Run a Newsroom.
With or Without a Team.
A fully automated news intelligence system that monitors stories, researches them at journalist depth, writes platform-native content, and produces full articles. Controlled 100% via Google Sheets. You never touch the code. We set it up on your own infrastructure, starting at $497.
We configure it for your niche and deliver it ready to run. You review everything before it goes live.
The Production Bottleneck
Is Not Your Fault.
But It Is Your Problem.
You started publishing because you had something worth saying. A beat worth covering. An analysis sharper than what the mainstream was producing. A niche you understood better than anyone else.
What you didn't sign up for was the production operation.
The research that takes three hours before you write a single word. The image that takes forty-five minutes in Canva before you're satisfied it doesn't look embarrassing. The thread you planned to write at 9 AM that never got written because the research ran long and a client email arrived and suddenly it's 4 PM and the story is half a news cycle old.
You know what consistent, research-backed publishing looks like. You've seen it on the accounts growing fastest in your space. You know the difference between a thread written from one Google search and a thread written from genuine investigative depth. You can produce the second kind.
You just can't produce it three times a day, every day, while running everything else.
That is not a discipline problem. It is not a motivation problem. It is a production infrastructure problem — and production infrastructure is exactly what independent publishers have never had access to.
Until now.
The Research Burden
Researching one piece at journalist depth takes 2-4 hours. At three pieces per day, that's up to 12 hours of research before you write a word. It's not sustainable. Nothing gets published.
The Google Zero Threat
Organic search traffic is projected to drop 43% as AI answer engines take over. If you aren't rapidly increasing your content velocity and atomizing across social channels, your audience is actively shrinking. Time is out.
The Consistency Trap
You know consistency is everything. You've read the statistics about how algorithmic reach compounds with frequency. You post when you can — which means sporadically — and watch the accounts that post daily pull ahead.
The AI Garbage Problem
You've tried the AI writing tools. The output is recognizably synthetic: generic sentence structure, no real sourcing, no counter-narrative depth. Publishing it as-is would embarrass you. Editing it takes as long as writing from scratch.
The Visual Gap
There is an immediate quality difference between your content's images and those of the publications you're competing with. Theirs are editorial and consistent. Yours are Canva templates that look like what they are.
The Data Journalism Gap
The most authoritative content in your niche uses data. Charts. Statistics with sources. You skip it because sourcing accurate data, building a chart, and embedding it correctly is an hour you don't have.
The Inconsistency Spiral
When a project, illness, or travel interrupts your posting, the recovery takes three times as long as the interruption. Every gap compounds the previous gaps. Audience momentum does not pause — it reverses.
The Team Economics Problem
The people publishing at the volume and quality you want are either burning out, have a team, or have a system. A team costs $3,000-8,000 per month. You don't have that. So you've been doing it manually.
The accounts growing fastest in your niche are not working harder than you.
They have solved a problem you haven't solved yet.
You've Tried the Alternatives.
Here's Why They Couldn't Work.
You've tried AI writing tools.
ChatGPT. Jasper. Whatever the newest one is. They give you text generated from training data — not from live web research. There is no sourcing. No verification. No journalism framework. No image generation. No social publishing. No WordPress integration. And the output still sounds like it was written by a robot that read a lot of blog posts.
You've tried the SaaS Subscription Trap.
Stacking Jasper AI ($59/mo), Taplio ($39/mo), and other tools quickly scales past $1,400+ per year. And worse, they operate in silos. You are still the bottleneck manually transferring data, engineering prompts, and copy-pasting between platforms to maintain the production pipeline.
You've tried DIY n8n Templates.
You bought a $169 "content farming" JSON file online. Then you realized you had to manage complex API integrations, standardize wildly different RSS schemas, deduplicate database hashes, and build fallback error-handling logic. When an API endpoint changes, the workflow breaks, and you can't debug it.
You've thought about hiring.
