Plurai
Plurai is the real-world trust platform for AI agents, built for simulation-driven evaluation, protection, and optimization that turns agents into trusted, continuously improving production systems. It helps teams train evals and guardrails tailored to their use case, bridging the gap from prototype to reliable production at scale. Plurai’s simulation platform prepares agents for the real world, not the lab, with hyper-realistic, product-tailored experimentation and evaluation that covers production complexity. It generates authentic multi-turn scenarios, personas, required artifacts, and tool mocking, using organizational PRDs, relevant sources, and policies to build a knowledge graph and expand edge-case coverage. Instead of relying on static datasets, manual test creation, or inconsistent LLM-as-a-judge methods, Plurai groups evaluations into structured, runnable experiments so teams can test new versions, measure regressions, and validate improvements before release.
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Phinite
Phinite provides shared infrastructure for building, deploying, and governing AI agents across orchestration, security, observability, lifecycle management, and environment promotion — so engineering teams don't rebuild these layers for every new agent use case.
Core capabilities:
Orchestration for multi-agent systems (agent-to-agent, nested calls)
Deep session-level observability: execution timelines, decision variables, tool calls, latency/cost tracking
Private Agent Registry for skill discoverability
Eval suite for accuracy/safety benchmarking
Dev-to-Production workflow with environment promotion
Kubernetes-native deployment, VPC-internal deployability
SOC 2 Type 2 compliance
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Forsy
Forsy is built around authentic human signal from real agent workflows, helping teams capture, understand, and trade agent trajectory data across the agent stack. It tracks agent work in real time as it happens, rather than reconstructing activity afterward, creating native capture for traces, tasks, and toolchain activity. It is designed for full coverage across everyday tasks, specialized workflows, and different domains, giving teams one engine for trajectory data across the agents they already use. Forsy turns AI agents into strategic assets by making authentic workflow data discoverable, licensable, and sellable through a market for agent data. Its high-fidelity data is purpose-built for teams building more capable and reliable agents, helping them access the kinds of real workflow traces needed to improve agent behavior, reliability, and evaluation.
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JetBrains Air
Air is an agentic development environment created by JetBrains that allows developers to delegate coding tasks to multiple AI agents and manage them within a single, unified workspace. Instead of functioning as a simple chat-based assistant, it is designed as a full development environment where tools are built around AI agents, enabling users to guide, supervise, and refine their output more effectively. Developers can run several agents concurrently, each working on different tasks in isolated environments, which helps prevent conflicts and improves productivity when handling complex projects. It supports integration with multiple AI systems such as Claude, Gemini, Codex, and other coding agents, allowing flexible, model-agnostic workflows within the same interface. Users can define tasks with rich context by referencing specific files, commits, classes, or code elements, ensuring that the agents generate more accurate and relevant results based on the actual codebase.
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