# AutoRFP.ai vs Inventive AI: Which Platform Fits Your RFP Workload? AutoRFP.ai vs Inventive AI compared by published workload, workflow, security, and pricing. Match the product to the queue you actually run. AutoRFP.ai vs Inventive AI is the head-to-head for buyers matching a product to the response workload they actually run. Inventive.ai is the product site for Inventive AI. Founding Story comes first: who built each company, who it answers to, and where the team sits. The tables then group published facts by response volume, collaboration scale, capabilities, and information security. Later sections take those facts into response accuracy, reporting and insights, and implementation and support. The same slice tables also live on the [AutoRFP.ai vs Inventive AI landing page](/alternatives/inventive). Sources are public product, pricing, and security pages; Inventive's G2 page as of August 17, 2026; dated Inventive homepage captures from August 17, 2026; and Y Combinator's Inventive AI company and Launch YC pages, retrieved August 17, 2026. AutoRFP.ai facts link to the [Trust Center](/trust) and [pricing](/pricing) pages. ## Founding Story Company history is how each product was built, who it answers to, and how wide the operating team is. AutoRFP.ai first, then Inventive AI. ### AutoRFP.ai Jasper Cooper is Co-founder and CEO. Before AutoRFP.ai he led a global enterprise sales team and ran the RFP cycle himself: more than 500 RFPs, including a first million-dollar win at 19, and contracts with large brands from Starbucks to state governments. Years inside Loopio made the library-upkeep problem concrete. Before ChatGPT was a household name, he came across OpenAI's early language models. The first AutoRFP script followed in 2022, with Louis Lloyd-Besson as Co-founder and CTO. AutoRFP.ai is bootstrapped from day one and has no venture-capital investors. The roadmap is shaped by customers. The company shipped early AI responses in this category and later the [first MCP server built for RFP, DDQ, and security-questionnaire teams](/blog/autorfp-mcp-server-launch). The team now works from New York, Vancouver, Stockholm, and Brisbane, covering the US, Canada, Sweden, and Australia. AutoRFP.ai is used by Fortune 500 response teams. The longer founder letter lives on the company page. ### Inventive AI [Y Combinator's company page](https://www.ycombinator.com/companies/inventive-ai) lists Inventive AI as founded in 2023 in the Summer 2023 batch. Y Combinator describes the company as "Built by a customer-obsessed team comprising an ex-exec from a Fortune 500 company and ex-AI team from Google & Stanford." The [Launch YC post](https://www.ycombinator.com/launches/JBU-inventive-ai-automate-responses-to-sales-information-requests-with-ai) says Dhiren Bhatia previously founded and led Viewics (acquired by Roche), and that Gaurav Nemade was a product manager at Google AI and Google Brain. In 2024, [Y Combinator announced](https://www.linkedin.com/posts/y-combinator_inventive-ai-yc-s23-has-raised-4m-in-seed-activity-7241506126452682755-AfKD) that Inventive AI (YC S23) raised $4M in seed funding. That funded start, and the Google product background, is a genuine strength for a young company. Inventive remains a lean team spanning the US and India. Y Combinator lists the company in the San Francisco Bay Area. ## Response Volume A few questionnaires a year can live with a product manager, sales engineer, or operations lead who already has another job. Inventive does not publish a typical quarterly volume. [MaxVal](https://www.inventive.ai/case-studies/best-rfp-software--90-faster-rfps-0-weekend-hours-lost) is written as handling 10-15+ RFPs and security questionnaires per quarter. [AssetWorks](https://www.inventive.ai/case-studies/how-assetworks-facilities-achieved-422-roi-on-rfp-automation-with-inventive-ai) responds to roughly 30 RFPs per year. Insider and RAD AI do not publish a count. This slice checks whether the product is sized for those published loads, or for a live queue that keeps arriving while last week's workbook is still in review. Library upkeep shows up as the pile grows: - **Occasional work** can finish the current questionnaire and stop. - **A live queue** needs approved answers to flow back into the library before the next file arrives. Inventive's [features page](https://www.inventive.ai/features) still marks its self-updating knowledge base as Beta as of August 17, 2026. Capacity, automation, and management reporting sit in Reporting & Insights. Line up your published volume with the first rows, then read the rest of this page as the operating layer that volume creates. ## Collaboration Scale The next cut is who has to sit inside the product. A side-task questionnaire can stay with the people already in the thread. A dedicated response function still needs every reviewer in the same system. Reviewers also need a path from Slack and Microsoft Teams when that is where the request already lives. Inventive's [pricing page](https://www.inventive.ai/inventive-ai-pricing) includes unlimited users, which is a genuine fit when the circle is small and