// Features
Every feature below is architecturally verified across seven technical workflow documents. These are not marketing claims. They are engineering decisions — each with a specific reason it was built the way it was.
Each card describes one architectural decision that makes the system categorically different from anything else available.
The research engine runs two independent web searches with an AI evaluation layer between them. If the first search doesn't deliver sufficient depth, the system generates a corrective second query targeted at the gaps. This replicates the iterative nature of real investigative research — where the first query is never the best query.
No commercial content tool does this.
Before each research cycle, an AI agent generates a custom reasoning framework for the downstream synthesis agent — tailored to the exact topic, encoding twenty advanced prompt engineering techniques. The research quality is not limited by a static template. It improves with every topic.
The system writes better instructions for itself on every run.
The article writing pipeline is built around a journalism-native editorial framework — an extension of the inverted pyramid used since the 19th century. This system produces journalism, not content. The structure, the attribution discipline, the accountability — all journalism-native.
The only automated content pipeline built on a journalism framework.
Each section of an article is written independently, with the LLM's full context window focused on a specific word budget and brief. A dedicated Assembly Agent then stitches the sections into a coherent narrative with smooth transitions. Focused writing + global editing.
Every section of your article gets its own full AI focus.
The editing pipeline separates diagnosis from implementation. The editor produces a clinical diagnostic report of what needs fixing. A separate Revision Applier implements the fixes faithfully, without rewriting content in the editor's voice. Your prose style is preserved.
Two professional editorial passes that fix the article without destroying your voice.
AI images are generated using a four-bloc prompt structure anchored to a real reference image. The reference image provides the style authority — composition, typography, color palette — so the AI generates content into that structure rather than inventing a new one.
Consistent brand visuals across hundreds of posts.
Every AI-generated image activates Gemini's web search grounding capability. When an image depicts an institution, a location, or a public figure, the system searches for a real visual reference and incorporates it. Images are grounded in verifiable reality.
Every image shows a real place or real institution — not a hallucinated version of one.
The chart production pipeline performs original data research, validates the data, confidence-scores every row, runs a three-layer integrity check, and publishes a live, interactive, embeddable Datawrapper chart directly in the article. This is automated data journalism.
The only automated content system that produces live interactive charts from original research.
The Retrievability Router, the Confidence Gate, and the Verification Loop form a three-layer data integrity system. If the data isn't good enough to publish confidently, the system automatically replaces the chart with a high-quality editorial image.
It won't publish a chart with unreliable data. It will produce something better instead.
Four visual modes for Twitter, three for Facebook — each controlling a different image strategy — all activated by changing one cell in a Google Sheet. No code. No workflow editing. Complete editorial flexibility from a spreadsheet.
Full visual publishing strategy control from a mobile phone.
Your editorial identity — voice guidelines, brand standards, taxonomy, audience profile — is embedded in the system prompts of every agent. Every agent operates from the same editorial source of truth, at the same moment, with no retrieval variability.
Your voice is in the system's DNA — from the first query to the final HTML verification.
The $0.60/month research cost is not an accident. It is the result of deliberate free-tier API stacking, strategic model selection, and self-hosted infrastructure. Cost was treated as a first-class design constraint. The result: newsroom-grade production at individual creator economics.
Not incrementally cheaper. Structurally, categorically cheaper.
We configure the system for your niche before delivery. You review everything before it publishes. Starting at $497, one-time.