doteval
doteval is an AI-assisted evaluation workspace that simplifies the creation of high-signal evaluations, alignment of LLM judges, and definition of rewards for reinforcement learning, all within a single platform. It offers a Cursor-like experience to edit evaluations-as-code against a YAML schema, enabling users to version evaluations across checkpoints, replace manual effort with AI-generated diffs, and compare evaluation runs on tight execution loops to align them with proprietary data. doteval supports the specification of fine-grained rubrics and aligned graders, facilitating rapid iteration and high-quality evaluation datasets. Users can confidently determine model upgrades or prompt improvements and export specifications for reinforcement learning training. It is designed to accelerate the evaluation and reward creation process by 10 to 100 times, making it a valuable tool for frontier AI teams benchmarking complex model tasks.
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Reins
Reins is a global mobility payments and orchestration platform powering end-to-end payment programs across fuel, EV charging, parking, and tolls.
We serve fuel retailers, fleet operators, mobility providers, and payment players through a single unified layer that supports both closed-loop and open-loop models.
Reins is also the gateway for banks, fintech, and digital payment providers entering the mobility space. We enable them to extend existing card programs into fully governed mobility and fleet solutions, connect to acceptance networks, and manage complex payment flows with real-time control, risk management, and full settlement visibility, without building mobility infrastructure from scratch.
Built on a three-layer architecture, Reins combines API-first infrastructure, advanced payment control, and commercial growth tools, including loyalty, pricing, segmentation, and partner management.
The result: faster scaling, better control, and turning payments into a growth engine.
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Peta
Peta is an enterprise-grade control plane for the Model Context Protocol (MCP) that centralizes, secures, governs, and monitors how AI clients and agents access external tools, data, and APIs. It combines a zero-trust MCP gateway, secure vault, managed runtime, policy engine, human-in-the-loop approvals, and full audit logging into a single platform so organizations can enforce fine-grained access control, hide raw credentials, and track every tool call made by AI systems. Peta Core acts as a secure vault and gateway that encrypts credentials, issues short-lived service tokens, validates identity and policies on each request, orchestrates MCP server lifecycle with lazy loading and auto-recovery, and injects credentials at runtime without exposing them to agents. The Peta Console lets teams define who or which agents can access specific MCP tools in specific environments, set approval requirements, manage tokens, and analyze usage and costs.
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MintMCP
MintMCP is an enterprise-grade Model Context Protocol (MCP) gateway and governance platform that provides centralized security, observability, authentication, and compliance controls for AI tools and agents connecting to internal data, systems, and services. It lets organizations deploy, monitor, and govern MCP infrastructure at scale, giving real-time visibility into every MCP tool call, enforcing role-based access control and enterprise authentication, and maintaining complete audit trails that meet regulatory and compliance needs. Built as a proxy gateway, MintMCP consolidates connections from AI assistants like ChatGPT, Claude, Cursor, and others to MCP servers and tools, enabling unified monitoring, blocking of risky behavior, secure credential management, and fine-grained policy enforcement without requiring each tool to implement security individually.
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