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CloudByte PMS

AI session telemetry, prompt governance, and productivity analytics for Claude Code and other AI coding tools.

CloudByte PMS is the analytics and management layer for AI-assisted engineering teams. A lightweight sync agent captures every Claude Code, GitHub Copilot, and Cursor session — prompts, responses, tokens, commits, and machine health — and surfaces per-developer adoption, cost per session/PR, ghost-seat detection, and prompt governance in one org-scoped dashboard with RBAC. BYOK Anthropic keys, self-host and air-gap options. Free for teams up to 5 developers.

What it measures

Per-developer session capture across Claude Code, GitHub Copilot and Cursor
Cost per session, per developer, per project and per PR — all four Anthropic token types
Ghost-seat detection via per-seat heartbeat; roughly 24% of seats in a typical rollout are never activated
Commit-level AI attribution: AI-assisted vs unassisted work by the same developer
DORA-metric correlation against AI-assisted commit ratios

Governance and security

Skills library for prompt standardisation and governance
AI data-leak prevention — alerts on secrets and sensitive prompts
Team Wide Security Policy Implementation.
RBAC and SSO with org-scoped multi-tenant isolation
SOC 2 Type II in progress (target Q4 2026); GDPR DPA and BAA available today

Integrations

Claude Code · GitHub Copilot · Cursor · GitHub · GitLab · Bitbucket · Linear · Jira · Slack · Anthropic API (BYOK)

A startup from India that is founded by Pranav Lakhani, Brijesh Shah.

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Pricing:

Freemium
Free Trial
$15.0 / Monthly
Official Pricing

Platforms:

SaaS
Windows
MacOS

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CloudByte PMS Reviews and Details

This page is designed to help you find out whether CloudByte PMS is good and if it is the right choice for you.

#Developer Tools #Engineering #AI Security #AI Cost Management #Ai Agent Skill Builder #AI

Screenshots and images

Login Page //
2026-08-13
Integrations. //
2026-08-13
Security Policy Setup //
2026-08-13
Skill Hub //
2026-08-13
Team Prompt & Session -> Observation //
2026-08-13

Features & Specs

Prove your AI tools are actually paying for themselves

Renewal comes round and nobody can show whether Claude Code made the team faster. CloudByte PMS maps per-developer session data to commits and merged PRs, so you walk into that meeting with a defensible number instead of a hunch.
Find the seats nobody is using

Around 24% of seats in a typical rollout are never activated — provisioned, billed, and completely dormant. A per-seat heartbeat surfaces zero-session seats within days of provisioning, not at renewal.
Stop secrets leaking into AI prompts

Developers paste API keys, database credentials and tokens into AI tools every day, and nobody finds out until it matters. AI DLP scans prompts and responses, alerts on secrets and sensitive content, and keeps a full audit trail.
Standardise the prompts that actually work

Most teams have a dozen different prompts doing the same job, with the best performing several times better than the worst. The skills library captures the good ones and governs what the team ships.
Connect AI activity to delivery outcomes

DORA metrics tell you delivery improved; they cannot tell you AI caused it. Comparing AI-assisted against unassisted commits from the same developer, on the same codebase, isolates the real contribution.
Catch broken agent installs before they cost you a sprint

A developer whose agent silently stopped syncing looks identical to one who stopped using AI. Agent health monitoring flags stalled installs and version drift before they distort your data.
Answer the compliance question without a fire drill

RBAC, SSO and org-scoped isolation, with exportable audit trails and process reporting. BYOK Anthropic keys, self-hosted and air-gapped deployment for teams whose data cannot leave the building.

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Questions & Answers

As answered by people managing CloudByte PMS.

What makes CloudByte PMS unique?
CloudByte PMS is the analytics and management layer for AI-assisted engineering teams. A lightweight sync agent captures every Claude Code, GitHub Copilot, and Cursor session — prompts, responses, tokens, commits, and machine health — and surfaces it in one org-scoped dashboard with RBAC.

What no generic engineering-analytics tool gives you:
- Session-level telemetry — not just that AI tools are used, but how, by whom, and at what cost
- Per-developer adoption and cost per session, per project, per PR
- Ghost-seat detection — find paid seats nobody is using
- Prompt governance and a shared skills library across the team
Why should a person choose CloudByte PMS over its competitors?
Platforms like Jellyfish measure engineering output broadly; native Copilot analytics only cover Copilot. CloudByte PMS is purpose-built for AI coding telemetry across tools — Claude Code, GitHub Copilot, and Cursor in one dashboard.
- Commit-level AI attribution — AI-assisted vs. not, for the same developer
- DORA-metric correlation with AI-assisted commit ratios
- Ghost-seat detection and cost tracking across all four Anthropic token types
- BYOK Anthropic keys, self-hosted, and air-gapped deployment for stricter environments
- Free for teams up to 5 developers
How would you describe the primary audience of CloudByte PMS?

Engineering managers and CTOs at software teams of 10–200 developers who have rolled out AI coding tools and now need to answer: who's actually using them, what are they costing, which seats are idle, and is delivery actually improving? Reviewers and platform teams also use it for prompt governance and auditing.
Which are the primary technologies used for building CloudByte PMS?
- Backend: Node.js + PostgreSQL + VectorDB
- Dashboard: React + TypeScript
- Deployment: Docker, AWS infrastructure managed with Terraform
- Integrations: native Claude Code hooks and the Anthropic API (BYOK) Cursor Integration
What's the story behind CloudByte PMS?

CloudByte PMS started when Pranav and Brijesh saw the same pattern across every engineering team adopting AI coding tools: shadow AI everywhere, costs nobody could track, and usage data trapped in silos — one tool per vendor dashboard, no single picture of what developers were actually doing.

They believed this problem deserved more than a point solution. Their vision: a common platform for AI engineering — telemetry, security, and governance in one place — where every team, whatever tools they use, can see adoption, control costs, and set guardrails without slowing developers down.

That vision became CloudByte PMS: a lightweight sync agent capturing every Claude Code, GitHub Copilot, and Cursor session, prompt, and commit into one org-scoped dashboard — built to make AI-assisted engineering visible, accountable, and safe for everyone.

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