The engineering intelligence layer for the AI era
iftrue connects AI code attribution, DORA metrics, and team health into one platform, so engineering leaders can measure what matters and make decisions with data, not dashboards.
Trusted by engineering teams shipping 2x faster
Teams winning with AI focus on four things
AI changed how code gets written. The teams getting real leverage from it changed how they manage the whole engineering system, not just the IDE.
AI accelerates the Code stage. The other 90% of lead time is where the real wins are.
- Architecture and trade-offs
- What to build, why, for whom
- Code review judgment
- "Is this good enough to ship?"
- Incident calls and rollback decisions
- Boilerplate and scaffolding
- Test fixtures and unit cases
- Mechanical refactors
- Doc generation and changelogs
- Mundane edits and migrations
Teams that flip this split, where AI drives decisions and humans rubber-stamp, ship more bugs and lose senior engineers fastest.
I have access to effective AI tools to support my work.
↑ 1.2AI tools help me work faster and reduce repetitive tasks.
↑ 1.2Our team encourages and supports productive use of AI tools.
↑ 1.1"Copilot saves me an hour a day on boilerplate. I actually have time to think about design now."
Senior Engineer · Platform team
"I'd love a clearer policy on what's okay to send to AI tools. Right now everyone improvises."
Engineer · Payments team
Know exactly how AI is reshaping your engineering output
- See which PRs and code blocks are AI-generated vs human-written
- Measure whether AI adoption is actually improving velocity, or just inflating metrics
- Compare AI impact across teams to identify best practices and risks
- Track adoption trends over time with attribution dashboards
Ship faster with confidence, not hope
- DORA metrics tracked automatically from your existing tools, zero config
- Spot bottlenecks in cycle time before they become delivery risks
- Forecast sprint outcomes based on real velocity data, not optimistic estimates
- See where engineering investment goes: features vs bugs vs maintenance
Retain your best engineers by knowing what they need
- Spot workload imbalance and burnout signals before they become resignations
- Walk into 1:1s prepared with AI-generated talking points from real activity data
- Measure developer experience with surveys that drive action, not just scores
- Plan capacity with data so no one is overloaded and nothing is understaffed
Real results from real engineering teams
- Reduction in cycle time
- 60%
- Feature velocity
- 2x
- To positive ROI
- 2 months
Works where your team already works
Connects in minutes. No code changes. No workflow disruption.
How a leading media company cut cycle time by 60%
"iftrue gave us the AI adoption metrics we were missing. We can finally tell which teams are getting real lift from Copilot and Cursor, and which ones are just shipping more churn."
Engineering Director
#1 Online Media Company in Turkey
See what your engineering org is missing
Join engineering teams that have moved from gut-feel to data-driven decisions.