Tuning Engines
Tuning Engines is a unified AI control and governance layer for teams building production intelligence across models, agents, tools, and fine-tuned systems.
It brings together the full AI lifecycle in one governed platform: inference, model routing, fallback policies, fine-tuning jobs, datasets, evaluations, model imports and exports, custom models, agents, MCP servers, reusable skills, guardrails, AGT YAML policies, data capture, runtime traces, usage analytics, API keys, billing, team roles, and integrations.
Developers get OpenAI-compatible APIs, Anthropic-compatible routes, CLI workflows, MCP access, coding-agent integrations, and resource catalogs for models, agents, tools, and skills. Teams can connect Claude Code, OpenCode, Aider, Cline, Roo, Continue.dev, Cursor, VS Code, Windsurf, and other AI workflows through a single governed platform.
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Dynamiq
Dynamiq is a platform built for engineers and data scientists to build, deploy, test, monitor and fine-tune Large Language Models for any use case the enterprise wants to tackle.
Key features:
🛠️ Workflows: Build GenAI workflows in a low-code interface to automate tasks at scale
🧠 Knowledge & RAG: Create custom RAG knowledge bases and deploy vector DBs in minutes
🤖 Agents Ops: Create custom LLM agents to solve complex task and connect them to your internal APIs
📈 Observability: Log all interactions, use large-scale LLM quality evaluations
🦺 Guardrails: Precise and reliable LLM outputs with pre-built validators, detection of sensitive content, and data leak prevention
📻 Fine-tuning: Fine-tune proprietary LLM models to make them your own
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AgentKit
AgentKit is a unified suite of tools designed to streamline the process of building, deploying, and optimizing AI agents. It introduces Agent Builder, a visual canvas that lets developers compose multi-agent workflows via drag-and-drop nodes, set guardrails, preview runs, and version workflows. The Connector Registry centralizes the management of data and tool integrations across workspaces and ensures governance and access control. ChatKit enables frictionless embedding of agentic chat interfaces, customizable to match branding and experience, into web or app environments. To support robust performance and reliability, AgentKit enhances its evaluation infrastructure with datasets, trace grading, automated prompt optimization, and support for third-party models. It also supports reinforcement fine-tuning to push agent capabilities further.
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Maxim
Maxim is an agent simulation, evaluation, and observability platform that empowers modern AI teams to deploy agents with quality, reliability, and speed.
Maxim's end-to-end evaluation and data management stack covers every stage of the AI lifecycle, from prompt engineering to pre & post release testing and observability, data-set creation & management, and fine-tuning.
Use Maxim to simulate and test your multi-turn workflows on a wide variety of scenarios and across different user personas before taking your application to production.
Features:
Agent Simulation
Agent Evaluation
Prompt Playground
Logging/Tracing Workflows
Custom Evaluators- AI, Programmatic and Statistical
Dataset Curation
Human-in-the-loop
Use Case:
Simulate and test AI agents
Evals for agentic workflows: pre and post-release
Tracing and debugging multi-agent workflows
Real-time alerts on performance and quality
Creating robust datasets for evals and fine-tuning
Human-in-the-loop workflows
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