Bewize provides a private management platform that lets enterprises provision and govern AI coding agents—such as Hermes, Claude Code CLI, and OpenAI Codex CLI—under a centralized control plane.
Funding
Funding not disclosed
Founders
Product
Problem
Enterprises using AI coding agents face uncontrolled deployment, data leakage, and opaque cost tracking because agents run in personal accounts or unmanaged environments. This creates security, compliance, and budgeting challenges for organizations that need to keep work and model spend within corporate boundaries.
Solution
Bewize offers a private management platform that centralizes the provisioning and governance of AI agents such as Hermes, Claude Code CLI, and OpenAI Codex CLI. Each employee, team, or operational role receives a dedicated agent identity whose runtime, memory, tools, storage, and credentials are defined by administrators. The platform enforces tenant‑isolated execution, ensuring that memory, sessions, logs, and secrets remain within the company’s chosen deployment boundary, whether on‑prem or in a private cloud. Administrators gain full visibility into model usage, token consumption, and scheduling, allowing precise attribution of AI spend. A single control plane lets ops teams create, pause, update, and audit agents, while policy‑driven skill packs and approved runtimes keep functionality aligned with corporate standards.
Target Audience
Bewize is aimed at large enterprises, software development organizations, and IT/operations teams that need to deploy AI coding agents at scale while maintaining security, compliance, and cost visibility.
Features
- Central registry assigning managed AI agents to individual users, teams, or roles with distinct runtime identities
- Tenant‑isolated execution that separates memory, browser profiles, logs, and secrets per agent
- Policy‑driven runtime selection supporting Hermes, Claude‑style, and Codex‑style agents under a unified model
- Secure integration with approved storage, credentials, and skill packs for controlled resource access
- Observability dashboard attributing runs, schedules, token usage, and model costs to specific agents
- Lifecycle controls (wake, stop, schedule, rollback) and staged runtime releases managed from a single control plane
- Option for private deployment within on‑prem or enterprise‑controlled infrastructure