You've priced out a social media manager, a research assistant, a graphic designer. Together they run $3,000-8,000 per month. You don't have that budget. And even if you did, the coordination overhead — briefings, revisions, communication, quality control — is itself a job.
The pattern: Every tool you've tried solves one part of the production problem. None of them solve the full pipeline. Because the full pipeline — from source monitoring through research through writing through editing through visual production through WordPress publishing through social distribution — has never been built as a single automated system for solo operators.
Until this.
What you need is not a better tool. You need the infrastructure.
This Is the Infrastructure.
The Autonomous News Intelligence System is not a writing tool. It is not an AI assistant. It is a complete editorial production infrastructure — seven interconnected automated workflows that replicate the full production operation of a staffed newsroom.
It runs semi-autonomously at scheduled times. It monitors your RSS feeds while you sleep. It scores every incoming story against your editorial standards. It researches high-priority stories across 15-20 sources — with a self-correcting, multi-chain AI research engine — in under three minutes.
And you control everything from a Google Sheet.
You do not need to log into n8n. You do not need to touch complex workflow builders. The automation drops the generated content (Twitter threads, Facebook posts, full articles) directly into your spreadsheet. You simply change a dropdown status to "Approve," and the system publishes it.
Your editorial judgment stays yours. The production infrastructure runs automatically. The base setup starts at $497.
Before This System. After This System.
| BEFORE | AFTER |
|---|---|
| Research takes 4 hours. Writing takes 2. By the time the piece is ready, the story is half a news cycle old. | Research report delivered in under 3 minutes. Thread in review within 8 hours. Story covered while it's still news. |
| Posting twice a week because that's all the production capacity you have — and watching the algorithm punish the gaps. | Three researched Twitter threads and three Facebook posts per day, every day, automatically — regardless of what else is happening in your schedule. |
| Images made in Canva in a hurry — inconsistent, recognizably amateur, visually embarrassing next to media outlets in your niche. | Branded editorial images in FT-style visual language — generated per post, consistent, grounded in real institutions via Google Search grounding. |
| "I should post something about that story." Then three days pass, the moment is gone, and you never covered it. | Every high-scoring story in your niche is flagged, researched, and drafted before you decide to write about it. Your queue waits for your judgment, not your capacity. |
| Skipping data charts because finding the data, verifying it, and building the visualization is an hour you don't have. | Live, interactive Datawrapper charts built from original data research, confidence-scored, and embedded automatically — or replaced with an editorial image if the data doesn't clear the threshold. |
| Feeling like a one-person blog competing against media outlets that have teams doing in a day what takes you a week. | Operating with the production infrastructure of a staffed newsroom — managed entirely from a Google Sheet. |
What Monday Morning Looks Like
When the System Is Running
You open your editorial queue in Google Sheets. Overnight, the News Monitor ran three cycles. It read every RSS feed in your source list — two dozen publications in your niche. It found eighteen new articles. It scored each one against your editorial taxonomy on three criteria: audience relevance, urgency, and source credibility. Thirteen scored below your threshold. Five scored above it.
Those five are at the top of your queue, summarized, categorized, and with an angle suggestion for each one. You read the summaries. You flag three. You change their Status field from not-used to ready. You close the laptop.
While you make coffee, the Research Engine fires on the first flagged article. It generates a custom reasoning framework for this specific topic. It runs three independent chains of analytical thinking to formulate the best possible search query. It sends two rounds of searches to the Brave API, evaluates the quality of the first results, and fires a corrective second search if the first didn't deliver enough depth. It extracts full article content from the top-ranked sources. It synthesizes everything into a 700-word intelligence report with citations.
Under three minutes. While the coffee brews.
Three Twitter threads are being drafted in parallel. Each one runs the research report through a journalism framework — mandatory counter-narrative identification, historical precedent, expert attribution, three-impact analytical structure. The cover image AI agent is generating an FT-style editorial collage for the first tweet. The body image agents are working on the remaining five.
Your Twitter review queue has three complete threads. Each has six tweets. Each tweet has its own AI-generated branded editorial image. The cover tweet has a real photograph scraped from the source article. The full research report is archived alongside each thread so you can verify any claim before you publish.
