Jev Task Routing Demos

Filtering 3,412 leads with 20,472 fast decisions so Grok opens only high-signal records

Classifying two million RedReplier rows at about 5× the previous speed while improving quality

Checking uploaded resumes against explicit conditions and supporting every verdict with a quoted passage

Routing a deal to approval, document requests, or parallel sales, finance, and legal reviews while keeping the final call human

Reading 156,703 Gmail messages from 14 years, inventing labels when needed, and organizing them into 90 categories

Comparing Jev with two Gemini Flash models on 612 banking rows across accuracy, time, and cost

Returning four typed ticket decisions at once and closing 13 tickets without streamed prose or JSON reparsing

Sorting incoming email and prioritizing follow-up work to save an estimated two to three hours each week

Reading first-week PostHog events for 672 signups and answering five triage questions in 32 seconds

Scoring task, difficulty, privacy, and web need with four probabilities before routing to the right model

Scoring each Notion inbox note and auto-routing only confident items to tasks, decisions, or knowledge

Triaging 998 Y Combinator prospects from self-descriptions and three yes-or-no growth questions in 22.4 seconds

Reading 1,000 GitHub issues across 20 top repositories in eight seconds to find existing fixes and stalled pull requests

Filtering research links before deeper analysis so low-value threads do not consume agent context or tokens

Scoring 1,000 old leads and narrowing the sales team's call list to the 50 highest-value prospects

Sorting 20,000 emails into four bins in 4.6 seconds for $0.15 at a reported 99.7% accuracy

Building a call-center demo in 10 minutes to route inquiries between AI and human operators

Coordinating six micro-agents to handle company operations and reporting net cash flow growing from $150 to $6,888 in 48 hours

Analyzing each support ticket in one call with seven typed classifications, scores, and boolean judgments in about 500 ms

Routing support tickets by team, urgency, severity and customer mood in one call

Automating fraud screening, buying-signal triage and viral-content monitoring in three workflows

Proposing ticket departments, flagging uncertain cases for review and measuring routing accuracy

Watching 267 deal posts against price requests, making 4,005 judgments and suppressing 63.3% of posts

Classifying posts in 70–500 ms, triaging email instantly and routing low-confidence cases to local Ollama