Gumloop 记录了 379,557 月访问量，月度环比增长为 -21.1%，定价为免费增值，付费，定价请咨询。TypeSafe AI - Jev 记录了 6,148,688 月访问量，增长率为 -36.4%，定价为付费。
Gumloop is a no-code AI agent and automation platform where teams build agents that connect to their tools, browse the web, and complete real business tasks.
TypeSafe AI is an AI lab building machine-native intelligence infrastructure, and Jev is its first System One Model — a model designed to make decisions inside software rather than reply to humans. Instead of returning strings, Jev accepts structured questions and returns typed decisions with calibrated confidence scores, so applications can act autonomously when confidence is high and escalate for human review when it is not. TypeSafe reports roughly 193x faster and 444x cheaper performance on System One workloads compared with general-purpose LLMs.
| 维度 / 指标 | | |
|---|---|---|
| 官方域名 | gumloop.com | typesafe.ai |
| 定价模式 | 免费增值，付费，定价请咨询 | 付费 |
| 月访问量 | 37.96万 (379,557) | 614.87万 (6,148,688) |
| 月度环比流量变化 | -10.14万 (-21.1%) | -351.3万 (-36.4%) |
| 主要市场与份额 | 🇺🇸 美国 (36.1%) | 🇺🇸 美国 (26.4%) |
| 直接访问 / 月 | 12.56万 | 314.11万 |
| 用户评分 | 4.4 | 4.2 |
| 支持的平台 | 网站 | 网站 |
Gumloop is a no-code AI agent and automation platform where teams build agents that connect to their tools, browse the web, and complete real business tasks.
Describe the outcome you want and let teammates who understand the problem assemble the agent — no scripting or learning curve required.
Wire agents into Slack, HubSpot, Salesforce, Gmail, Gong, NetSuite, Shopify and hundreds more tools, then fire them on schedules, webhooks or events.
Agents sign in with saved logins or 1Password, browse from trusted connections, clear CAPTCHAs, and hand the live session to a human when needed.
Run 35+ models from Anthropic, OpenAI, Google, xAI and open-source providers, or bring your own API keys, with per-agent access control.
TypeSafe AI is an AI lab building machine-native intelligence infrastructure, and Jev is its first System One Model — a model designed to make decisions inside software rather than reply to humans. Instead of returning strings, Jev accepts structured questions and returns typed decisions with calibrated confidence scores, so applications can act autonomously when confidence is high and escalate for human review when it is not. TypeSafe reports roughly 193x faster and 444x cheaper performance on System One workloads compared with general-purpose LLMs.
Jev outputs typed decisions that application code can act on directly, rather than prose that must be parsed and interpreted.
Every decision carries an estimate of how confident the model is, so you can set thresholds for autonomous action versus human escalation.
TypeSafe reports Jev at roughly 193x faster and 444x cheaper than LLM-based workflows on comparable System One tasks, with a price of $42 per billion input tokens.
Because confidence estimates expose uncertainty, Jev is designed to avoid hallucination-style failures in automation, enabling zero-hallucination decision paths where confidence is high.
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