You spend fifteen minutes reviewing. One thread is good to go. One needs a small edit in Tweet 3. One you decide to hold for tomorrow.
Two threads are scheduled. One is back in review status. The Facebook posts for the same three stories are in the Facebook queue, each with a 300-word counter-narrative post and a branded editorial collage image ready to go.
Your entire content day is handled. You have three researched, sourced, visually produced content pieces approved for publication, and a complete audit trail of the research behind every claim.
You have a full day of editorial work ahead — the thinking, the judgment, the voice-of-expertise writing that only you can do. The production machine ran while you were making coffee.
That is not a hypothetical.
That is what a configured system running in your niche looks like at 7:52 on a Monday morning.
Seven Workflows. One Continuous Pipeline.
Every Stage of Production Automated.
The system is not a single tool. It is seven interconnected workflows, each with a specific job, each feeding the next. Here is what each one does and why it was built the way it was.
The News Monitor
What it does: Monitors every RSS feed in your source list continuously. Runs a dual-agent AI analysis on every new article — one agent categorizes and suggests angles, a second scores it on three editorial criteria out of 30 points. Deduplicates against everything already in your queue. Delivers a ranked, scored editorial briefing to Google Sheets.
The architectural decision worth knowing: The two AI agents are separated deliberately. Categorization is a creative editorial task. Scoring is an analytical evaluation task. Combining them into one LLM call produces worse results from both. Two agents. Two cognitive modes. Better editorial intelligence.
What this means for you: Open your spreadsheet and see exactly which stories from the last 24 hours deserve your attention — scored, summarized, with a suggested angle. No manual monitoring. No missed stories.
The Research Engine
What it does: Takes any topic and produces a 500-1,200 word cited intelligence report from live web sources. Runs a 12-step research protocol including: dynamic prompt generation customized per topic, three-chain query formulation, dual Brave API searches with AI-evaluated self-correction between them, source quality ranking, full-page content extraction, and multi-model synthesis (Gemini for reasoning, Grok for final synthesis).
The architectural decision worth knowing: The Analyst Emulator — the first stage of the research engine — does not perform research. It writes the instructions for the AI that will perform research, dynamically tailored to the exact topic. The quality of the final report is not limited by a static prompt template. It is dynamically optimized for every research cycle.
What this means for you: Research reports that cite 15-20 real sources, surface expert quotes, provide historical context, and cost $0.02 each to produce. Every piece of content this system creates — every thread, every Facebook post, every article — is grounded in a research report this engine produced.
Cost: $0.60/month for 30 research cycles. Everything except one xAI Grok API call is free tier.
The Twitter Thread Machine
What it does: Pulls high-scoring articles from the editorial queue, fires the Research Engine, writes a 6-tweet investigative thread using a journalism framework, generates 6 branded AI editorial images (FT-style cover + institutional body cards) via reference-image architecture with Google Search grounding, scrapes a real photograph from the source article, and delivers the complete thread to a review queue.
The architectural decision worth knowing: Before writing begins, the Thread Writer runs a mandatory reasoning protocol: counter-narrative identification, historical precedent research, stakeholder impact mapping, and audience relevance calibration. The thread is written after this reasoning is complete. The result is analysis, not summarization.
What this means for you: Six-tweet threads that cite real sources, name real institutions, provide the angle mainstream coverage misses, and carry branded editorial images — automatically, three times a day — for approximately $0.05-0.10 per thread.
The four visual modes: Control the visual presentation of every thread with one spreadsheet cell. Full AI image package. Featured article photo only. Hybrid. Or text-only for breaking news. One cell. No workflow editing.
The Facebook Post Machine
What it does: Produces a single 250-450 word Facebook post — structured in five blocs engineered for Facebook's "See More" fold mechanics, emotional resonance triggers, and comment-driving question architecture — with a branded editorial collage image. Runs three times daily. Built on the same research engine as the Twitter workflow.