everyone already shares an office. Coverage hours, support team, and regional hosting are compared under Implementation & Support. ## Capabilities Compared This slice is what the product actually does on a file: whether it is AI-native, whether it translates, how conflicting sources are handled, and whether a price is listed. Inventive is a fair pick when the job is a handful of questionnaires and a generated draft will finish the current file. AutoRFP.ai publishes translation across 44+ languages and public Scale and Accelerate plans on the [pricing](/pricing) page. Inventive's [pricing page](https://www.inventive.ai/inventive-ai-pricing) starts at $10,000 per year; the per-project usage rate is not listed. Use this table for what each vendor documents on the file itself, before you get to InfoSec. ## Information Security InfoSec will ask what is certified, who can see which answers, and whether drafts are grounded in approved content. This slice is that checklist. Inventive's [security page](https://www.inventive.ai/security) publishes SOC 2 Type II, SAML, and general user roles. That package can clear a light questionnaire. AutoRFP.ai's [Trust Center](/trust) adds ISO 27001:2022, regional hosting, SCIM, and a public subprocessor register. Zero hallucination by design: AutoRFP.ai writes only from approved content, cites the sources on each answer, and routes anything it cannot support to a person. Take this table into the security review. The [Trust Center](/trust) is the downloadable packet behind the rows: - **ISO 27001:2022** and **SOC 2 Type II** - **GDPR** controls and regional hosting (US, EU, AU) - Security documents and a public [subprocessor register](/trust/subprocessors) - **SCIM, SSO, SAML**, and permission boundaries that apply to both users and retrieval The Trust Center states that model services run through Azure, Google, and AWS under enterprise controls. Customer content is not used to train shared models. Inventive's [security page](https://www.inventive.ai/security) names OpenAI and Anthropic as model providers. Its ISO 27001 statement describes the cloud providers that host the infrastructure. Those named providers have published their own incident posts. OpenAI's [March 20, 2023 ChatGPT outage post](https://openai.com/index/march-20-chatgpt-outage/) reported that a bug allowed some users to see titles from another active user's chat history, and that the same bug may have made payment-related information of some ChatGPT Plus subscribers visible. On July 21, 2026, [OpenAI reported](https://openai.com/index/hugging-face-model-evaluation-security-incident/) that models in a sandboxed testing environment obtained open internet access and reached Hugging Face production infrastructure. Anthropic's [July 30, 2026 review](https://www.anthropic.com/news/investigating-incidents-cybersecurity-evals) reported three incidents in which a Claude model reached the internet from an evaluation environment and gained unauthorized access to the real systems of three organizations. ## Response Workflow **Intake, review, and return** stay in one project: - **Salesforce** opens the opportunity and the response project together. - **Assignments, comments, sequential reviews, and approvals** stay on the record. - **Slack and Microsoft Teams** carry review requests without moving the source of truth into chat. - **Exact-format export** writes approved answers back into the issuer's Excel or Word file, including nested sheets, formulas, macros, and validation lists. - **Portal Agent** handles questionnaires that arrive through procurement and security portals. ### Intake from Salesforce When Salesforce opens an opportunity, the response project opens with it. Audit history stays on the record, and response work starts on one path. **Knowledge stays governed** after the draft: - Connected content remains in SharePoint, Google Drive, OneDrive, Box, Confluence, Notion, Zendesk, and other approved sources. The [integration directory](/integrations) explains the job each connector performs. - **MCP** extends the same permission-aware layer to Claude, ChatGPT, Microsoft Copilot, and Gemini, so the team does not paste source documents into a separate chat. ## Response Accuracy Buyers comparing accuracy claims need a published method, a denominator, and a way to find the answers the system cannot support. Inventive's homepage publishes a 95% accuracy headline alongside an absolute outcome claim. Ninety-five percent accurate means about 5% inaccurate. Both positions appear in the same homepage block. The dated captures below quote that page as it stood on August 17, 2026. ![Inventive homepage block stating 95% accuracy and an absolute hallucination claim](~/assets/images/blog/inventive-accuracy-homepage-claim.png) The FAQ on the same homepage gives two accuracy figures in one answer. It says "over 95% accuracy," then "over 90% accuracy." The answer also says the AI will not generate a fabricated response when content is missing and will flag the gap. ![Inventive homepage FAQ stating over 95% accuracy and over 