Manual testing left engineers prioritizing fixes by intuition. Now, an AI classifier calculates error impact to target critical updates.
An enterprise application generation platform that allows over 10,000 companies to build custom admin panels, dashboards, and internal workflows.
After launching an AI development assistant, the engineering team relied on manual dog-fooding sessions and intuition to identify failure modes. As...
“This allowed us to shuffle some priorities, go and address that specific pointed problem, take that on as a project, and monitor its success afterwards.”
Development platform for building internal software, apps, and AI workflows.
AI observability and evaluation platform that helps developers build, test, and monitor LLM-powered applications.
Related implementations across industries and use cases
Complex queries bottlenecked access to insights. Agents now translate plain language into expert dashboards and root cause analysis.
Developers spent 10+ hours a week testing and documenting APIs. Now, an AI assistant automatically writes tests and updates specs.
Reviewers struggled to predict how code ripples through the system. AI now flags cross-service risks that cause outages.
Analysts spent days building reports from slow, siloed tools. Now, they ask a question and an AI agent instantly generates an accurate chart.
Solopreneurs guessed at growth tactics. AI now queries 10+ data sources to trigger specific SEO and pricing workflows.
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.
Analyzing 10TB of weekly telemetry took IT specialists days. Now, engineers ask AI in natural language to instantly retrieve charts.
Experts spent 15 minutes pulling data from scattered systems. Natural language prompts now generate detailed reports instantly.
Manual testing left engineers prioritizing fixes by intuition. Now, an AI classifier calculates error impact to target critical updates.
An enterprise application generation platform that allows over 10,000 companies to build custom admin panels, dashboards, and internal workflows.
After launching an AI development assistant, the engineering team relied on manual dog-fooding sessions and intuition to identify failure modes. As...
“This allowed us to shuffle some priorities, go and address that specific pointed problem, take that on as a project, and monitor its success afterwards.”
Development platform for building internal software, apps, and AI workflows.
AI observability and evaluation platform that helps developers build, test, and monitor LLM-powered applications.
Related implementations across industries and use cases
Complex queries bottlenecked access to insights. Agents now translate plain language into expert dashboards and root cause analysis.
Developers spent 10+ hours a week testing and documenting APIs. Now, an AI assistant automatically writes tests and updates specs.
Reviewers struggled to predict how code ripples through the system. AI now flags cross-service risks that cause outages.
Analysts spent days building reports from slow, siloed tools. Now, they ask a question and an AI agent instantly generates an accurate chart.
Solopreneurs guessed at growth tactics. AI now queries 10+ data sources to trigger specific SEO and pricing workflows.
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.
Analyzing 10TB of weekly telemetry took IT specialists days. Now, engineers ask AI in natural language to instantly retrieve charts.
Experts spent 15 minutes pulling data from scattered systems. Natural language prompts now generate detailed reports instantly.