The architectural decision worth knowing: Facebook content is not repurposed Twitter content. The Facebook workflow was built from scratch for Facebook's algorithmic reality. The five-bloc structure — emotion anchor, hook, counter-narrative insight, human element, community question — is a journalism framework for social engagement, not a content template.
What this means for you: Facebook posts that feel written, not generated. Counter-narrative depth that rewards the "See More" click. Closing questions that earn comments. Brand-consistent visuals. Three times daily.
The Article Writing Pipeline
What it does: Takes a research-backed topic through an 11-phase production pipeline: editorial planning → JSON blueprint generation → chapter-by-chapter writing with independent focus per section → key takeaways generation → assembly and stitching → two-pass editorial review (developmental + copy) → pre-format review → HTML conversion → 22-point structural verification → clean WordPress output.
The architectural decision worth knowing: Each chapter is written independently — the LLM gives its full context window to one section at a time rather than trying to write a 2,000-word article in a single pass. This is the difference between focused and diffused attention.
What this means for you: A full article that has been outlined by an editorial architect, written section by section, assembled, reviewed in two professional passes, converted to HTML, and verified — delivered as a WordPress draft for your review.
The Visual Enrichment Pipeline
What it does: Takes the finished article HTML, runs it through an HTML structure enforcer, then sends it to the Imagenator — an AI art director that makes editorial decisions about 2-4 visual placements. Each placement is routed to either the Image Generation Lane or the Chart Production Lane. Assembles the visuals and publishes to WordPress.
The architectural decision worth knowing: The Chart Production Lane performs original data research, validates the data, confidence-scores every row, and only publishes a chart if the data meets confidence thresholds. If it doesn't, the chart is automatically replaced with an editorial image. The system will not publish a chart with unreliable data.
What this means for you: Your articles have publication-grade visual enrichment — editorial images that look like a real publication's art direction and live interactive charts readers can hover over — from data the system researched and verified.
The Automated Publishing Layer
What it does: Takes approved content from the review queues and publishes it to Twitter/X and Facebook via the Blotato API. Manages content as a FIFO queue. Updates the source row's status to posted with a timestamp after every successful publication.
The architectural decision worth knowing: Nothing in this system auto-publishes. The publishing layer only activates when the operator changes the Status field. Editorial sovereignty is preserved at every stage. The automation executes the operator's decisions — it never makes them.
What this means for you: Change one cell in a spreadsheet. Your content goes live — correctly formatted, with the right images, on the right platform, with a complete audit trail.
Twelve Things This System Does That Nothing Else Does.
Self-Correcting Dual-Search Research
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.
The Analyst Emulator — Prompts That Write Prompts
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 Constructive Pyramid Journalism Framework
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.
Chapter Isolation with Assembly Stitching
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.
Diagnose-Then-Treat Editing
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.
Reference-Image Visual Architecture
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.
Google Search Grounding for Visuals
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.
Live Interactive Data Charts
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.
Three-Layer Data Honesty Architecture
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.
Status-Column Visual Publishing
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.
Editorial DNA in Prompts, Not Retrieval
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.
Cost Architecture as a Design Principle
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.
What a Team Like This Costs.
What This System Costs.
This is not a "save time" argument. This is an economics argument.
The production work this system does — the research, the writing, the image creation, the editing, the publishing — has a market rate. That rate is $4,800-13,500 per month if you hire the human equivalent team to do it.
Most independent publishers have never been able to afford that team. So they've done it manually — which means at reduced volume, reduced quality, or reduced sanity. Usually all three.
