“Make me a hero in board meetings. That's a $50K product.”
CTO · Series C startup
Build the AI-native Engineering org, with Tetriz
It moves every engineer up the AI adoption curve, so AI stops being a pilot and starts being how the team ships
Book a demo
Four stages, one direction
Tetriz maps where every engineer is on the AI curve, and moves them up
A few engineers experimenting
No org-wide picture of who's using what
Experimenting
A few engineers experimenting
No org-wide picture of who's using what
Adopting
Most engineers have a license
Use is uneven, no one knows what's working
Mastering
AI is in the daily loop
Quality and ROI are tracked, tooling decisions are data-driven
Leading
AI is how the team ships
Adoption is universal, ROI is reported to finance every week
Three signals that turn AI use into engineering craft
Saturation
Catch sessions running out of context before they ship broken code
Saturation
Catch sessions running out of context before they ship broken code
Prompt quality
Coach prompts toward clarity, specificity, and grounding, at the session level
Effective sessions
Surface which sessions actually shipped code, and which got abandoned
The agentic platform
Coming soonTetriz is an agentic platform, four agents pull these levers, each running a different engineering job
Meet the four agents
The proof, in adoption, impact, and ROI
Three layers of numbers, all moving in the same direction
Adoption
How much engineering work AI is actually doing, across every tool in use.
- % PRs attributable to AI
- % code (LOC) attributable to AI
- % issues closed with AI
- Coding-tools split across Cursor, Claude, Copilot, Codex
Impact
ROI
Adoption
How much engineering work AI is actually doing, across every tool in use.
- % PRs attributable to AI
- % code (LOC) attributable to AI
- % issues closed with AI
- Coding-tools split across Cursor, Claude, Copilot, Codex
Impact
Whether AI made engineers faster and code better, or just added more of it.
- PR review TAT, pre vs post AI
- First-pass merge rate on AI code
- Code churn on AI-attributed code
- Bugs traceable to AI sessions
ROI
Engineering hours saved, rolled up to dollars finance can read.
- Time recovered per engineer
- Loaded cost per engineer
- Dollar savings, org-wide
- Auditable methodology card for finance
Every engineer becomes AI-native,
one session at a time
Personal Leverage Scores from real merged PRs, with prescriptive coaching on what to sharpen each session
[QUALITY]
Input Quality Scorecard
Six-dimension prompt quality per session, 7-day trend, weak spots flagged.
[ATTRIBUTION]
Session-to-PR linkage
Tracks which AI sessions produced which merged code. No manual tagging.
[EFFICIENCY]
Token-waste visibility
Surfaces where tokens burn without value, week over week.
[COACHING]
Personal coaching
Strongest dimension surfaced first. Targeted suggestions on what to lean into next.
One connection, reads every tool
Role-based access, audited connections, zero new policy
Claude Code
GitHub
GitLab
Bitbucket
Jira
Slack
Google Workspace
Per engineer pricing
Lite
Coming Soon$9/seat/month
Bring Your Own Key (BYOK) model.
- All four agents
- Coding, Issue, and PR connectors
- Bring your own LLM API key
- Email support
Pro
Recommended$29/seat/month
Tetriz-hosted LLM, end to end.
- Everything in Lite, plus:
- Tetriz-hosted LLM access
- SSO (Google / Microsoft)
- Audit log
Max
$49/seat/month
Google Workspace and Slack signals.
- Everything in Pro, plus:
- Google Workspace connector
- Slack connector
- Priority support
Enterprise
Custom
For 100+ engineer orgs and bespoke needs.
- Everything in Max, plus:
- SAML / Okta SSO
- Multiple concurrent connectors
- Org-wide attribution
- Custom data export
- Dedicated support agent
What CTOs and Leaders told us
And why we built Tetriz
“People expect magic. You must now do what you did yesterday with one-tenth of the people.”
CTO · Fintech, >$1Bn TPV
“You don't want to measure the quality of input. You want to measure the quality of output.”
CTO · Developer Tools platform
“We are doing a lot of stuff but are blind on effectiveness.”
VP Eng · Enterprise SaaS
“I don't have a good way of doing metrics-based AI analysis. It is definitely vague right now.”
CTO · B2B SaaS
“There's a year-on-year productivity increase you need to show. 20%. You can't just say they're now writing 120 lines of code.”
TPM · FAANG
“The primary bottleneck is code reviews. We need ways to speed this up.”
Engineering Leader · B2B SaaS
“Specific instructions were given. They didn't do it. Just generated some code, it's working, so they just push it.”
Engineering Leader · Mid-market SaaS
“Right now there is no tool. I have to manually go and ask the status. I have to actually follow up.”
Engineering Leader · Enterprise
“DORA is not enough. We need a post-shipment quality metric.”
Engineering Leader cohort synthesis