Scalekit
Scalekit is an authentication platform for AI agents that enables secure, user-delegated access to SaaS applications, APIs, databases, and MCP servers. Rather than relying on shared service accounts, Scalekit allows agents to perform actions on behalf of individual users using their own identities, permissions, and approved scopes. The platform manages OAuth flows, credential storage, authorization, token refresh, and tool execution behind the scenes, simplifying agent development. It includes over 100 connectors, support for custom integrations, and compatibility with popular AI frameworks. Scalekit also provides detailed auditing, encrypted credential storage, and enterprise deployment options for production environments. By handling the authentication and authorization infrastructure, Scalekit helps developers build secure AI agents that integrate with external systems at scale.
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asqav
asqav is an AI governance and security platform designed to make AI agents audit-ready by providing real-time monitoring, enforcement, and verifiable proof of every action taken by an agent. It introduces a lightweight SDK that allows developers to integrate governance directly into their agents in just a few lines of code, enabling continuous oversight across the full lifecycle of AI operations. It includes behavioral monitoring to detect issues such as drift, rate limits, and scope violations, along with advanced threat detection that identifies prompt injections, exposure of sensitive data, toxic outputs, and other risks. It enforces policy through configurable “policy gates,” which apply per-agent rules, preflight checks, and dynamic approvals before actions are executed, ensuring that agents operate within defined boundaries. asqav also provides automated incident response capabilities, including the ability to suspend, quarantine, or escalate risky agents.
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Cloptima
Cloptima is an AI and cloud FinOps platform that brings LLM spend governance, multicloud cost intelligence, Kubernetes optimization, query analysis, and engineering cost controls into one operating model. Its AI gateway lets teams use their own OpenAI, Anthropic, Gemini, Vertex AI, and Amazon Bedrock credentials behind encrypted controls, then apply virtual keys, model policies, token limits, budgets, guardrails, and attribution before calls reach providers. Spend analytics break down usage by provider, model, team, application, environment, user, agent session, tool, workflow, and dimensions, while agent controls track retries, loops, tool calls, and runaway-cost risk. Exact and semantic response caching can reduce repeated usage, and intelligent routing can shift eligible traffic to cheaper or faster models with canary rollout and rollback if quality, latency, or errors regress.
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LLMeter
LLMeter is an open source AI cost monitoring platform that gives developers one dashboard for tracking spend across OpenAI, Anthropic, DeepSeek, OpenRouter, Mistral, and Azure OpenAI. Teams connect read-only provider keys and can see real costs, daily trends, model-level breakdowns, and optimization opportunities in about 30 seconds without installing an SDK, changing endpoints, or routing production traffic through a proxy. Because requests continue going directly to the model provider, LLMeter adds no latency, does not become a point of failure, and never sees prompts or completions. Budget alerts warn teams before spending crosses daily or monthly limits, while anomaly detection identifies unexpected usage spikes before they grow. The dashboard shows which providers, models, endpoints, customers, and environments are driving costs, and OpenRouter support extends visibility across more than 500 models.
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