The Human Equivalent
| Role | What they'd do | Monthly rate |
|---|---|---|
| Research Assistant (2 hrs/day) | Source monitoring, article research, citation formatting | $1,500–3,000 |
| Social Media Producer | Write + schedule Twitter threads and Facebook posts daily | $1,000–3,000 |
| Editorial Image Designer | Design branded images for every post | $500–2,000 |
| Copy Editor (2 passes) | Two editorial passes per article | $300–1,000 |
| Data Journalist | Research, build, and embed interactive charts | $1,000–3,000 |
| Web Developer / CMS Operator | WordPress publishing, metadata, slugs, CSS | $500–1,500 |
| Full team | $4,800–13,500/mo | |
| This system | All of the above | $497 once + ~$10/mo |
$497 is not the price of a tool. It is the price of access to production infrastructure that was previously available only to operations with a team budget.
The ongoing API costs to run the system — the Brave searches, the Grok synthesis calls, the Gemini image generation — run approximately $10 per month. The research alone costs $0.60 per month for 30 deep investigations.
We did not price this at $497 because it does $497 worth of work. We priced it at $497 because we wanted it to be accessible to the people who need it most — the solo operators who have been trying to compete with teams using only their own two hands.
The Cost Per Output
| Output | Human equivalent cost | This system |
|---|---|---|
| 1 deep research report (15-20 sources, citations, expert quotes) | $25–50 | $0.02 |
| 1 six-tweet thread with 6 branded editorial images | $150–400 | $0.05–0.10 |
| 1 Facebook post with research + editorial collage image | $80–200 | $0.03–0.05 |
| 1 full article (research + 11-phase writing + 2 editorial passes + HTML) | $300–800 | under $1 |
| 1 article with 2 AI editorial images + 1 live interactive chart | $400–1,200 | under $2 |
| 30-day full operation (3 threads/day, 3 FB posts/day, 4 articles) | $9,000–30,000 | $497 once + ~$10/mo |
This Is What the System Produces.
Not mockups. Not examples. Actual outputs from the system running on real news topics.
Every piece of content you've seen above was delivered to a human review queue before publication. Every claim has a citation. Every image has a real-world reference. Every article went through two editorial passes.
The operator reviewed and approved all of it.
This System Was Built for You If...
You are a solo journalist or independent reporter
You cover a specific beat with editorial standards you take seriously. You've been trying to build the publishing infrastructure that matches your journalistic ambitions — and you've been doing it alone. This system is the newsroom you couldn't hire.
You are a freelance writer building your own platform
You build your platform while doing client work. Your own publishing is always the last priority. Your Twitter hasn't been active in weeks. Your blog has sporadic pieces and six-month gaps. This system runs while you're billing. Your platform grows while you sleep.
You are an independent blogger or digital publisher
You understand content strategy and want to add a news dimension. You've watched news-adjacent accounts grow faster than opinion-only accounts. You just didn't have the research infrastructure to produce it at scale. Now you do.
You are a solo content creator or personal brand builder
You operate in a niche where news happens. You want to be the account people follow because they trust your analysis, not just because you post consistently. This system is the credibility layer that turns a creator account into a media account.
You are a lean media team or collective
You are a small editorial team facing declining ad revenues and increasing overhead. You need to reduce headcount or scale output drastically without sacrificing quality. You need enterprise-grade newsroom infrastructure designed for lean operations.
What all four of you share: editorial judgment that is already there. What you've been missing: the production infrastructure to exercise it every day, at scale, without burning out. That is exactly what this system provides.
Who This System Is Not For
This is the honest section. It matters as much as everything above it.
You want fully automated publishing with no human review.
Every piece of content this system produces lands in a human review queue. You decide what gets published. The automation handles production; you handle editorial control. If you want a system that publishes without you, this is not it.
You are looking for a content marketing tool.
The system is built on journalism frameworks — research depth, source attribution, editorial rigor. It is not designed for product promotion or marketing copy. If your goal is creating promotional content for a business, this is the wrong tool.
You have no interest in daily editorial engagement.
Running this system well requires approximately 30-60 minutes per day of editorial attention. If you want to configure something and forget about it entirely, this will disappoint you.
You are a complete beginner to digital publishing.
The system assumes familiarity with Google Sheets, WordPress, and basic social media management. You don't need to understand n8n or APIs, but if you have never managed a content calendar, the editorial layer will feel overwhelming.
