Turn what your company does into content only your team could write.
SignalStory surfaces signals across your stack like a newly shipped feature, a closed deal, or a client interview. It scores these signals and turns the relevant ones into LinkedIn posts, X threads, and blog drafts in your team's voice, so you keep showing up while you build. Six agents think before one writes, and the anti-slop editor rejects anything generic.
The cost isn't a missed demo this week. It's a brand nobody can picture six months from now.
The weeks you never post
You know you should publish consistently. Between building and selling, a month goes by, the feed stays quiet, and nobody can picture what your company does.
No point of view
Prompt-to-post tools don't know what your team believes, so they fill the gap with the average opinion of the internet.
Anyone could have posted it
If a competitor could publish the same post by swapping the logo, you are building the category for them.
Silence compounds the same way consistency does, just in the wrong direction. SignalStory is built for the other side of that: your own signals in, writing happens last, and every draft grounded in what your company believes, says, and can prove before the first sentence exists.
From signal to scheduled post in four steps.
Six agents run in order, and only the fifth one writes.
Most tools ask a single model to do the whole job in one pass. SignalStory splits the work across specialists, with a quality gate before the writing and another after it.
Event Listener
extractionTurns the raw signal into clean, verifiable facts: what happened, who was involved, and what can be proven.
Significance Scorer
reasoningJudges whether the signal deserves content at all, scored against your editorial strategy.
Not everything deserves a post.
Weak signals are rejected here rather than padded into thin content, and the rejection comes with a note on what would change the verdict.
Story Finder
reasoningGenerates competing angles for the same signal, then ranks them by how distinctive each one is.
Narrative Strategist
reasoningCommits to one angle and builds the brief: the argument, the structure, and a ledger of claims. Each claim is marked supported or unsupported by your knowledge library.
Channel Transformer
writingThe first and only agent that writes prose. It turns the brief into a LinkedIn post, an X thread, and a blog piece, each shaped for how that channel gets read.
Anti-Slop Editor
reasoningScores every draft against one question: could a generic model have written this without your context?
Generic drafts don't ship.
A failing draft gets exactly one rewrite using the editor's notes. If it fails again, it is flagged for you instead of being published quietly.
What you get alongside the drafts.
Your tools, connected once
Native connections for Pipedrive, Attio, Linear, and GitHub, plus a generic webhook that covers HubSpot, Salesforce, Gong, Slack, and anything Zapier or Make can reach.
Content that cites its sources
Paste in case studies, changelogs, and past posts. Drafts pull from them with citations, and every claim shows whether a real source backs it.
Every claim traced to a source
Each draft carries its evidence trail: which sources grounded it, and which claims you should check yourself before publishing.
Written for each channel
One brief becomes a LinkedIn post, an X thread, and a long-form blog piece. Each is restructured for its format rather than copy-pasted between them.
Scheduled, not sporadic
Queue approved posts on a calendar and auto-publish to LinkedIn at the time you picked. The week you are heads-down building is the week the queue carries you.
The numbers behind the habit
Follow drafts from generated to approved to posted, alongside anti-slop pass rate and cost per signal, so consistency is a number you watch rather than a feeling.
Common questions
Will this get me more demos?
Not on its own, and we won't pretend otherwise. Brand compounds over months, not per post, so any tool promising you demos per post is guessing. What SignalStory removes is the reason most teams go quiet, and what it shows you is the part it can actually measure: how many signals become published posts, how steady your cadence is, and what that costs. Inbound follows presence over time. It does not follow one post.
Why does the output sound less like AI?
Because writing happens last. Every earlier stage is grounded in your founder's beliefs, brand voice, editorial strategy, and cited company knowledge. An anti-slop editor then gates whatever comes out of the writing step.
How often should I be posting?
Whatever cadence you can hold. SignalStory exists so the answer isn't zero: a signal you already have becomes drafts in minutes, and the calendar keeps approved posts going out on the weeks you're heads-down.
Do I have to write the content myself?
No. You submit a short signal, and the pipeline produces LinkedIn, X, and blog drafts you can review, edit, copy, export, or schedule.
What makes the output 'grounded'?
A retrieval step pulls proof from your own knowledge store, and the brief records which claims those sources actually support. Anything ungrounded is flagged for you.
Can I bring signals in automatically?
Yes. Connect Pipedrive, Attio, Linear, GitHub, or any tool through a generic webhook, and qualifying events become signals on their own.
Who is this for right now?
SignalStory is pre-launch and onboarding a founding cohort of B2B teams. Early users shape what gets built next. We would rather show you real numbers from your own account in a couple of months than a wall of testimonials we invented.
Start showing up consistently, beginning with this week's signal.
SignalStory is pre-launch and onboarding its first teams, who get a direct say in what gets built next. Connect your tools, teach it your voice, and turn the work you are already doing into a presence that compounds.