90% accuracy](~/assets/images/blog/inventive-accuracy-faq-conflicting-percentages.png) Zero hallucination by design: AutoRFP.ai writes from approved content, shows the source passage and Trust Score, and withholds the draft when evidence is missing. The question is marked No Search Results at zero trust and routed to a person. ## Reporting & Insights Once someone owns the queue, they need a view of capacity, automation, and recurring gaps. A list of generated drafts does not plan the year or explain the operation to management. This section collects what each vendor publishes about that operating layer. **Reporting** is how a queue becomes manageable: - AutoRFP.ai reports **automation rate** from the actual answer history. - It shows **workload**, project performance, modeled ROI, and recurring compliance gaps. - The ROI model exposes the assumptions behind its savings estimate. - **Scheduled reports** take the results to management. Inventive's [G2 page](https://www.g2.com/products/inventive-ai/reviews), as of August 17, 2026, lists Insufficient Analytics (22), Poor Reporting (18), and Access Management (4) among its cons tags. Those categories appear when response work becomes a managed function. **Go/no-go and gap analysis** belong in the same operating layer: - AutoRFP.ai screens an incoming RFP against the team's own criteria before drafting begins. - Each result keeps its source. - The analysis exports for approvers. - **Gap Analysis** then shows which requirements keep causing trouble across completed work. ## Implementation & Support After the first file, a dedicated team still has to get live and stay covered: onboarding locations, support hours, and regional hosting. The table is the published coverage. The notes after it are the implementation facts each vendor puts on its own site. - AutoRFP.ai supports implementation from **Stockholm, Vancouver, New York, and Brisbane**. - Customers span Silicon Valley and Wall Street, including one of the world's top three fintechs, several of the top twenty private equity funds, and Fortune 500 response teams. - The product team has shipped Trust Score, gap analysis, configurable go/no-go, exact-format export, and MCP. Identity and assistant access use the same permission boundaries: SCIM provisioning and MCP answers stay inside the project. ## High Compliance Response Environments - **Fintech.** Questionnaires sent by banks and processors create representations about the business. [FintechOS](/customer-stories/how-fintechos-achieved-60-efficiency-gains-with-ai-rfp-automation) Bid Manager Mihai Popa reports that AutoRFP.ai cut the time allocated to responses by 60%. Inventive does not publish a named fintech case study. - **Healthtech.** [Cubiko](/customer-stories/how-cubiko-slashed-security-questionnaire-response-time-by-85-with-ai-rfp-software) Head of Sales and Marketing Bryn Tardent-Powell moved a security questionnaire from one week to one hour. [MedeAnalytics](/customer-stories/medeanalytics-transforms-healthcare-rfp-chaos-into-streamlined-success-with-rfp-software) used AutoRFP.ai to answer 75% of a security questionnaire containing more than 1,000 questions. Inventive's named healthcare case is RAD AI. - **DDQ.** Teams face the same standard across [ILPA](/blog/ilpa-ddq) and [AIMA](/blog/aima-ddq) questionnaires. They need the original Excel workbook returned, and an unsupported control must stay unanswered until a person provides evidence. ## Compare the commercial models against the queue [Inventive AI pricing](https://www.inventive.ai/inventive-ai-pricing) starts at $10,000 per year. A platform fee covers setup and product access, usage charges scale with RFP and security-questionnaire volume, unlimited users are included, and unused credits roll over. The per-project usage rate is not public. [AutoRFP.ai pricing](/pricing) is public. Scale is $899 per month, Accelerate is $1,299 per month, and Enterprise is custom. Plans are paid yearly and include unlimited users. The [Inventive AI pricing guide](/blog/inventive-ai-pricing) covers the detailed commercial comparison. ## Test the platform on a live questionnaire Use the same knowledge and one live questionnaire: - **Plant conflicting values** for a control. - **Ask a question that has no source** and require the product to withhold the answer. - **Export** the completed work into the issuer's original Excel file. Those three artifacts test conflict handling, abstention, and submission fidelity. If you need a worksheet for the evaluation, use the [Go/No-Go decision template](/downloads/go-no-go-decision-template-for-rfps). ## The buyer cut Published Inventive volumes are MaxVal's 10-15+ questionnaires a quarter and AssetWorks' roughly 30 RFPs a year. AutoRFP.ai is the AI-native platform that passes compliance review, and the one a bid, proposal, or SE team runs when they own the queue. Book a demo and run one live questionnaire through a two-week proof of concept. Judge the artifacts on the live file. The [Inventive AI alternatives](/blog/inventive-ai-alternatives) guide covers the wider shortlist. For this decision, bring the real queue, the real access model, and the real files.