You represent a massive enterprise legacy media company.
This system is architected for solo operators and small, lean media teams. Massive enterprise needs — hundreds of seats, legacy CMS white-labeling, and multi-layered bureaucracy — are outside the scope of this product.
If you read the above and none of it describes you — you're a solo publisher who takes editorial quality seriously, wants to publish consistently, and understands that the tool requires your editorial judgment to work — then you are exactly who this was built for.
One Investment. One Configured System. Yours to Run.
The Human Equivalent
Research assistant, social media producer, editorial image designer, copy editor, data journalist, and CMS developer.
- ✓ All 7 workflows configured for your niche before delivery
- ✓ Hosted on YOUR Google Cloud / API accounts
- ✓ 100% operated via a simple Google Sheet interface
- ✓ Base package for solo practitioners
- ✓ Enterprise/Team packages available (starting at $999+)
APIs break. Prompts need tweaking. If you don't want to maintain the system yourself, we handle 100% of the debugging, modifications, and updates for $150/month. (Included free for the first month in Enterprise packages).
The Human Equivalent
Research assistant, social media producer, editorial image designer, copy editor, data journalist, and CMS developer.
- ✓ All 7 workflows configured for your niche before delivery
- ✓ 24/7 News Monitor & Self-Correcting Research Engine
- ✓ Twitter Thread & Facebook Post Machines
- ✓ 11-Phase Article Pipeline with Datawrapper Charts
- ✓ Automated Publishing Layer controlled via Google Sheets
- ✓ A configuration session with us before delivery
~$0.60/mo for research infrastructure. Total estimated API costs: ~$10-15/mo at full publishing volume.
For $1.36 per day, you have a research assistant, a social media producer, an editorial image designer, and a copy editor working in your niche around the clock — every day of the year.
"You review everything before it goes live."
Nothing auto-publishes. Every piece of content lands in your review queue. You read it. You approve it. The editorial control is yours. The production work is ours.
"We configure it before you use it."
Not a template you set up yourself. We work with you to configure your editorial identity, source list, brand standards, and WordPress setup before delivery. You start with a system built for your specific niche.
The Delivery Confidence Guarantee
Before you see an invoice, we run a configuration session together. Your editorial niche, your RSS sources, your brand standards, your WordPress setup — we scope all of it with you first. You know exactly what you're getting before a single dollar changes hands. If we can't configure the system to your specifications, you don't pay.
Limited Configurations Per Month
Every system is configured for your editorial niche, your RSS sources, your brand standards, and your WordPress setup before delivery. That personalization takes time. We configure a limited number of systems per month. If you're reading this, a slot is available.
Questions Worth Answering Honestly
Stop Producing Manually.
Start Publishing at Newsroom Quality.
You've been doing this manually because there was no alternative.
Now there is.
The Autonomous News Intelligence & Publishing System is the production infrastructure for the independent publisher who takes editorial quality seriously. Research reports in under three minutes. Platform-native Twitter threads and Facebook posts three times a day. Full articles with interactive data charts delivered to WordPress as drafts. Everything reviewed by you before anything goes live.
The Roadmap to a Fully Autonomous Media Operation
This is not a static tool. It is an evolving architecture designed to automate every layer of digital journalism. This is where it's going.
PHASE 1: VIDEO INTEGRATION
A multi-modal video pipeline that identifies, extracts, and re-engineers source video into platform-native short-form assets (Reels, TikToks, Shorts) with automated captioning and branding.
PHASE 2: PODCAST & AUDIO
An end-to-end audio production suite. High-fidelity text-to-speech conversion for every article, plus an automated podcast compiler that scripts, voices, and assembles weekly news roundups from the system's top-performing stories.
PHASE 3: LIVE FIELD REPORTING
Real-time field reporting synthesis. The system ingests unstructured audio notes and photos from a reporter on the ground and transforms them into structured, multi-platform news coverage in minutes, not hours. The field reporter reports; the system publishes.