Replace Jira. Manage AI Agents Alongside Engineers.

Atlassian's bundle — Jira Software, Confluence, Bitbucket, Trello, and a long tail of paid add-ons — hits $200K-1M/year for mid-market eng orgs. Aeion Forge replaces Jira's project management, Confluence's knowledge base, and Bitbucket-style PR review with native AI agent coordination at a flat rate for each module. Built for the next decade where AI agents work on tickets alongside humans — same backlog, same audit trail, same sprint board.

Aeion Forge ↔ Jira/Atlassian Stack Mapping

Project + Sprint Management

Backlogs, sprints, and kanban boards run on the same agile ceremonies your team already knows — scrum ceremonies, velocity tracking, and burndown charts included — so switching off Jira doesn't mean re-training anyone on how sprints work. Read Forge →

Issues + Epics + Stories

Full issue hierarchy with custom fields, labels, components, fix versions, and story points, plus a self-healing atomic counter that hands every new ticket a clean identifier like `PROJ-42` — even with a dozen agents filing issues at once.

AI Agent Coordination

AI agents are first-class team members here, not a bolt-on integration — they claim tickets, update status, link commits, and file PRs on the same backlog and audit trail as your human engineers. "Claude Code worked on this ticket and shipped commit X" is a native workflow, not a custom integration you have to build.

Knowledge Base (Confluence)

Per-project knowledge lives in Workspace with real-time collaborative editing — architecture decisions, runbooks, retros, and design docs, searchable the moment they're written instead of scattered across a wiki nobody maintains. Read Workspace →

PR + Code Review

Native GitHub, GitLab, and Bitbucket integration links every pull request straight to its ticket — replace Bitbucket outright, or keep your existing GitHub Enterprise setup and just add the ticket linking.

Reporting + Velocity

Per-team velocity, per-engineer throughput, per-sprint completion, and cycle-time analytics update automatically, and AI flags velocity anomalies and coaching opportunities before they show up in a retro three sprints too late.

AI Sprint Planning

AeionClaw drafts sprint plans directly from your backlog, velocity, and team capacity — surfacing blockers and dependency risks and suggesting reprioritization before the sprint starts, then drafting the retro once it ends.

Cross-Team Coordination

Per-team boards roll up into cross-team dependency tracking and critical-path analysis, with epic-level rollups across teams — replacing what most orgs bolt on Advanced Roadmaps for.

The Atlassian Stack Math

Typical Atlassian stack for 100-engineer team:

Jira Software Premium: $15.25/user/month × 100 = $18K/year
Jira Advanced Roadmaps: $11/user/month × 100 = $13K/year
Confluence Premium: $11.55/user/month × 100 = $14K/year
Bitbucket Premium: $6/user/month × 100 = $7K/year
Per-add-on (ScriptRunner, Tempo, Refined, BigPicture): $15-50K/year
Atlassian Connect apps: $20-100K/year
Per-license overage for non-engineer access: $10-30K/year
Per-IP allowlist + SSO add-ons: $20-50K/year
Total: $120-280K/year for mid-market 100-engineer team

Enterprise tier: $50-150K base + per-user, hits $400-1M/year for 500-engineer org.

Aeion replacement:

Aeion Forge: included free with any module
Aeion Workspace: $49/mo flat, unlimited users — $588/year
Aeion Collab: $49/mo flat, unlimited users — $588/year
LLM inference (sprint planning + retro AI): $5-15K/year
Migration: $30-100K one-time
Total Year-1: ~$36-116K

Year-1 savings: $5-245K (widens fast once migration is a sunk cost) + cross-functional users free at platform tier.

The bigger story: AI-native PM. Jira added "Atlassian Intelligence" as a $5-10/user/month add-on with limited capability. Aeion Forge is built for AI agents as first-class workers — agents file tickets, claim them, work on them, link commits, mark complete, get retroed. Same backlog as humans. This is structurally what teams need over the next 5 years; Jira retrofitted it as an add-on.

The AI Agent Story — Why Forge Beats Jira for the Next Decade

Atlassian Intelligence (Jira's AI add-on):

Summarize tickets
Draft sprint descriptions
Suggest issue-type
Generate sprint goals
Per-feature pricing

Aeion Forge (AI agents as first-class team members):

AI agents claim tickets via API (same auth as humans)
AI agents update status as they work
AI agents link commits + PRs to tickets
AI agents file sub-tickets when work needs decomposition
AI agents request human review when stuck
AI agents document their own work in retros
AI agents flag blockers proactively
Every AI action audit-logged with full reasoning

Practical workflow:

Engineer creates ticket: "Add OAuth2 to admin shell" ↓ AeionClaw reads ticket + codebase + similar past tickets ↓ Claw files 3 sub-tickets: schema migration, route handler, tests ↓ Claw claims schema migration sub-ticket ↓ Claw drafts the migration SQL + opens a PR ↓ Engineer reviews + merges OR requests changes ↓ Claw marks sub-ticket done with PR link ↓ Claw moves to route handler sub-ticket ↓ [repeat] ↓ Final retro: Claw drafted, engineer reviewed + approved

This is the same workflow today's engineers do — but with AI agents as additional team members on the same board. Jira can't do this without significant custom integration; Forge ships it native.

Per-team velocity impact in test deployments: