Debugging 100-step AI workflows meant manually sifting logs. Now, engineers trace inferences to isolate errors and rapidly deploy models.
An AI assistant for in-house legal teams processes complex multistage inferences across heterogeneous data sources, including messaging platforms, support tickets, and legal documents.
As the platform's language model capabilities expanded, workflows containing up to 100 nested inferences became increasingly difficult to manage....
AI-powered legal assistant for contract review, drafting, and policy automation.
Framework and developer platform for building LLM-powered applications.
Wordsmith's Model performance monitoring is part of this use case:
Related implementations across industries and use cases
Tracking spend for 300M AI agent runs was a black box. Real-time tracing now lets finance pinpoint costs and update pricing within hours.
Black-box AI logic hid costly retry loops. Granular traces exposed redundant tool calls, enabling engineers to optimize agent reasoning.
Inconsistent manual call notes caused billing errors. Now, zero-retention AI turns VoIP calls into synced case and billing entries.
Tracking spend for 300M AI agent runs was a black box. Real-time tracing now lets finance pinpoint costs and update pricing within hours.
Black-box AI logic hid costly retry loops. Granular traces exposed redundant tool calls, enabling engineers to optimize agent reasoning.
Manual research took days. Consultants now generate cited summaries in minutes, validating findings instantly during client meetings.
Infrastructure compliance checks took months. Now, engineers use AI to parse massive datasets, cutting final review cycles by up to 90%.
A 200% yearly data expansion bottlenecked global operations. Now, AI accelerates coding, drafts recipe cards, and resolves inquiries.
Moderation couldn't keep pace with 600M users. AI agents now filter toxicity while models recognize 2.5B objects to refine search.
Debugging 100-step AI workflows meant manually sifting logs. Now, engineers trace inferences to isolate errors and rapidly deploy models.
An AI assistant for in-house legal teams processes complex multistage inferences across heterogeneous data sources, including messaging platforms, support tickets, and legal documents.
As the platform's language model capabilities expanded, workflows containing up to 100 nested inferences became increasingly difficult to manage....
AI-powered legal assistant for contract review, drafting, and policy automation.
Framework and developer platform for building LLM-powered applications.
Wordsmith's Model performance monitoring is part of this use case:
Related implementations across industries and use cases
Tracking spend for 300M AI agent runs was a black box. Real-time tracing now lets finance pinpoint costs and update pricing within hours.
Black-box AI logic hid costly retry loops. Granular traces exposed redundant tool calls, enabling engineers to optimize agent reasoning.
Inconsistent manual call notes caused billing errors. Now, zero-retention AI turns VoIP calls into synced case and billing entries.
Tracking spend for 300M AI agent runs was a black box. Real-time tracing now lets finance pinpoint costs and update pricing within hours.
Black-box AI logic hid costly retry loops. Granular traces exposed redundant tool calls, enabling engineers to optimize agent reasoning.
Manual research took days. Consultants now generate cited summaries in minutes, validating findings instantly during client meetings.
Infrastructure compliance checks took months. Now, engineers use AI to parse massive datasets, cutting final review cycles by up to 90%.
A 200% yearly data expansion bottlenecked global operations. Now, AI accelerates coding, drafts recipe cards, and resolves inquiries.
Moderation couldn't keep pace with 600M users. AI agents now filter toxicity while models recognize 2.5B objects to refine search.