Single-step workflows failed at deep research. Autonomous agents now run parallel investigations to deliver structured data in seconds.
A search technology provider building an autonomous agent capable of exploring the web to find structured information for complex user queries.
Moving beyond simple question-answering required an architecture capable of handling long-running, autonomous workflows. A rigid, single-step process...
“The observability – understanding the token usage – that LangSmith provided was really important. It was also super easy to set up.”
AI-native search engine and API for developers and LLM applications.
Framework and developer platform for building LLM-powered applications.
Related implementations across industries and use cases
Static workflows bottlenecked complex tasks. Now, Claude coordinates 8 agents to generate unique execution strategies for every query.
Manual review of sensitive files took two days. AI agents now finish the work in one hour.
Mapping workflow logic once took weeks. Now, users build autonomous Claude agents in minutes to reason through multi-step tasks.
Tax pros spent weeks sifting hundreds of sources. AI now synthesizes millions of documents into cited answers in seconds.
Analysts stitched insights from scattered PDFs. AI now retrieves buried data instantly, cutting memo creation from 2 days to 0.5.
Scattered spreadsheets couldn't catch AI hallucinations. Now, automated LLM judges evaluate every prompt change to block regressions.
Moderation couldn't keep pace with 600M users. AI agents now filter toxicity while models recognize 2.5B objects to refine search.
Hundreds of pages per board book slowed director prep. Now, isolated AI securely condenses sensitive materials into actionable briefs.
Experts spent 15 minutes pulling data from scattered systems. Natural language prompts now generate detailed reports instantly.
Single-step workflows failed at deep research. Autonomous agents now run parallel investigations to deliver structured data in seconds.
A search technology provider building an autonomous agent capable of exploring the web to find structured information for complex user queries.
Moving beyond simple question-answering required an architecture capable of handling long-running, autonomous workflows. A rigid, single-step process...
“The observability – understanding the token usage – that LangSmith provided was really important. It was also super easy to set up.”
AI-native search engine and API for developers and LLM applications.
Framework and developer platform for building LLM-powered applications.
Related implementations across industries and use cases
Static workflows bottlenecked complex tasks. Now, Claude coordinates 8 agents to generate unique execution strategies for every query.
Manual review of sensitive files took two days. AI agents now finish the work in one hour.
Mapping workflow logic once took weeks. Now, users build autonomous Claude agents in minutes to reason through multi-step tasks.
Tax pros spent weeks sifting hundreds of sources. AI now synthesizes millions of documents into cited answers in seconds.
Analysts stitched insights from scattered PDFs. AI now retrieves buried data instantly, cutting memo creation from 2 days to 0.5.
Scattered spreadsheets couldn't catch AI hallucinations. Now, automated LLM judges evaluate every prompt change to block regressions.
Moderation couldn't keep pace with 600M users. AI agents now filter toxicity while models recognize 2.5B objects to refine search.
Hundreds of pages per board book slowed director prep. Now, isolated AI securely condenses sensitive materials into actionable briefs.
Experts spent 15 minutes pulling data from scattered systems. Natural language prompts now generate detailed reports instantly.