Private preview · A Momentum AI platform layer

Hive: AI-Native Workflow Orchestration for Software Development.

Compose long-running SDLC workflows using AI agents, triggers, approvals, integrations, and verification checkpoints — designed for teams that ship continuously.

139 SDLC capabilities Event-driven workflows Human approvals Verification-first execution Enterprise integrations

Live visualizer

A real workflow, running in front of you.

Watch Hive carry a Jira ticket through technical planning, implementation, verification, human-approved merge, and release — pausing on real-world events and resuming when they fire.

Workflow · ticket-to-release
Running Waiting Verified Complete Pending

Simulated visualization. Every step maps to a real, composable Hive capability.

Workflow library

Eight workflows your team can compose today.

Every workflow is built from reusable SDLC capabilities, wired to your existing event sources, and gated by the human approvals your org already trusts.

How Hive works

Trigger. Compose. Execute. Continue.

01

Trigger

An event starts the workflow — a Jira ticket created, a PR merged, a CI build passing, a Slack command, an API spec change, or a security finding.

02

Compose

Hive chains together SDLC automation capabilities — drawn from a library of 139 reusable, composable building blocks.

03

Execute + Verify

AI agents perform work behind verification checkpoints — tests, policy checks, evaluators, and human approvals — before progressing the workflow.

04

Continue on events

Workflows pause and resume on real-world events — PRs merging, CI passing, approvals completing, deployments finishing. Built for long-running work.

Integrations

Built to support the stack you already run.

Hive plugs into the tools your engineers, platform teams, and security teams already operate.

GitHub GitLab Jira Slack Linear CI/CD Kubernetes OpenAPI Docker AWS Azure GCP

Positioning

Hive is not another AI coding assistant.

It is the orchestration layer for autonomous software development operations — designed to run long after a coding session ends.

Dimension
Traditional AI coding tools
Hive
Trigger model
Prompt-driven
Event-driven
Lifetime
Single-session
Long-running
Scope
Coding-focused
Lifecycle-wide
Initiation
User-triggered
Integration-aware, event-aware
Memory
Limited workflow memory
Persistent across the workflow
Quality model
Best-effort output
Verification-first, human-in-the-loop

Private preview

See Hive at the Momentum AI booth.

We're previewing Hive with a small group of design partners. Request access — or book a 1:1 walkthrough with our team at the conference.