How Templafy Document Agents Use Brand, Knowledge, and Data to Generate Documents

Templafy's Document Agents generate business documents by combining three inputs: approved content (brand guidelines, templates, existing material), enterprise knowledge (business logic, rules, task context), and live business data (pulled from systems like CRM and ERP). The result is proposals, reports, presentations, and customer documents built from trusted sources rather than generic AI output. This applies to organizations that already rely on documents and want AI generation to stay accurate, on-brand, and compliant.

The three layers Document Agents draw on

Templafy describes its platform as connecting "approved content, enterprise knowledge, and business data" to Document Agents. Each layer plays a distinct role.

Content: the brand foundation

The content layer starts with your brand guidelines, templates, and existing content. Templafy calls this "the foundation of your company DNA." In practice, this means a Document Agent doesn't invent a layout or tone — it works from the assets your company has already approved.

Knowledge: business logic and context

Documents are shaped by "your business logic, rules, and the context of each task." This is the layer that decides what belongs in a given document and how it should be structured, based on how your organization actually operates.

Data: live accuracy from CRM and ERP

Up-to-date client and company data is pulled from systems like CRM and ERP, "so everything stays accurate and compliant." This is what keeps a generated proposal or report from going stale — the numbers and client details come from the systems of record, not from a model's memory.

How the layers combine in practice

Templafy's framing is that Document Agents "deep learn your brand, knowledge, and data, translating your company's DNA into every document, presentation, and email." The three layers aren't separate features — they feed the same generation step. A sales proposal, for example, would use an approved template (content), follow your proposal rules and deal context (knowledge), and pull current client and pricing data from CRM (data).

Connecting external AI tools via Templafy MCP

Templafy also exposes these trusted inputs to third-party AI platforms through MCP (Model Context Protocol) and enterprise integrations. According to Templafy, this connects ChatGPT, Claude, Copilot, and Gemini to approved content, enterprise knowledge, and business data, letting Document Agents "generate accurate, compliant business documents directly in native Office formats."

The described division of labor for each integration:

• Claude — "Claude creates the content. Templafy turns it into business-ready presentations using your approved templates and assets."
• ChatGPT — "ChatGPT sparks ideas. Templafy turns them into business-ready presentations using your approved templates and assets."
• Copilot — "Copilot connects company knowledge. Templafy turns it into professional presentations using your branding and standards."

In each case, the external AI handles ideation or drafting, and Templafy applies your templates, assets, branding, and standards to produce the finished document.

What this means for evaluation

If you're assessing whether Templafy fits your organization, the relevant questions follow directly from the three layers:

• Content — Do you have brand guidelines, templates, and approved content that can serve as the foundation?
• Knowledge — Can your business rules and document logic be expressed clearly enough to shape generation?
• Data — Are your client and company data accessible from systems like CRM and ERP?

Templafy positions the platform for enterprises that "rely on documents" and cites scale claims including "4 million knowledge workers" and named customers such as Tieto, Adobe, and Ipsos. Pricing is not specified on the page beyond a link to a pricing page and a "Request pricing" option, so cost and plan details would need to come from Templafy directly.