AI that drafts and summarizes hands the real work back. Claude finishes it—ticket triage, contract review—for 350,000 organizations.
An enterprise software company behind Jira, Confluence, and 20+ collaboration tools used by more than 350,000 organizations, with AI now built into every product it ships.
Atlassian's customers want agents to handle real, consequential work, from reviewing contracts to triaging support tickets, not just summarize...
“We're good at building UIs for humans. The next muscle is making sure those capabilities are usable by agents as well. How do I make sure agents are an equivalent customer of our software?”
Enterprise collaboration and project management software for development and business teams.
Anthropic is a technology company specializing in artificial intelligence and machine learning solutions.
Atlassian's Workflow automation is part of this use case:
Related implementations across industries and use cases
Scattered data and basic coding tools bottlenecked engineers. A 9-agent AI workflow shifts them from writing code to directing AI teams.
Same work tracked in four disconnected tools. AI pulls live context from all of them—drafts land ready to sharpen, not start.
Rigid prompts limited AI to isolated tasks. Now, a central reasoning model coordinates agents to plan and execute complex workflows.
Underperforming agents meant engineers rewriting prompts by hand and guessing. Now a self-correcting system reads scores and rewrites them.
Leaning on external APIs for sensitive government workflows cost MISA control and cash. On-premise AI factory cut it.
Surging calls caused long holds and overtime. A 24/7 AI voice agent handles routine payroll, freeing 700 HR partners for advisory work.
Keyword bots bottlenecked 100 agents supporting millions. Now, AI resolves FAQs, freeing staff to mine chat logs for product feedback.
Software updates were tied to rigid vehicle production cycles. A GenAI platform now frees 5,000 developers to release code independently.
Scattered AI tools and manual document searches slowed engineers. Now, a unified AI rapidly retrieves specialized technical answers.
AI that drafts and summarizes hands the real work back. Claude finishes it—ticket triage, contract review—for 350,000 organizations.
An enterprise software company behind Jira, Confluence, and 20+ collaboration tools used by more than 350,000 organizations, with AI now built into every product it ships.
Atlassian's customers want agents to handle real, consequential work, from reviewing contracts to triaging support tickets, not just summarize...
“We're good at building UIs for humans. The next muscle is making sure those capabilities are usable by agents as well. How do I make sure agents are an equivalent customer of our software?”
Enterprise collaboration and project management software for development and business teams.
Anthropic is a technology company specializing in artificial intelligence and machine learning solutions.
Atlassian's Workflow automation is part of this use case:
Related implementations across industries and use cases
Scattered data and basic coding tools bottlenecked engineers. A 9-agent AI workflow shifts them from writing code to directing AI teams.
Same work tracked in four disconnected tools. AI pulls live context from all of them—drafts land ready to sharpen, not start.
Rigid prompts limited AI to isolated tasks. Now, a central reasoning model coordinates agents to plan and execute complex workflows.
Underperforming agents meant engineers rewriting prompts by hand and guessing. Now a self-correcting system reads scores and rewrites them.
Leaning on external APIs for sensitive government workflows cost MISA control and cash. On-premise AI factory cut it.
Surging calls caused long holds and overtime. A 24/7 AI voice agent handles routine payroll, freeing 700 HR partners for advisory work.
Keyword bots bottlenecked 100 agents supporting millions. Now, AI resolves FAQs, freeing staff to mine chat logs for product feedback.
Software updates were tied to rigid vehicle production cycles. A GenAI platform now frees 5,000 developers to release code independently.
Scattered AI tools and manual document searches slowed engineers. Now, a unified AI rapidly retrieves specialized technical answers.