Overview
Beezi AI is an orchestration layer for engineering teams that already use AI in their delivery workflow but have no way to standardize, measure, or control it. Instead of being another coding assistant, it sits above the assistants — turning ambiguous tickets into structured prompts, routing tasks to the right model, and tracking token spend per feature so leaders can see where AI is actually paying off.
The product is built around a simple observation: most teams adopt Cursor, Copilot, or Claude Code without changing how tickets are written or how usage is reported. The result is invisible AI spend, inconsistent code quality, and no clear answer to "is this working?" Beezi targets that gap rather than competing for the IDE itself.
It plugs into Jira, GitHub, Slack, and the LLM providers your team already pays for, then layers in Smart Tickets, model routing, RBAC, and an analytics hub. The pitch most engineering leaders respond to: "from setup to shipping in 20 minutes" — meaning the platform sits in front of existing tools rather than asking the team to migrate.
Key Features
Smart Ticket System — Scores incoming tickets for ambiguity, runs assisted clarification workflows, and turns vague requests into structured prompts. Output is a ticket your AI tools can act on without round-tripping back to the PM.
Intelligent Model Routing — Automatically picks the right LLM (OpenAI, Anthropic, Google Gemini) per task based on reasoning depth, speed, and cost. Reduces overpaying for premium models on simple tasks.
Codebase Learning — The platform studies your existing code patterns and conventions, so generated work matches your team's style rather than producing generic AI-flavored code.
Parallel Task Execution — Multiple tickets get processed concurrently, which matters most for teams trying to clear backlog rather than just speed up individual PRs.
Analytics Hub — Real-time dashboards for token spend, cost per task, monthly AI budget vs. actual, adoption rates by team, and ROI signals. The most useful screen for engineering leaders is "what did we spend AI on this sprint."
Pull-request workflow support — Beezi's public workflow references a PR stage, but specific PR-comment limits by plan are not publicly verified. Avoid relying on Free/Pro PR-comment caps unless confirmed in the app or sales materials.
Enterprise Security — SOC 2 Type II, ISO 27001:2022, and ISO/IEC 42001:2023 certifications. Optional self-hosted deployment for organizations that can't send code outside their VPC.
Access control — Beezi publicly references role-based access setup and enterprise access control. Branch-strategy controls and exact plan placement are not publicly verified, so confirm them with Beezi before relying on them.
Integration Guide
Beezi's value comes from how it composes with the tools engineering teams already use. The integrations fall into four layers:
Project management (where tickets live)
- Jira — Most common deployment. Smart Tickets read from Jira, and analytics map back to Jira boards.
- Azure DevOps — Native support for both work items and pipelines.
- The platform doesn't replace your project tracker — it reads tickets, scores them, and writes structured prompts back.
Source control (where code lives)
- GitHub — PR comments, code-level analytics, repository scope.
- Bitbucket — Same surface area, alternative for teams on Atlassian's stack.
- Azure DevOps Repos — For teams already standardized on Microsoft tooling.
Communication (where teams coordinate)
- Slack — Notifications, ticket clarification prompts, AI usage alerts.
- Microsoft Teams — Equivalent surface for Microsoft-shop organizations.
LLM providers (where the actual AI work runs)
- OpenAI, Anthropic, Google Gemini are first-party connectors.
- Custom LLM providers and private LLMs — Beezi publicly says teams can bring self-hosted or private LLMs, but the exact plan boundary is not clearly published. Treat Azure OpenAI, private endpoints, and self-hosted model routing as sales-confirmed items rather than guaranteed Pro features.
- The Model Routing Optimizer chooses among connected providers per task; Beezi also describes cost-aware model control, but a separately named Token Balancer is not publicly verified.
The setup pattern most teams follow: connect Jira and GitHub first (10 minutes) → connect one LLM provider → enable Smart Tickets on a single board to evaluate before broader rollout → add Slack and analytics last. Paid teams should confirm custom LLM connectors, RBAC, and private deployment requirements with Beezi before expanding beyond the initial proof point.
Pricing & Plans
Beezi AI uses a per-user FREEMIUM model with a 25% discount for annual billing.
| Plan | Price | Users | Highlights |
|---|---|---|---|
| Free / Discover | $0/user/mo | Public sources conflict: Beezi terms mention up to 5 users, while public pricing listings describe unlimited users | Smart Ticket System, integrations, implementation plan, and limited task usage. Treat project, repo, PR-comment, and connector caps as unverified unless confirmed in-app. |
| Pro / Adopt | $30/user/mo | Not publicly specified | Includes everything in Free/Discover, plus unlimited tasks, manager analytics, Model Routing Optimizer, and 24/7 support. Verify exact seat, project, repo, and connector limits during checkout. |
| Custom | Custom | Unlimited | Everything in Pro + self-hosted deployment, enterprise security, team onboarding, priority support, SAML/OIDC SSO |
Notes worth flagging:
- The Free plan is best treated as an evaluation tier. Beezi's terms confirm a free plan with feature limitations, but the exact project, repo, connector, and RBAC caps should be verified in-app because they are not clearly listed on the public website.
