Using Markdown Files for Client Assessments and Scaling AI Agent Responses

·Apr 03, 2026 11:05 PM·

For responding to client assessments / questionnaires, anyone out there found success in leveraging .md files? I’m in the early stages of trying to understand how to setup AI agents and welcome any thoughts from those also trying to scale their processes.

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Using Markdown Files for Client Assessments and Scaling AI Agent Responses
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Jacob G.
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hey Andrew K.: Centralizing + tagging is one approach. you could store all your .md files, policies, and past responses in one searchable library with tags for product/region/framework. The key is applying tags at upload time, then filtering by tag when generating responses. in vanta, you can create tag categories in the Knowledge Base, apply them to content, then select relevant tags when starting each questionnaire—Vanta auto-filters what the AI uses. i also wonder if this would be a good Q to post to our Questionnaire Automation Product Manager, coming here later this month to answer Qs on this and similar topics? if you want, submit your Q here, couldnt hurt to have a Vanta PM pov too!
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Andrew K.
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Jacob G. We’ve tried tagging but that looks like it’s done at the questionnaire level and it would be great to have the routing done at the question level. As an example, if a questionnaire has a question is related to GDPR, it is routed to a data privacy team. Having the ability to crate markdown files with specific routing rules would help distribute the workload rather than requiring manual assignment. Maybe this is in the Vanta platform and I’m missing it
👀1
Jacob G.
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hey Andrew K. thanks for this further context! i wonder if this clip addresses the granularity of getting down to the question level? the only thing remaining is that I'm not sure this is specific to your point of .md files. And if not, I can definitely submit further let me know!

Vanta Community
APP
·
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This post is now synced! Check it out here:
Using Markdown Files for Client Assessments and Scaling AI Agent Responses
⤵️ Any future comments will be automatically posted to the thread
Jacob G.
·
·
hey Andrew K.: Centralizing + tagging is one approach. you could store all your .md files, policies, and past responses in one searchable library with tags for product/region/framework. The key is applying tags at upload time, then filtering by tag when generating responses. in vanta, you can create tag categories in the Knowledge Base, apply them to content, then select relevant tags when starting each questionnaire—Vanta auto-filters what the AI uses. i also wonder if this would be a good Q to post to our Questionnaire Automation Product Manager, coming here later this month to answer Qs on this and similar topics? if you want, submit your Q here, couldnt hurt to have a Vanta PM pov too!
1
Andrew K.
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Jacob G. We’ve tried tagging but that looks like it’s done at the questionnaire level and it would be great to have the routing done at the question level. As an example, if a questionnaire has a question is related to GDPR, it is routed to a data privacy team. Having the ability to crate markdown files with specific routing rules would help distribute the workload rather than requiring manual assignment. Maybe this is in the Vanta platform and I’m missing it
👀1
Jacob G.
·
·
hey Andrew K. thanks for this further context! i wonder if this clip addresses the granularity of getting down to the question level? the only thing remaining is that I'm not sure this is specific to your point of .md files. And if not, I can definitely submit further let me know!