Oz
Oz is a cloud-based orchestration platform for AI coding agents that lets developers and teams run, manage, automate, and scale unlimited parallel cloud coding agents without building custom infrastructure, providing programmable, auditable, and fully steerable workflows that automate repetitive development tasks and complex code changes. It enables you to launch agents from the CLI, web app, APIs, SDKs, Warp Terminal, or even mobile, orchestrate hundreds of agents in parallel with built-in audit trails, session tracking, and visibility, and monitor or interact with running agents in a shared control plane. Oz supports flexible hosting on your infrastructure or Warp’s, isolates each agent in secure environments, produces real artifacts like plans and pull requests, and handles multi-repo changes so agents can coordinate sweeping updates across large codebases.
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Forest
Forest is an operational infrastructure platform for regulated companies that helps teams run humans, AI agents, BPOs, LLMs, suppliers, and workflows together with full auditability and control. The platform acts as an operational backend between company data, compliance providers, human teams, AI agents, and tools connected through MCP. Forest includes business logic, smart actions, workflows, permissions, RBAC, audit trails, and a shared control plane deployed inside the customer’s infrastructure. It supports regulated workflows such as KYC, KYB, onboarding, document checks, beneficial-owner discovery, screening, risk routing, agent triage, and human review. Every provider call, agent step, workflow action, and reviewer decision is recorded at the record level for compliance and audit readiness. Built for regulated operations, Forest helps companies make agentic operations safer, faster, more governed, and easier to scale.
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SearchUnify
SearchUnify is an enterprise Agentic AI platform that unifies enterprise knowledge and powers autonomous AI agents across the customer support lifecycle. Built on SearchUnifyFRAG™ (Federated Retrieval Augmented Generation) and Agentic RAG, it delivers contextually accurate, real-time responses across self-service, agent-assisted, and automated support workflows.
Its product suite includes Cognitive Search, SearchUnifyGPT™, SUVA (Virtual Assistant), Knowbler, and Agent Helper. The Agentic AI Suite deploys eight specialized AI Agents handling case resolution, case classification, escalation management, knowledge management, case quality auditing, and L2 technical workflow automation.
SearchUnify supports BYOLLM, enabling LLM flexibility without vendor lock-in, and uses Model Context Protocol (MCP) for secure enterprise integrations. A built-in governance layer provides role-based access control, PII masking, and compliance with ISO 27001, HIPAA, and SOC 2.
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Agent Control
Agent Control is the open source control plane for AI agents, built to establish a new standard for governing agent behavior at scale. It solves the problem of scattered, hardcoded checks by giving teams a centralized governance layer with step-level enforcement that can be managed from a single control plane and updated in real time without touching agent code. Developers can make any function governable by adding the control() decorator, turning meaningful decision points inside an agent into independently governed control points with their own policies. When a decorated function executes, Agent Control evaluates the input or output against the active policy and returns a decision: deny, steer, warn, log, or allow. If the decision is denied, the SDK raises a ControlViolationError before the unsafe action can proceed. Policies are decoupled from code, so developers decide where to place control hooks while policy teams decide what those hooks enforce.
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