OPOV is in early access. The first fifty datasets get white-glove coverage builds.
For operators, creators, and their agencies
Thought leadership content, backed up by data science.
We help you form an Original Point of View — an OPOV: a hot take found by our patent pending analytics pipeline, validated by a python engine that only ships statistically valid perspectives.
PRODUCT PREVIEW — A VALIDATED TAKE · ILLUSTRATIVE DEMO DATA
Every published piece carries this footer·sources + pull dates·engine version + core hash·run date·every number recomputable
The argument
When writing became free, the writing stopped being the product.
01Prose now costs nothing. Anyone can generate ten thousand competent words before breakfast. Whatever value an article still has, it is not in the sentences.
02So the value moved into the claims. A piece is worth exactly what it asserts that a reader could not get anywhere else — which is why most generated content is worth what it cost.
03And a claim is worth what it survives. Verification is the new scarcity. The publishers who win the next decade won't produce the most content; they'll be the ones whose numbers hold when somebody checks.
What this implies
A tool that always finds a story is a fiction generator.
Every content tool must produce output — that is the business model — but nothing upstream of the words ever touches evidence, so the tool cannot know whether what it made is true. In 2026, a Big Four firm retracted a published report after its references turned out not to exist. OPOV is organized backwards from the category: evidence first, gate second, words last.
Built to generate
×Starts from a keyword and rehashes what already ranks — content that says what everyone says.
×Numbers come from the model's imagination. You fact-check everything before you dare publish.
×Always produces something — the tool never says "there's no story here."
×Credits expire monthly. You pay for drafts you deleted.
Built to find
✓Starts from your data and finds patterns nobody has published, because nobody had them.
✓Every number is computed from data, archived, and recomputable from the piece's own footer.
✓A pattern engine that refuses to answer when the signal is weak — takes exist only when they earn it.
✓Runs that find nothing are refunded. You pay for validated findings, not word count.
What we ship
Professional grade, cited, research content — and the visuals to match.
Articles, social posts, and related visual assets — every claim cited, every chart sourced per bar.
PUBLISHED ARTICLE — SOURCED CHART + CITED PROSE · ILLUSTRATIVE DEMO DATA
How it works
Four steps from context to published take.
You give context and approvals — you never write prompts, pick keywords, or promise the answer in advance. The evidence does the rest.
STEP 01
Give us some context.
30 seconds: your website, your market, and anything you're already arguing about. We read your site in the background so your takes talk like you — everything you tell us is a prior, never an override.
Your website — we read it in the background
yourcompany.com
✦ READ FROM YOURCOMPANY.COM — CONFIRM OR CORRECT
SubjectYour name · your role
MarketYour market
Entities in your worldListings · Sellers · Neighborhoods
Your vocabulary“DOM” · “price improvement” · “your shorthand”
PRODUCT PREVIEW — ONBOARDING · CONTEXT · ILLUSTRATIVE DEMO DATA
STEP 02
Gather the Data.
Connect a tool, drop a CSV — or let us build the dataset from public sources. Before anything runs you approve the coverage plan: what's buildable, where every column comes from, its license, and the cost. "Unbuildable" is a result, not an apology. One approval. No surprise spend.
Gs
sheets
not connected
Pg
postgres
not connected
Ml
mls extract
connected ✓
Drop a CSV or XLSX here — or click to browse
Build it for me → your market
Assessor records · Census ACS · FRED · your licensed MLS extract. You approve the coverage before anything is built or spent.
PRODUCT PREVIEW — POINT US AT THE DATA · ILLUSTRATIVE DEMO DATA
STEP 03
Analytics Engine.
The engine asks the questions — hundreds of candidate patterns, gated hard, best bets run first. Takes appear in your rail the moment they're validated and archived, never before. Empty results show up too, refunded, because the absence can be the story. You choose; nothing publishes itself.
Cleared
Overpriced-at-list sits past 90 days at 1.9× the metro rate
honest empty · run refunded · the absence can be the story
refunded ↩
PRODUCT PREVIEW — LIVE TAKES · ILLUSTRATIVE DEMO DATA
STEP 04
Create.
Pick a take, a format, and a destination. Deep research runs after you choose — anchors, context, counter-evidence kept in — then OPOV drafts in your voice. The numbers never move: every figure is audited against the archived envelope before you publish.
