Instrumentl, Grantable, and Submittable: Comparing AI-Powered Grant Management Tools

Unlike generic AI tools that generate content without context, Grantable learns from your organization's best work. As you upload successful proposals, program descriptions, and impact narratives, the platform builds a knowledge base specific to your organization. When drafting new proposals, the AI draws from this library, ensuring new content reflects your established voice, proven approaches, and actual program details.

This addresses one of the biggest challenges with AI-assisted grant writing: maintaining authenticity. Funders can spot generic, templated language. Grantable's approach helps ensure your proposals sound like they come from your organization, not a robot, while still accelerating the drafting process significantly.

• Upload unlimited past proposals, program descriptions, and organizational materials
• AI learns your writing style and organizational voice patterns
• New drafts incorporate language and approaches from your best past work
• Content library improves over time as you add more successful proposals

Grantable's workflow is straightforward: upload an RFP, and the platform produces structured responses based on your prompts and content library. You can generate sections individually or entire proposals at once. The AI identifies key questions and requirements from the RFP, ensuring your draft addresses everything funders need while drawing from your proven language and program descriptions.

The platform's strength is speed. What might take hours or days of initial drafting becomes a matter of minutes. You then invest your time refining, personalizing, and enhancing the AI-generated draft with specific stories, recent data, and strategic framing. This shifts your effort from staring at blank pages to editing and improving existing content, a much more efficient use of human expertise.

• Upload RFPs and receive structured outline of all requirements
• Generate draft sections addressing each funder question
• Iterate quickly on drafts with conversational AI prompting
• Claims to speed up drafting by 80% compared to starting from scratch

Grantable's focused approach means it doesn't attempt to be a full grant management platform. It offers fewer built-in research and analysis tools than platforms like Instrumentl or Grant Assistant. You'll still need separate systems or processes for discovering opportunities, tracking deadlines, managing post-award compliance, and building funder relationships.

The platform also doesn't discuss the material used to train its AI system on its website, meaning it may require more hand-holding to generate consistent, context-specific responses compared to tools trained specifically on grant writing datasets. Additionally, like all AI writing tools, outputs require careful human review to ensure accuracy, avoid hallucinations, and add the nuanced storytelling that makes proposals compelling.

• No grant discovery or funder database features
• Limited post-award tracking and compliance management
• Requires existing knowledge base of past proposals to work effectively
• AI-generated content needs significant human review and enhancement

Grantable offers a free plan with limited features for individuals or small teams, making it accessible for organizations wanting to test AI-assisted writing before committing financially. Paid plans unlock more extensive AI capabilities, larger content libraries, and advanced collaboration tools. Flexible subscription plans are designed to scale with your organization's needs, offering options for monthly flexibility or annual commitments.

This tiered pricing makes Grantable particularly attractive for smaller nonprofits or those just beginning to explore AI for grant writing. You can start free, prove the value with actual proposals, and upgrade if the tool delivers meaningful time savings. The pricing is generally more accessible than comprehensive platforms like Instrumentl, reflecting its focused scope.

• Free plan available for testing and limited use
• Paid plans with tiered pricing based on organizational size and needs
• Monthly or annual billing options for budget flexibility
• Generally more affordable than full-featured grant management platforms

Data privacy and security are top priorities for Grantable, with strict confidentiality ensuring grant content stays exclusively within your organization and is never used to train AI models. This addresses a major concern nonprofits have about using AI tools: that sensitive organizational information might be exposed or used to benefit other users.

Unlike free AI tools where your inputs may train the model and become accessible to other users, Grantable's commitment to data isolation means your proposals, program details, and organizational materials remain private. This makes it appropriate for use with sensitive information, though organizations should still review their internal policies about what information can be entered into cloud-based AI tools.

• Your content is never used to train AI models or shared with other organizations
• Data remains within your organization's account with strict access controls
• Appropriate for use with most organizational information and program details

• Small to mid-sized nonprofits where one person handles most grant writing
• Organizations with strong existing content that needs to be adapted for new applications
• Nonprofits struggling with the time burden of drafting multiple proposals
• Grant writing consultants managing multiple client organizations
• Organizations that already have discovery and tracking systems but need writing acceleration

Platform adoption fails when organizations skip training and simply expect staff to figure it out. Budget time for comprehensive onboarding, not just for the primary grant writer but for anyone who will interact with the system. This might include program managers who provide data, finance staff who track budgets, and executive leadership who review reports.

• Schedule formal training sessions rather than relying on self-directed learning
• Create internal documentation specific to your workflows and processes
• Designate a platform champion who becomes the expert and internal resource
• Allow time for learning curves rather than expecting immediate productivity gains

Organizations should remove confidential information and personally identifiable information before interacting with AI tools. Implement a human-in-the-loop approach that uses a combination of machine and human intelligence to train, use, verify, and refine AI outputs. Establish clear policies about what information can and cannot be entered into these platforms.

• Review platform security policies and data handling practices before committing
• Create guidelines for what types of information can be entered into AI tools
• Establish verification processes for all AI-generated content before submission
• Ensure your AI use aligns with funder requirements and expectations

Before implementing a platform, establish clear metrics for success. This might include time spent per proposal, number of applications submitted, win rate, or dollars secured per hour of staff time invested. Track these metrics before and after implementation to demonstrate ROI and inform decisions about renewals or changes.

• Baseline your current time investment and success rates before implementing new tools
• Track both efficiency metrics (time saved) and effectiveness metrics (funding secured)
• Gather qualitative feedback from staff about workflow improvements and challenges
• Reevaluate your platform choice annually based on performance and changing needs