Building agents took 4-5 months, with no guarantee of production. A 4-person team built a platform cutting that to under a day.
A software platform for HR, finance, and IT used by more than half the Fortune 500, operating under some of the strictest security and data governance requirements in enterprise software.
Leadership set an ambitious goal for agents in production, but product teams needed a platform supporting both rapid prototyping and production...
“Anytime there was some AI concept that LangChain had put out, we tried to build a Python SDK for that same concept, but at Workday.”
Cloud platform for enterprise human resources, finance, and business planning.
Framework and developer platform for building LLM-powered applications.
Workday's Agent development platform is part of this use case:
Related implementations across industries and use cases
Siloed models couldn't reason across domains; a supervisor now routes read, retrieval, and action agents across HR, IT, and finance.
Routine cloud setups tied up engineers for days. Now, developers ask AI agents in Jira and Webex to provision resources instantly.
Underperforming agents meant engineers rewriting prompts by hand and guessing. Now a self-correcting system reads scores and rewrites them.
SUnderperforming agents meant engineers rewriting prompts by hand and guessing. Now a self-correcting system reads scores and rewrites them.
Manually tuning prompts in secure environments was slow and inaccurate. Now, automated feedback loops let engineers refine AI instantly.
Thousands of tables tracking the same metrics differently. No one knew which to trust — not humans, not AI. One governed layer changed that.
On-chain AI agents took weeks of stitching and ran trapped on local machines. BNB Agent Studio ships them globally in 15 minutes.
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.
Building agents took 4-5 months, with no guarantee of production. A 4-person team built a platform cutting that to under a day.
A software platform for HR, finance, and IT used by more than half the Fortune 500, operating under some of the strictest security and data governance requirements in enterprise software.
Leadership set an ambitious goal for agents in production, but product teams needed a platform supporting both rapid prototyping and production...
“Anytime there was some AI concept that LangChain had put out, we tried to build a Python SDK for that same concept, but at Workday.”
Cloud platform for enterprise human resources, finance, and business planning.
Framework and developer platform for building LLM-powered applications.
Workday's Agent development platform is part of this use case:
Related implementations across industries and use cases
Siloed models couldn't reason across domains; a supervisor now routes read, retrieval, and action agents across HR, IT, and finance.
Routine cloud setups tied up engineers for days. Now, developers ask AI agents in Jira and Webex to provision resources instantly.
Underperforming agents meant engineers rewriting prompts by hand and guessing. Now a self-correcting system reads scores and rewrites them.
SUnderperforming agents meant engineers rewriting prompts by hand and guessing. Now a self-correcting system reads scores and rewrites them.
Manually tuning prompts in secure environments was slow and inaccurate. Now, automated feedback loops let engineers refine AI instantly.
Thousands of tables tracking the same metrics differently. No one knew which to trust — not humans, not AI. One governed layer changed that.
On-chain AI agents took weeks of stitching and ran trapped on local machines. BNB Agent Studio ships them globally in 15 minutes.
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.