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Vivgrid

Managed skills platform for AI agents — server-side prompts, tools and memory with tracing, evals and global inference

freemiumThree tiers. Free is $0 to start on pay-as-you-go pricing, including managed skills and memory, access to cost-efficient models, geo-distributed LLM providers with low latency, 1-day API access log retention, email support and standard rate limits; approved open-source maintainers can request $200/month in credits. Growth is $25/month and includes everything in Free plus $25 in token credits each month with pay-as-you-go beyond that, higher rate limits for production workloads, access to the latest frontier models (the page names Fable 5, Claude Opus 4.8, GPT-5.5 and DeepSeek V4 Pro), unlimited managed skills and memory, Agent Insights reporting on what customers ask and what it costs, overdraft protection so agents keep running past the balance, 90-day API log retention and advanced support. Enterprise is custom-priced with SSO/SAML, custom SLAs, VPC and private deployments, audit logs, granular access controls, security reviews and volume pricing. The operator is Allegro US, LLC in San Francisco.View full pricing →

Visit Vivgrid

https://vivgrid.com

About Vivgrid

Vivgrid is a managed skills platform for production AI agents, and its central architectural claim is decoupling: system prompts, model selection and tool definitions live server-side rather than shipped inside the client, so changing an agent's behaviour is a configuration update measured in minutes instead of a release cycle and an app-store review. Tools execute as serverless LLM function calls in the cloud, which means API keys and credentials stay in the operator's own cloud rather than being embedded in a distributed client, and a skill updated once propagates to every agent everywhere immediately. Memory is scoped to agents and organisations rather than only to individual users, which matches how a business actually needs recall to work. Around that sit the two capabilities that make the difference between a prototype and something you would put revenue behind: full tracing, where every prompt, tool call and decision is visible in one place so a failed conversation can be traced to the exact step that lost the customer, and pre-release evaluation with guardrails that catch regressions and off-policy behaviour before a customer sees them. Inference runs on a globally distributed GPU network with roughly 50 ms latency, quoted at 22 ms in Paris, 30 ms in Tokyo and 35 ms in Los Angeles.

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Key Features

Prompts, models and tools managed server-side, decoupled from the client
API keys never leave your cloud during serverless tool execution
Full tracing of every prompt, tool call and decision
Pre-release evaluation and guardrails to catch regressions
Memory scoped to agents and organisations, not just users

Tags

ai-agentsllm-toolsobservabilityevaluationfunction-calling
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