Fill judgment signals like a careful VA - for every company, in parallel.
You already have the list. You need hiring, founder activity, why-now - with proof you can hand an AE. BlitzClaw runs a dedicated research agent on each row, returns value + sources + confidence, and only asks you to review the weak cells.
Built for GTM engineers who use Clay, Claude, and outbound stacks - and still lose evenings to row-by-row research.
- value
- SDR + Enterprise AE open
- path
- careers → ATS → LinkedIn check
- source
- careers.acme.com/jobs
- snippet
- “Enterprise AE, NYC · posted 3d”
- confidence
- 0.86
- if wrong when
- post removed / role filled
This is the unit of delivery - not a rumor in a spreadsheet cell.
The work that still falls on you
Email waterfalls are known paths. Judgment signals are not. Each company wants a different research route - and a decision: put it in the cell, or don’t.
Row 1 Careers page. Real AE post. Easy.
Row 4 No careers. Founder posts after funding. Different path.
Row 12 List is wrong. Discard. Don’t “enrich” garbage.
Row 17 Half-true hiring signal. That hesitation is the product. Fixed workflows don’t solve it.
What you get after a run
Three outcomes GTMEs actually pay time for - not “AI features.”
-
Depth per company
Each row gets its own agent that can choose careers, LinkedIn, news, or discard. Same list. Different paths.
-
Evidence in the cell
Sources, snippet, confidence, and what would change the call. If you can’t defend it, it’s not done.
-
Human work on the exceptions
High-confidence rows ship. Low-confidence land in a review queue. You stop re-researching everyone at 1am.
- Upload the list Companies you already care about.
- Name signal columns Hiring roles, founder activity, why-now. Optional: what you sell.
- Run agents in parallel Dedicated workers fan out across the list - deep research, not one pass over the sheet.
- Review weak cells Challenge proof only where confidence is low. Export the rest.
What this is not
If you only need this table, you already have tools. BlitzClaw is for the other job.
Sheet-wide Claude
Fast. Wide. Shallow. Optimizes for filling the sheet, not finishing the company.
Clay / Claygent
Excellent when the path is known (email waterfalls). Breaks when every row needs different judgment research.
DIY agent farm
Works until you’re the on-call for scrapers, credits, and silent failures at 7am.
BlitzClaw
Depth per company. Parallel across the list. Proof required in every cell. You own the exceptions, not the glue.
Questions GTM engineers ask first
Isn’t this just Claude filling a CSV?
Claude can fill gaps in a sheet - one pass, average path, weak proof. BlitzClaw gives each row a dedicated investigator with tools and path choice, requires evidence, and runs those workers concurrently so depth doesn’t mean serial babysitting.
Is this a Clay alternative?
No. Keep Clay for known-path enrichment. Use BlitzClaw when columns need multi-path judgment research with defendable sources.
Does per-row mean slow?
No. Workers fan out in parallel (AWS Lambda-scale concurrency). Quality is deep; wall-clock is list-scale, not single-threaded.
What about email enrichment?
Optional later. Core product is signal columns with evidence and confidence - the work still eating GTM nights after the waterfall is “done.”
Request early access
For GTMEs who already feel the research tax. No invented customer counts. No sales theater. Tell us your email - we’ll open seats when ready.
One field. That’s the whole ask.