One AE held the team's institutional knowledge—90% of his day in Slack. A digital double in his voice freed him to sell.
A software company whose institutional knowledge was fragmented across Gong, Salesforce, and Slack, with new hires depending on a handful of long-tenured employees for everything from product context to process guidance.
The first account executive was spending 90% of his day answering internal Slack questions, leaving no capacity for actual sales work. Expert...
“I have the opportunity to think more about the art of marketing and have my data engineer too—my Notion Custom Agent.”
Inference platform for deploying and scaling machine learning models in production.
A new tool that blends your everyday work apps into one. It's the all-in-one workspace for you and your team.
Baseten's Expert Q&A is part of this use case:
Related implementations across industries and use cases
Onboarding across four platforms required weeks of shadowing. Now, an AI assistant instantly answers Slack queries so new hires self-serve.
One BD person, 3–10 leads daily, days behind on research. Clients moved on. A plugin now scores fit, creates deals, and posts to Slack.
Staff spent hours manually scanning transcripts. Agents now monitor feeds and update sales docs before the team logs on.
Staff spent hours manually scanning transcripts. Agents now monitor feeds and update sales docs before the team logs on.
Similarity search mixed up Q3 and Q4 earnings. Hybrid AI now anchors retrieval with keywords and learns from human fixes instantly.
Scattered data and basic coding tools bottlenecked engineers. A 9-agent AI workflow shifts them from writing code to directing AI teams.
Sequential AI testing bottlenecked development. Engineers built a concurrent, code-first pipeline to evaluate agent responses in seconds.
Energy market research that took weeks now closes same-day. Staff freed from chasing information to make the calls that matter.
With 99% of records missing metadata, teams sifted unlabeled databases. Now, AI generates column descriptions for data experts to verify.
One AE held the team's institutional knowledge—90% of his day in Slack. A digital double in his voice freed him to sell.
A software company whose institutional knowledge was fragmented across Gong, Salesforce, and Slack, with new hires depending on a handful of long-tenured employees for everything from product context to process guidance.
The first account executive was spending 90% of his day answering internal Slack questions, leaving no capacity for actual sales work. Expert...
“I have the opportunity to think more about the art of marketing and have my data engineer too—my Notion Custom Agent.”
Inference platform for deploying and scaling machine learning models in production.
A new tool that blends your everyday work apps into one. It's the all-in-one workspace for you and your team.
Baseten's Expert Q&A is part of this use case:
Related implementations across industries and use cases
Onboarding across four platforms required weeks of shadowing. Now, an AI assistant instantly answers Slack queries so new hires self-serve.
One BD person, 3–10 leads daily, days behind on research. Clients moved on. A plugin now scores fit, creates deals, and posts to Slack.
Staff spent hours manually scanning transcripts. Agents now monitor feeds and update sales docs before the team logs on.
Staff spent hours manually scanning transcripts. Agents now monitor feeds and update sales docs before the team logs on.
Similarity search mixed up Q3 and Q4 earnings. Hybrid AI now anchors retrieval with keywords and learns from human fixes instantly.
Scattered data and basic coding tools bottlenecked engineers. A 9-agent AI workflow shifts them from writing code to directing AI teams.
Sequential AI testing bottlenecked development. Engineers built a concurrent, code-first pipeline to evaluate agent responses in seconds.
Energy market research that took weeks now closes same-day. Staff freed from chasing information to make the calls that matter.
With 99% of records missing metadata, teams sifted unlabeled databases. Now, AI generates column descriptions for data experts to verify.