An anonymous website visitor becomes a researched, personalized outreach package — a written email plus a three-slide deck — in about 90 seconds.
Built for a B2B SaaS go-to-market team. Intent-data tools already tell you which company was on your pricing page an hour ago and who from it. The signal is solved. The bottleneck is what comes next: turning that signal into a personalized, non-generic touch takes a rep twenty to thirty minutes of research per visitor, so most signals go cold unworked. This workflow closes that gap to about a minute and a half.
Context
B2B SaaS engagement
Run Time
~90 Seconds
Output
Email + 3-Slide Deck
Reusability
Any Team With Intent Data
De-anonymization tools like RB2B and Vector have made the hard part easy. You know the visitor, the company, the page they read, and how they got there. What they don't do is the work. A rep still has to research the company, find the right angle, name the right buyer, and write something that doesn't read like a template. At twenty-plus minutes apiece, that step is where high-intent signals quietly die. The team had the data firehose and no way to drink from it fast enough.
One command runs the whole chain. It pulls a real visitor, researches them live on the open web, maps them to a single sharp play, writes the email, and renders the deck.
Pulls a real identified visitor from the intent platform and scores it against the engagement's ICP: industry, revenue tier, title relevance, recency, and hot-page signals.
Searches the open web for the company's current retention strategy, news from the last 30 days, and the most likely buyer by name or role.
Picks the single best-fit product surface and the closest peer case study. One specific play, never a kitchen-sink feature list.
Drafts a personalized email in the operator's own voice, under 120 words, opening on a specific public fact about the company.
Builds a three-slide deck (cover, the mapping, proof and next step) and opens it in the browser.
Writes a research-notes file citing the source for every claim, so any line in the email can be audited on the spot.
Speed is easy. Speed you can put in front of a customer is not. Every substantive claim the workflow makes about a visitor's company has to cite a real URL or a knowledgebase file. If it can't be cited, it gets cut or flagged unverified — never invented. A receipts file ships with every run, so if anyone in the room challenges a line, the source is right there.
It also drafts, it does not send. The email lands as a file the operator reviews and sends themselves. It is read-only on the CRM. The human keeps the judgment and the send button; the machine does the twenty minutes of work.
It does one visitor at a time, on purpose. The value is one sharp artifact, not a batch blast. I validated it live three times back-to-back in front of a company team before a sixty-person demo — three different real visitors, three different personalized packages, no repeats, each in about ninety seconds. The workflow is parameterized by ICP, voice, and knowledgebase, so the same machine runs for a different company by swapping three inputs. Any team sitting on intent data it isn't working fast enough can use it tomorrow.
I build working AI tools for businesses, not slide decks about AI. If you have a signal you can't act on fast enough, let's talk.