Chrome Extension for Real-Time Malicious Address Detection
Jevscan is a Chrome extension that detects malicious addresses and transactions on Etherscan in real-time, utilizing Jev from Typesafe AI.
view details →ops use cases
188 published use cases filed under ops.
AI Agent Integration with Jev by Typesafeai
An experiment integrating Jev into a SaaS AI Agent shows remarkable speed, responding faster than user input. It operates at approximately 100 times lower cost than traditional LLMs and efficiently directs requests needing a full LLM.
view details →Jev Integration for Orus Agents
Jev, a model from TypeSafe AI, is now integrated into Orus agents to review proposed trades. It can approve, refuse, or request further observation based on user-defined conditions.
view details →Autonomous Knowledge Reliability Agent Setup
Set up Oracle as an autonomous agent in Notion to manage schema health, eliminate duplicate cards, and perform scheduled database sweeps.
view details →Collaboration Between Agents Yields 4,700 Leads
A partnership between Instinct and Muse agents resulted in 4,700 leads harvested and validated without duplication. They also created a work contract independently.
view details →AI Agent Drives Robot Using PyTorch and Depth Estimation
Meta's Muse successfully drove a robot by installing PyTorch and Depth Anything V2 in its own VM to estimate distance and navigate.
view details →Argument Validator Performance Comparison
The argument validator in PatchOpsAi, built with Luna, shows performance metrics of 1.1–2.8 seconds, while @typesafeai's Jev took 195–251 ms on the validator and 221–901 ms on the scanner.
view details →Trading Bot for AAPL, TSLA, NVDA
This trading bot monitors AAPL, TSLA, and NVDA in USDG, providing buy, sell, or hold recommendations through a single call. Built as a fun project using 3Route, Jev (TypeSafe), x402, and Robinhood Chain.
view details →Grok Bot for Landlord Outreach
Chase is a Grok Bot designed for landlord outreach, creating LLC rental-owner lists and mail-merge packs. It also facilitates LinkedIn connection waves for property management and buy/sell activities.
view details →Improved Model Routing and Action Review with Jev
The integration of Jev from @typesafe_ai replaced three steps in Prio, achieving 100% accuracy in model routing and significantly reducing action review time from 5 seconds to 0.25 seconds for clear cases.
view details →Jev Adapter for Prompt Classification
The Jev adapter classifies prompts before they reach the LLM, reducing token consumption and costs. It provides classification and confidence scores, marking prompts for review when confidence is near the threshold.
view details →3D Model Viewer Development Using Muse
A 3D Model Viewer is being built to list parts for easier product assembly. The viewer utilizes GLB files created by Muse, with a preference for a version from Claude Opus.
view details →Tiny Support Ticket Classifier Using JEV
This support ticket classifier built with JEV categorizes tickets, assesses urgency, and determines if human intervention is needed. It has achieved 100% accuracy in initial tests and operates at a lower cost.
view details →Content-Aware PII Redaction in Postgres
This system uses Jev to tag personal information in support messages, allowing selective redaction. The redact() SQL function ensures that only sensitive data is masked while keeping the rest of the message readable.
view details →Visit Tracking and Dashboard Setup with Muse AI
Implemented visit tracking across three sites and created a private visits dashboard. Addressed issues with placeholder numbers and shared insights on OpenAI's model misbehavior.
view details →Client Built on Mac Mini Using Robinhood MCP
A small client was developed on a Mac mini utilizing Robinhood MCP. Initially using Codex CLI, the project was adapted to function independently.
view details →Sales Bot Built with Dr Eggbot
A sales bot was created using Dr Eggbot in Grok Bot, achieving impressive stats on the first day after launching the website without any marketing spend.
view details →Contract Review Assistance with ChatGPT
Utilize a ChatGPT agent to review contracts, focusing on seller and buyer risks. It highlights key areas for attention, streamlining the redline markup process.
view details →User Reluctance to Trust AI for Critical Tasks
The user expresses skepticism about AI's reliability for critical tasks due to model hallucinations. They have also established a server with personal tools that Poke accesses, preferring not to redo their setup.
view details →Trading Bot Built with Jev
This trading bot determines whether to buy or sell based on asset pair price feeds and executes real trades. It utilizes Monad to place orders on Kuru's on-chain order book every 300ms.
view details →Mapwright: Document Architect for Agent-Fleet Maps
Mapwright integrates with Grok Bot and Dr Eggbot to maintain coherent maps for agent fleets. It features a single source of truth index, differentiating live and dead paths while ensuring structural changes are managed by the CoS.
view details →Automated Tool Evaluation with Claude Code
Claude Code evaluates new tools based on your existing setup, streamlining the decision-making process. This week, it assessed Paseo, an open-source app for managing sessions across devices.
view details →CRM Development by Jason LK
Jason LK mentions the development of a CRM, indicating its functionality.
view details →Muse's User-Friendly AI Capabilities
Muse simplifies AI interactions, allowing users to create and manage contracts effortlessly. Its intuitive design has impressed users of all ages, making advanced AI accessible to a broader audience.
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