Pipeline re-engagement
418 closed-lost opportunities sat unread in the CRM. Athena drafted a cited, approval-gated note for every account where something had changed.
- Before
418 closed-lost opportunities in the CRM. Nobody had time to re-read them.
- What we did
Athena re-read every one against what had changed since: funding (from funding databases), hiring (from hiring data), new leadership (from LinkedIn), new product (from product announcements and news sources). Drafted a note for each that warranted one. Held them in a queue for rep approval in Slack.
- After
Three warm leads in four days. Every note approval-gated; every claim in the note cited.
The agent found the signal. The rep wrote the last sentence.
Re-engagement requires re-reading hundreds of old records against new market data. Athena reads 418 accounts in hours.
From closed-lost CRM records to approved outreach notes
“He wrote the entire stuff. By itself. And I was there, and I was thinking, alright. If I had to write all this stuff, I mean, I would've spent days, days, days.”
“I send that to the programmer and he said, alright. I read your file. I copied the section of the code because he has the right interface, and it works. Wow. Just like magic.”
“Digital worker, it gets spun up, it gets given access to the toolkits that it needs. It gets given access to the data that it needs. Just exists for the period it needs to exist to perform the task. And then it gets torn back down again afterwards.”
“I like that direction, that concept of the agent is the agent. It becomes an entity in its own right with its own ownership and its own missioning, and you get rid of the gray area and the blurry lines.”
“This combination is a winning combination for us, and this is where we see maximum traction, which is how do you apply all the intelligence that you have within [our data platform] and not worry about how you render that output.”
“A lot of people are telling us that, oh, I sold in this package because of this info... I secured this distribution because of the selling assistance help.”
“I am not a programmer. I cannot read a line of program in SQL or anything... The only thing that I'm doing is just writing prompts.”
“I finally got a chance to play around with the computer asset and build out the chatbot you mentioned. It was really impressive.”
“So we use the SDK, and we write that in Python, and it calls Athena majority by API. The results appear in the interface itself.”
“You guys are functioning better because the harness is tested for a longer period of time against enterprise customers.”
Verbatim from customer calls. Customers anonymized.
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