Adopt AI coding with confidence, with data captured automatically from every developer machine.
Scan every prompt for PII, credentials and other sensitive data, and push AI-suggested guardrails to your whole team.
Discover every AI tool, plugin and MCP server on developer machines, and catch changes to Claude Code, Cursor and Copilot settings.
Turn vague prompts into precise ones with each developer profile, the current context and your project knowledge base, before they reach the model.
One searchable home for everything your team and its AI have learned about each project, fed back into future prompts so nobody starts from zero.
Every prompt, observation and session, with tokens, models, tickets and commits, added up per developer, project and team.
Track every commit developers make on their machines and every commit that reaches the remote, each with an AI summary linked to its ticket and sessions.
Deployment frequency, lead time, change failure rate and time to restore, measured from the first local commit and split by AI-assisted and manual work.
Real AI ROI, hours saved and adoption for every developer, with usage and prompt patterns behind them.
See where every AI token and dollar goes, split by token type and grouped by developer, project or model.
See how well each developer uses AI, not just how much: cache efficiency, prompt size, tool use, model mix and session completion.
An AI-written summary of every developer's work, a status that shows who is stuck, active, exploring or idle, and badges earned from real activity.
A library of 1,000+ approved skills, discovery of the ones that fit each project, AI-suggested skills and project skills that keep improving through two-way sync.
On the Enterprise plan, bring your own Anthropic API key, encrypted at rest with AES-256-GCM, plus GitHub OAuth, enterprise SSO and optional self-hosting on your own AWS account.
A heartbeat from every installed agent every 3 minutes, so silently broken setups and version drift are caught before they skew adoption data or cost a sprint.
We ran CloudByte AI across our own team for a month. These are the numbers it produced.
668
AI sessions tracked
1.8×
Average multiplier
14.3×
Peak project multiplier
24%
Seats never activated
Measured multiplier by kind of work
22 developers · 30 days
The same four questions every engineering leader gets asked, answered with guesswork or with data.
| Capability | Without observability | With CloudByte AI |
|---|---|---|
| DORA Metrics Attribution | Guess whether AI helped — or hurt — your DORA metrics | Attribute every commit, PR, and deploy to the AI sessions that wrote it |
| Seat Utilization | Pay for every seat and hope people are using them | See weekly activity per developer and reclaim idle seats before renewal |
| Audit Trail | Prompts and outputs disappear the moment the terminal closes | Every AI action logged with user, project, prompt, and token spend |
| SDK Integration | Stitch vendor exports and spreadsheets together by hand | Pull every metric through a REST API with an OpenAPI 3 spec and 40+ endpoints |
DORA Metrics Attribution
Seat Utilization
Audit Trail
SDK Integration
Start free in minutes, or book a demo and we will walk you through ROI, spend, and security for your rollout.
