Braintrust
Code generation
Feature requests once sat in backlogs. Now, developers let AI generate working preview branches in minutes for real-time customer review.
- 50% team adoption of Codex within one month
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Technical context was scattered across outdated documentation and senior staff, meaning onboarding to new codebases took weeks of manual research....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.
Devs manually seeded context for complex tasks. Agents now retain memory for weeks, working independently after a single session.
Rapid code changes left documentation outdated for weeks. An AI agent now monitors every commit and auto-generates PRs to fix discrepancies.
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.
On-premise systems, dispersed and brittle, bottlenecked every release. AI agents now run routine dev steps — hours cut to minutes.
A mistranslated word could derail global R&D projects. Now, researchers instantly refine technical papers & communicate seamlessly across languages.
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.
Devs manually seeded context for complex tasks. Agents now retain memory for weeks, working independently after a single session.
Rapid code changes left documentation outdated for weeks. An AI agent now monitors every commit and auto-generates PRs to fix discrepancies.
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.
On-premise systems, dispersed and brittle, bottlenecked every release. AI agents now run routine dev steps — hours cut to minutes.
A mistranslated word could derail global R&D projects. Now, researchers instantly refine technical papers & communicate seamlessly across languages.