint,
Google Drive, OneDrive, Box, Confluence, Notion, Seismic, Zendesk, Intercom, Salesforce, Slack,
Microsoft Teams, Okta, Microsoft Entra, Google Workspace, Gong, and an official MCP server.
Use the current product pages and a live proof of concept, not that 2024 comparison page, as the
record of what each platform does now.
## Final decision
Start with Steerlab when a security team wants a lighter product for sourced questionnaire drafts,
confidence-guided review, and one free document. Its public evidence does not make it the stronger
choice for a mid-market or enterprise response operation with layered governance, broad
integration requirements, exact-format file return, and management reporting.
Start with AutoRFP.ai when the response process needs inspectable quality controls and enterprise
governance across RFPs, security questionnaires, and DDQs. Sentence-level citations name the
source and the person, two scores focus review, unsupported questions route to a person, and work
continues through sequential approval, exact-format return, identity lifecycle, integrations, and
operations reporting.
We'd rather show you than tell you: bring a real fortnight of response work, your own sources,
reviewers, and approval policy. The AutoRFP.ai proof of concept covers the whole platform for two
weeks at no cost and with our team supporting the run, so the artifacts you keep at the end are
drafts, cited sentences, named sources and people, score explanations, review history, audit
records, and returned files from your actual workload.