A bug sat for years because the fix meant a month of digging. AI traced the fragmented code to draft a solution in three days.
A global revenue platform manages a decade of engineering investment across fragmented codebases built in Java, Ruby, TypeScript, Python, and Scala.
Technical context was scattered across outdated documentation and senior staff, meaning onboarding to new codebases took weeks of manual research....
“Factory has nearly doubled my productivity. It helps me deliver higher-quality code faster, onboard to new codebases more smoothly, review PRs more efficiently, and even brainstorm ideas more effectively.”
AI-powered revenue platform for sales forecasting and pipeline management.
AI software development agents for automating engineering workflows.
Clari's Software engineering is part of this use case:
Related implementations across industries and use cases
Feature requests once sat in backlogs. Now, developers let AI generate working preview branches in minutes for real-time customer review.
Launching one outreach campaign meant clicking through four interfaces. Now customers state the goal; Apollo's assistant runs the full loop.
Devs manually seeded context for complex tasks. Agents now retain memory for weeks, working independently after a single session.
Feature requests once sat in backlogs. Now, developers let AI generate working preview branches in minutes for real-time customer review.
Devs manually seeded context for complex tasks. Agents now retain memory for weeks, working independently after a single session.
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.
A bug sat for years because the fix meant a month of digging. AI traced the fragmented code to draft a solution in three days.
A global revenue platform manages a decade of engineering investment across fragmented codebases built in Java, Ruby, TypeScript, Python, and Scala.
Technical context was scattered across outdated documentation and senior staff, meaning onboarding to new codebases took weeks of manual research....
“Factory has nearly doubled my productivity. It helps me deliver higher-quality code faster, onboard to new codebases more smoothly, review PRs more efficiently, and even brainstorm ideas more effectively.”
AI-powered revenue platform for sales forecasting and pipeline management.
AI software development agents for automating engineering workflows.
Clari's Software engineering is part of this use case:
Related implementations across industries and use cases
Feature requests once sat in backlogs. Now, developers let AI generate working preview branches in minutes for real-time customer review.
Launching one outreach campaign meant clicking through four interfaces. Now customers state the goal; Apollo's assistant runs the full loop.
Devs manually seeded context for complex tasks. Agents now retain memory for weeks, working independently after a single session.
Feature requests once sat in backlogs. Now, developers let AI generate working preview branches in minutes for real-time customer review.
Devs manually seeded context for complex tasks. Agents now retain memory for weeks, working independently after a single session.
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.