- Public pricing listings put Beezi's paid Adopt/Pro-style plan at $30/user/month, making a 10-person team roughly $300/month before taxes or custom terms — still comparable to per-seat pricing for established AI coding tools, but Beezi sits at a different layer rather than competing seat-for-seat with assistants.
- No publicly accessible Beezi pricing material verified a 25% annual-billing discount; confirm annual terms directly in checkout or with sales.
- Custom (Enterprise) unlocks self-hosted deployment, which is the deciding factor for companies with strict data residency or air-gapped requirements.
Verify current numbers on the official pricing page; per-user AI tooling pricing moves more often than traditional SaaS.
Best For
- Engineering orgs running AI coding agents like Cursor, Copilot, or Claude Code who can't answer "what's our AI spend per feature?"
- Engineering leaders who need adoption metrics, ROI dashboards, and budget enforcement across multiple AI tools
- Teams running AI productivity workflows in Jira/GitHub who want Smart Tickets to standardize prompt quality
- Mid-to-large companies (15–500 engineers) where AI cost is starting to show up on the engineering budget line
- Regulated organizations needing SOC 2 / ISO 27001 / ISO 42001 compliance and optional self-hosted deployment
FAQ
Is Beezi AI a coding assistant like Cursor or GitHub Copilot?
No. Beezi sits above coding assistants rather than competing with them. It standardizes how tickets are written, routes work to the right LLM, and tracks usage and cost. Most customers run Beezi alongside Cursor, Copilot, or Claude Code, not instead of them.
What's the Free plan good for?
The Free plan includes Smart Ticket System access and limited usage, but public sources do not consistently confirm the exact user, project, repository, or LLM-connector caps. It's enough to evaluate the workflow on a single team, but the project/repo caps and the lack of RBAC make it a trial rather than a sustained free path.
How does Smart Ticket Scoring actually work?
Beezi scores incoming tickets for ambiguity (missing acceptance criteria, vague scope, unclear dependencies) and routes them through clarification workflows. The output is a structured prompt that downstream AI tools can act on more reliably than the original ticket text.
Which AI models does Beezi route between?
Out of the box, Beezi connects to OpenAI, Anthropic, and Google Gemini. The Model Routing Optimizer is publicly listed on the paid Adopt/Pro plan and selects per task based on reasoning depth, speed, and cost. Custom LLM providers and private LLM endpoints — including Azure OpenAI and self-hosted models — are referenced in Beezi materials, but confirm the exact plan tier with sales before relying on them.
Does Beezi require us to change our Jira or GitHub workflow?
No. Beezi reads from Jira/GitHub and writes structured artifacts back, but it doesn't replace either tool. The setup pattern is "connect, observe, then enable Smart Tickets on one board" — most teams keep their existing process intact.
Is the cost data accurate enough to base decisions on?
The Analytics Hub tracks token usage and cost per activity directly from the LLM providers connected to Beezi. Accuracy depends on every relevant LLM call going through Beezi's routing layer; usage that bypasses Beezi (e.g., an engineer using a personal API key in Cursor) won't show up.
Can we self-host Beezi?
Self-hosted deployment is available on the Custom (Enterprise) plan. This matters for organizations with strict data residency, air-gapped environments, or regulatory constraints that prevent code or telemetry from leaving the network.
Is Beezi secure enough for regulated industries?
Beezi holds SOC 2 Type II, ISO 27001:2022, and ISO/IEC 42001:2023 (the AI management system standard) certifications. Beezi publicly lists SOC 2 Type II, ISO 27001:2022, ISO/IEC 42001:2023, SSO, role-based access, and private/on-prem deployment language, but exact plan placement should be confirmed with sales.
What's the difference between Pro and Custom?
The paid Adopt/Pro-style plan publicly lists unlimited tasks, manager analytics, Model Routing Optimizer, and support. Unlimited projects/repos, custom LLM connectors, and RBAC should be treated as unverified until confirmed. Custom adds self-hosted deployment, SAML/OIDC SSO, team onboarding, and priority support — the differences matter mostly for organizations with strict compliance or scale needs.
Can I cancel or downgrade anytime?
Pro is a monthly or annual subscription that can be canceled or downgraded. Beezi's terms state that paid plans are billed per active seat and that paid fees are generally non-refundable; verify current downgrade, cancellation, and annual-contract terms before committing.
