In today's fast-paced business environment, creating proposals and responding to Requests for Proposals (RFPs) efficiently and accurately is mission-critical for securing new clients and driving revenue. However, if your team is buried under spreadsheets, chasing SMEs for answers, or copy-pasting responses from old proposals, it might be time to bring in reinforcements. And the one question that’s often asked is this: Should we buy a ready-made AI proposal software solution, or build our own?
Key Considerations for Decision-Making
The Temptation to Build: Custom, but Costly
Why Proposal Teams Need More Than General AI
The Case for Buying: Purpose-Built, Ready-to-Run
Frequently Asked Questions: AI Proposal Software – Buy vs. Build
Should You Build or Buy Proposal Software? Final Verdict
Why buy? Buy for speed, scalability, and proven ROI.
Why build? Build only if your use case is highly unique.
Purpose-built tools like QorusDocs save time and win more deals.
Purchasing an AI proposal software solution involves acquiring a ready-made platform specifically designed to streamline the proposal proposal process. Think content recommendations, automated workflows, collaboration tools, analytics dashboards and integrations with your Microsoft 365 tools, CRM or knowledge base.
Instead of hunting down boilerplate content, AI surfaces the best, most relevant answers. Instead of manually formatting proposals, the system does it for you. Instead of starting from scratch, you build on a library of past successes. All of this frees up your team to focus on the strategic stuff: crafting a compelling story, aligning your pitch to the client’s needs, and submitting proposals that win.
Building an in-house AI proposal solution entails developing a custom platform tailored to an organization's specific needs and workflows. Rather than starting from scratch, many organizations investigate building with Microsoft Copilot to create their own proposal tool. However, the ‘build your own’ route requires assembling a team of developers, data scientists, and subject matter experts to design, implement, and maintain the software. The goal is to create a solution that aligns perfectly with internal processes and requirements.
When deciding between buying and building, organizations should evaluate several critical factors:
Functionality and Features
Buying: AI proposal software solutions often come with a comprehensive set of features, including templates, content management tools, collaboration tools, and integration with existing systems.
Building: Custom development allows for tailored features that align precisely with unique business processes. However, achieving parity with a purpose-built AI proposal software solution feature sets can be time-consuming and resource intensive.
Buying: Off-the-shelf AI proposal software solutions can be deployed relatively quickly, enabling organizations to realize benefits sooner, often weeks to a few months.
Buying: Buying often results in lower upfront costs and predictable ongoing expenses.
Building: Initial development costs can be substantial, and ongoing maintenance, updates, and support add to the total cost of ownership.
Scalability and Maintenance
Buying: Vendors handle scalability and regular updates, ensuring the software evolves with industry standards and technological advancements.
Building: The organization is responsible for scaling the solution and keeping it up-to-date, which requires dedicated resources and expertise.
Buying: Purpose-built solutions often offer integrations with popular tools like CRM systems, document management platforms, and communication tools. Some even will integrate with industry-specific use, such as legal software and professional services software.
Building: Custom integrations can be developed to fit specific needs but may require additional time and resources.
Data Security and Compliance
Buying: Reputable vendors adhere to industry-standard security protocols and compliance requirements.
Building: Developing an in-house solution allows for complete control over data security measures, which can be advantageous for organizations with stringent compliance needs.
Building your own AI proposal automation software can sound appealing. You get full control. You can tailor it to your exact needs. You can build around your existing tools.
But in practice? It’s usually more trouble than it’s worth.
Here’s why:
You’ll need developers, data scientists, UX designers, project managers—and that’s just to get started. Even a basic solution can require hundreds of thousands of dollars.
When everything goes smoothly, custom software projects often take months (or longer). And while your team is heads-down building, opportunities are slipping by.
Once you build it, you own it. That means bug fixes, updates, security patches, and AI model tuning are all your responsibility. And when those resources leave the company? So does your institutional knowledge.
The world of AI is changing fast. Can your internal team keep pace with the exponential advancements in natural language processing, data privacy requirements, or integration standards? A proposal software vendor lives and breathes this space. Most internal teams don’t have that luxury.
Every hour your team spends building a custom proposal tool is an hour they’re not spending on your core product, customers, or strategy. Is that really where you want your engineering firepower going?
When you're deciding between buy vs. build, ask yourself:
What are our specific requirements and goals for proposal and RFP management?
Will our build-your-own solution be able to support the various internal use cases required (sales and marketing, bid teams, subject matter experts, etc.)?
How quickly do we need a solution in place?
Do we have the resources to build and maintain a complex AI system?
Are we solving a problem that’s truly unique? Or are we trying to solve a common challenge with a custom tool?
What is our budget for initial development and ongoing maintenance?
For most teams, the answers point in one direction: buy.
General AI tools are great for everyday productivity tasks across the organization; however, they aren’t built for the high-stakes, specialized demands of business development.
While Microsoft Copilot is an excellent AI tool for general research and content creation, it wasn’t built with the specific needs of proposal or business development teams in mind. It lacks the specialization, content access, and professional services workflow support necessary for streamlining the response process within a professional services organization.
That’s where QorusDocs comes in— with an AI assistant and agents purpose-built to support the intricate, strategic work that drives revenue and growth. QorusDocs delivers focused expertise, tailored support, and results that matter. Let’s dig into the gaps in Microsoft Copilot and how QorusDocs closes them.
Think of Copilot as your reliable general assistant—versatile and useful in many scenarios. But when it's time to pursue new business or manage complex proposals and RFPs with precision and insight, you need a specialist. Say hello to QorusDocs, proposal automation driven by AI.
Gap in Microsoft Copilot |
How QorusDocs Closes It |
Business Impact |
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No dedicated, vetted content library Copilot can only rummage through whatever files a user has permission to open; it doesn’t maintain a single source-of-truth for approved language. |
Curated “smart” content hub with metadata, expirations and usage scores, plus AI search to pinpoint the best answer blocks. (See how to set up a content and pursuits library.) |
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Generic drafting, no proposal workflow Copilot can summarize an RFP or draft text in Word, but it can’t route sections for review, lock boilerplate, or track versions. |
Built-in proposal/SOW templates, role-based approvals, version control and task assignment across Word, PowerPoint & Teams. |
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Zero engagement analytics After a document is sent, Copilot offers no insight into what the prospect read or shared. |
QorusDocs records page-views, time-on-page, clicks and shares—feeding win-loss analytics back into content scoring. You can report on most popular content, terms with the most searches, most useful templates, your best closers by deal value and by win rate, the number of active bids, or top collaborators. See how our data analytics works. |
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Limited to Microsoft Graph data Copilot does not natively connect to CRM objects or external contract repositories without extra build-out. learn.microsoft.com |
QorusDocs has one-click connectors for Salesforce, Dynamics 365 and dozens of line-of-business systems. Learn more about our integrations. |
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Broad, not role-tuned AI Copilot is great for “write me a summary,” but it has no domain skills such as mapping RFP questions to pre-approved answers. |
QorusDocs is trained on proposal patterns—auto-matches Q&A pairs, builds compliance matrices, and suggests win-themes. |
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Pricing optics Copilot is a flat fee per user per month, and many Microsoft 365 Copilot licenses require an annual commitment. In many cases, a separate Microsoft 365 license is required to purchase Copilot.
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QorusDocs pays for itself by shortening pursuit cycles and lifting win-rates; 71% of users report higher response quality. |
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Data-privacy Both run on Azure, but Copilot’s grounding spans the whole tenant, which may surface sensitive draft material across teams. |
QorusDocs keeps prompts and completions in a private Azure OpenAI instance dedicated to your org—no cross-customer training. |
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Buying a QorusDocs proposal software solution means you're getting a tool that's already designed, tested, and optimized for proposal teams like yours. Here are the biggest reasons to go this route:
Buying Doesn’t Mean Settling
One common objection to buying software is the fear of inflexibility. But the best AI RFP platforms are built to adapt. They offer:
In other words, you get the benefits of a purpose-built solution and the flexibility to make it your own. (See what makes us different!)
What is AI Proposal and RFP response software?
AI proposal and RFP response software is a tool that uses artificial intelligence to automate and streamline the process of responding to Requests for Proposals (RFPs). It helps teams draft answers, search for approved content, manage workflows, and collaborate efficiently—saving time and improving win rates.
Sure, building your own might seem appealing—especially if you’re trying to solve a very specific challenge. But the truth is, most proposal and RFP workflows follow a similar pattern. That’s why we have spent years perfecting solutions to help teams like yours respond faster, smarter, and more confidently.
So why start from scratch?
Buy the software. Win more deals. Get back to doing what you do best.
Want to see how a purpose-built proposal platform can work for you? Reach out for a demo or check out our free buyer’s guide to choosing AI RFP software.