Context-first generation
BlendScribe starts from domain scan data, products, categories, language and business facts before a draft is created. The article is connected to the real offer instead of being a detached generic text.
BlendScribe gives companies a free test of an own-domain AI blog service: business context goes in, reviewed articles and AI-readable publishing outputs come out.
Live publishing surfaces
The service combines a customer workspace, site scan, AI-assisted drafting, editorial review, own-domain rendering and machine-readable outputs. Customers can test the flow first, then decide how to roll it into their website.
BlendScribe starts from domain scan data, products, categories, language and business facts before a draft is created. The article is connected to the real offer instead of being a detached generic text.
Server-rendered pages expose primary copy, internal links, canonical metadata and JSON-LD before enhancement scripts run.
Markdown, RAG JSON, llms.txt and policy files give assistants cleaner material than scraped page fragments.
Operators can work through the draft, metadata, article design and public output before publishing to the customer domain.
The blog runtime can add a native publishing surface to an existing site without asking the customer to rebuild the whole frontend.
The business sees a normal domain-native blog. The operator gets a focused workspace for context, drafts, review and publishing. Search and answer engines receive cleaner source material behind the same public content.
Install a small PHP blog runtime on the customer domain. Add business context, generate and approve articles, then publish a public blog that feels native to the existing site.
The installed runtime requests server-rendered HTML and aligned metadata from the publishing engine. Machine-readable resources expose the same approved content in cleaner formats for crawlers and assistants.
Brand, domain, language, products and publishing preferences stay scoped to one customer account.
A lightweight runtime adds the blog surface to the existing customer domain.
Drafts use product context, templates, metadata, FAQ blocks and internal-link signals.
The blog is served as crawlable HTML with canonical metadata and structured data.
Clean content mirrors and manifests expose the same approved material to machines.
The workflow stays deliberately small: blend context, generate a structured draft, review the public output, then publish it for visitors, search engines and answer engines.
Start from a domain, products, categories, language and brand facts so articles are tied to the real offer.
Create drafts with headings, summaries, FAQ candidates, product links and metadata prompts baked into the flow.
Inspect the final article surface, schema, internal links and discovery endpoints before publishing.
The same approved content becomes HTML for visitors and clean source material for search and AI systems.
The product does not stop at generating text. Approved content can be served as human-readable pages and as structured source material that crawlers and assistants can parse with less guesswork.
/articleServer-rendered article HTML with canonical metadata, Open Graph and JSON-LD graph nodes.
Human surface?md=1Markdown Mirror for a clean article source with front matter, token estimate and content hash.
Agent source?rag=1Per-article JSON projection with heading-aware chunks for ingestion pipelines.
RAG ready/rag.jsonSite-wide manifest for change detection, filtering and corpus sync.
Manifest/llms.txtCurated Markdown index that explains the site and points assistants to important resources.
AI discovery/.well-known/domain-profile.jsonCanonical brand and software identity profile for answer engines and semantic extractors.
Identity/robots.jsonStructured crawler rules driven by the selected workspace policy.
PolicyModernity here means fewer moving parts, clearer output formats and less client-side fragility. The core page, metadata and links are available before any enhancement script runs.
Primary copy, links and schema exist in the initial HTML. JavaScript only enhances the interface.
Customer domains, settings and content operations stay isolated from each other.
Brand and domain values are configurable, so future naming changes stay manageable.
Teams can review drafts, rendered pages, structured data and machine-readable content sources before the public article becomes part of the customer domain.
Sections are written as self-contained idea blocks so people can scan them and machines can extract them without losing context.
Organization, WebSite, WebPage, SoftwareApplication and FAQ nodes share stable identifiers in the server-rendered structured data.
Public machine-readable resources help crawlers and assistants understand the approved content library.
Yes. The public blog is designed to be installed on the customer domain through a lightweight runtime, while the publishing system handles rendering and content operations.
No. Generation is only one step. The product also handles product context, metadata, public rendering, customer-domain routing, machine-readable mirrors and crawler rules.
Yes. Public articles can expose Markdown mirrors, RAG JSON projections, site-wide manifests and llms.txt discovery files so assistants can ingest the content cleanly.
No. The install model is meant to add the blog surface to an existing customer domain without forcing a full frontend rebuild.
Yes. The free test lets a customer register, enter the workspace and see the publishing flow before committing to a broader rollout.
The public surfaces are server-rendered, the core content and metadata are available in the initial HTML, and enhancement scripts stay small.
The workflow is designed for operator review. Drafts, metadata, article layout and discovery outputs can be checked before content is published.
Start with a free test, connect one customer domain, blend the business context, then publish content that works for visitors, search engines and answer engines from the same source.