AI for data work, with the work still visible.
Most analytics AI either operates as an opaque black box or gets banned outright. Both leave teams with work they can't defend. PulseQL keeps every step inspectable so the team can review, refine, and approve before anything ships.
Workflow
Reviewable
human-in-the-loop by design
Product
Desktop app
focused workspace
Scope
Focused
workflow, review, value
active workflow
Churn by acquisition channel
Ask a data question
plain-English starting point
Review the proposed work
human judgement stays visible
Refine the output
iterate before sharing
Promote what is useful
turn work into a reusable artifact
status
v1.1 soon
platforms
03
scope
focused
01 / The walkthrough
One question, end to end.
What “keeping every step inspectable” looks like in practice. A question goes in; a reviewed, approved artifact comes out — with the path between them visible the whole way.
ask
“What changed in this metric, and what should the team review before sharing it?”
review path
- 1
understand the request
keep the user intent visible
- 2
prepare a reviewable draft
no invisible automation
- 3
surface assumptions
make uncertainty easy to spot
- 4
promote only after review
team judgement stays in the loop
reviewed output
PulseQL keeps the proposed work, assumptions, and review state visible before a result becomes something the team depends on.
Review status: ready(human approval recommended)
Ready for team review.
AI-assisted data work should be reviewable before teams rely on it.
02 / What it does
Six capabilities, one loop.
Every feature ladders up to that promise. Together they form the same workflow on repeat: ask, review, refine, approve, share.
Bring the work together
Move from question to reviewed output in one focused workspace instead of bouncing across disconnected tools.
Ask in natural language
Start from a plain-English question and keep the generated work visible enough for a human to inspect.
Review before relying
PulseQL is designed around reviewable steps, not invisible automation.
Keep trust visible
Outputs are shaped so teams can understand why they should trust them before sharing them more broadly.
Respect governance
The product is built for teams that care about privacy, access boundaries, and approval workflows.
Publish to your team
Turn useful work into reusable team artifacts after the right people have reviewed it.
03 / Where it fits
Where it earns its keep.
Four team contexts where the reviewable workflow pays for itself — places where invisible automation isn't an option and banning AI isn't either.
Analytics engineering
Give analysts and engineers a shared place to review AI-assisted data work before it becomes a team artifact.
Pipeline generation
Move from intent to a reviewable draft that the team can inspect before using.
Governed self-serve BI
Help business users ask better questions while keeping serious data work reviewable by the team.
Workflow prototyping
Explore an analytical workflow quickly, then decide what deserves to become reusable.
04 / Try it
PulseQL v1.1 — releasing soon.
Builds for macOS, Windows, and Linux are in late-stage testing. Drop a note and you'll be the first to know when downloads go live — or read the case study for how the workflow was designed in the meantime.
macOS
releasing soonv1.1 builds will ship as .dmg.
Windows
releasing soonv1.1 builds will ship as .exe · .msi.
Linux
releasing soonv1.1 builds will ship as .deb · .rpm · .AppImage.