DRAFT · YOUR WEBSITE · NUMBERS AUDITED VS ENVELOPE ✓
The Second Price Cut Is a Confession
The house on the corner did everything the playbook says. It cut its price in July. It cut again in August. It is still for sale.
Across 1,940 listings in one metro, homes in the north submarket that took their first price cut after day 45 — and then took another — sat unsold past 90 days at 2.3 times the metro rate…
SOURCES: county assessor · regional mls extract (licensed) · census acs · fred ENGINE v0.2.0 · run R1 2026-08-17 · associations, not causal claims
PRODUCT PREVIEW — DRAFT · ILLUSTRATIVE DEMO DATA
The honesty part
A system that can't say “nothing there” can't be believed when it says “something.”
That is falsifiability, applied to publishing. OPOV's engine is allowed to refuse — it answers only when a pattern clears a hard statistical gate, and it archives the evidence when it does. That refusal shapes everything downstream: each take you publish inherits its credibility from the answers the engine declined to give.
Every 15%-plus discount looked generous. The data says it predicted 1.8× the cancellations.
Discount at booking> 15%
Booked ahead> 30 days
verified · engine v0.2.0 · run 2026-08-14 · envelope 9f3a…c41d · one pattern, not a ranking · associations, not causal claims
01No number without a receipt. Every figure in every piece traces to an archived engine result or a cited source — recomputable, not vibes.
02No take before it's earned. Findings surface only after validation and archiving. Zero optimistic emissions.
03No torturing the data. If nothing clears the bar, we don't reshape the question until something does. We show you the empty — and refund the run.
04Contradictions stay in. When research complicates a finding, the piece reports the tension instead of smoothing it.
From take to published
A finding still needs telling — so we finish the job.
Pick a take and OPOV researches the context around it — current events, the human story, the counter-evidence kept in — then drafts in your voice with a hard editing pass. Answer engines are ravenous for primary sources, and an original finding is the one kind of content that can't be paraphrased into someone else's post. We format for the machines, but the durable advantage is that nobody else has your numbers.
Researched article
Anchored, sourced, provenance footer, GEO-ready
Social post
The finding, sharpened for the feed
Video script
The story arc, timed and beat-mapped
Newsletter
Your take, in your readers' inbox
Pricing, the same way
You pay for validated findings, never for word count.
We price the way we publish: only what survives counts. Runs that come back empty refund automatically, and nothing expires at midnight. Every plan carries a 90-day money-back guarantee — no questions asked.
No. The findings come from a deterministic pattern-detection engine — same data in, same answer out, every time. Language models help plan, phrase, and frame, but no model ever originates a number, touches your dataset's values, or decides whether a pattern is real. The engine's gate decides, and it happily says no.
Q2What data does it use? What if I don't have any?
Bring a spreadsheet, connect a tool, or bring nothing: "build it for me" assembles a dataset from public sources — government portals, open data, registries — with the license and origin of every column recorded. You approve the coverage plan before anything runs.
Q3What happens when there's no story in my data?
We tell you, with reasons, and refund the runs that came back empty. Sometimes the empty is the story — "everyone believes X drives Y in this market; the data doesn't back it" is a stronger piece than a weak positive, and OPOV will help you publish exactly that.
Q4Can I verify a published number myself?
Yes — that's the point. Every piece ends with a provenance footer: the sources and pull dates, the engine version, the run date, and the archived result the numbers came from. A skeptical reader, editor, or client can check the math. We think that's what publishing should feel like again.
Q5Isn't “data-driven content” just the new buzzword?
Usually, yes — in most tools it means quoting someone else's survey. One question separates the two: did the number exist before the article did? OPOV's findings are computed from a dataset, gated, and archived before a single sentence is drafted. The article is written about the finding, never the other way around.
Q6Who is OPOV for?
Operators who know their numbers and want authority content that's actually theirs; creators who'd rather publish findings than takes on takes; and agencies that need client deliverables they can defend in the room when someone asks "where did this number come from?"
START WITH YOUR DATA
The most interesting thing you could publish is already sitting in the data.
Point us at your data. Approve the coverage. Publish the take you can prove — or publish the honest empty, and be the only one in your market telling the truth either way.