Launching one outreach campaign meant clicking through four interfaces. Now customers state the goal; Apollo's assistant runs the full loop.
A go-to-market platform covering the full sales cycle from prospecting to outreach sequencing and analytics, with 500k+ teams building on its API and 230M+ API calls served monthly.
After nearly a decade of product expansion, customers reported the platform felt overwhelming, with too many modules and manual coordination required...
“We had to write a new sub-agent for every new use case, then wire it into the supervisor and make sure it followed the prescribed path.”
AI sales intelligence and engagement platform for B2B go-to-market teams.
Framework and developer platform for building LLM-powered applications.
Apollo's Sales assistant is part of this use case:
Related implementations across industries and use cases
Untangling 30-call AI interactions consumed developers. Now, support teams use system traces to resolve context issues without engineers.
Rigid prompts limited AI to isolated tasks. Now, a central reasoning model coordinates agents to plan and execute complex workflows.
Dense API docs bottlenecked non-technical users. Now, Claude builds fully configured voice agents from simple plain-text requests.
Dense API docs bottlenecked non-technical users. Now, Claude builds fully configured voice agents from simple plain-text requests.
Stuck orders meant lost revenue for 700k merchants. Instead of just answering questions, an AI agent directly executes back-end fixes.
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.
Tournaments running simultaneously meant an hour of manual checks each. AI agents now run them in minutes, freeing the team to be proactive.
Large AI training jobs meant fighting for preemptible slots or leaving campus. Marlowe gave any lab guaranteed multi-node access on demand.
Launching one outreach campaign meant clicking through four interfaces. Now customers state the goal; Apollo's assistant runs the full loop.
A go-to-market platform covering the full sales cycle from prospecting to outreach sequencing and analytics, with 500k+ teams building on its API and 230M+ API calls served monthly.
After nearly a decade of product expansion, customers reported the platform felt overwhelming, with too many modules and manual coordination required...
“We had to write a new sub-agent for every new use case, then wire it into the supervisor and make sure it followed the prescribed path.”
AI sales intelligence and engagement platform for B2B go-to-market teams.
Framework and developer platform for building LLM-powered applications.
Apollo's Sales assistant is part of this use case:
Related implementations across industries and use cases
Untangling 30-call AI interactions consumed developers. Now, support teams use system traces to resolve context issues without engineers.
Rigid prompts limited AI to isolated tasks. Now, a central reasoning model coordinates agents to plan and execute complex workflows.
Dense API docs bottlenecked non-technical users. Now, Claude builds fully configured voice agents from simple plain-text requests.
Dense API docs bottlenecked non-technical users. Now, Claude builds fully configured voice agents from simple plain-text requests.
Stuck orders meant lost revenue for 700k merchants. Instead of just answering questions, an AI agent directly executes back-end fixes.
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.
Tournaments running simultaneously meant an hour of manual checks each. AI agents now run them in minutes, freeing the team to be proactive.
Large AI training jobs meant fighting for preemptible slots or leaving campus. Marlowe gave any lab guaranteed multi-node access on demand.